Cardiac biomarkers in Chronic Kidney Disease - UNSWorks

Cardiac biomarkers in Chronic Kidney Disease

Author:Kadappu, Krishna

Publication Date:2017

DOI:https://doi.org/10.26190/unsworks/19460

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THE UNIVERSITY OF NEW SOUTH WALES Thesis/Dissertation Sheet

Surname or Family name: Kadappu

First name: Krishna

Abbreviation for degree as given in the University calendar: PhD 1771

School: South West Sydney Clinical School

Title: Cardiac biomarkers in Chronic Kidney Disease

Other name/s: Kishor

Faculty: Medicine

The majority of patients with end stage renal disease die of cardiovascular causes. Co-morbid conditions like diabetes and hypertension are shared by both chronic kidney disease (CKD) and cardiovascular disease. To help physicians to identify high risk CKD patients, there is a need of sensitive biomarker to detect subclinical cardiac abnormalities in the early stages of CKD to permit initiation of necessary therapeutic intervention.

CKD results in several alterations in cardiovascular structure and function. We hypothesized that left atrial (LA) volume and LA strain would be sensitive markers of myocardial involvement in early CKD even In the presence of co existent diabetes and hypertension. We also hypothesized that LA metrics would be more sensitive parameters than LV parameters. We further hypothesized that LA metrics may be more sensitive than the measurement of N terminal brain naturetic peptide (NT ProBNP) to detect myocardial dysfunction in CKD patients.

To prove these congruent hypotheses, we recruited three groups of patients; the first group comprised of stage 3 CKD patients (30-59mL/min/1.73m2) with or without hypertension and or diabetes but without any previous cardiac events. Control groups were age and sex matched subjects with hypertension and or diabetes with normal renal function, without any previous cardiac history and the third group comprised of healthy adults. We additionally studied patients with diabetes and hypertension without CKD, to examine the independent effect of these conditions on LA parameters.

We found that LA metrics were significantly reduced in both the CKD group and the risk factor matched control group, compared with normal subjects. Importantly, LA metrics were significantly altered in CKD patients compared to risk factor matched subjects Indicating these parameters are sensitive markers to detect myocardial Involvement despite the presence of coexistent hypertension and diabetes. LA volume and strain also showed incremental value in diagnosing myocardial dysfunction In CKD in the presence of hypertension and diabetes. Finally we compared LA parameters with NT ProBNP; even though NT ProBNP was significantly elevated in CKD patients compared to the control group, levels were below the upper normal reference range whereas LA metrics were significantly altered compared to control group. These findings indicate that LA metrics are a sensitive, non-invasive tool to detect myocardial involvement in early CKD.

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Krishna Kishor Kadappu

A thesis in fulfilment of the requirements for the degree of

Doctor of Philosophy

South Western Sydney Clinical School

Faculty of Medicine

March 2017


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Table of content

Declaration 5 Abstract 6 List of figures 8 List of tables 9 Abbreviations 10 Acknowledgements 12 Publications 13 Chapter 1: Introduction and literature review 16

1.1Chronic Kidney Disease 17 1.1 Effect on Australian population 17

1.2 Classification 19 1.3 CKD and CVD: the relationship 20

1.3.1 Impact of CKD on the cardiovascular system 201.3.2.Underestimation of cardiovascular risk in CKD 21

1.4 Pathophysiology of cardio renal syndrome 21 1.4.1Uraemia and CVD 25 1.4.2 Cardiovascular disease due to volume overload in CKD 25 1.4.3 Renin-angiotensin aldosterone system in CKD 26

1.5 Myocardial involvement in CKD 29 1.5.1 Left ventricular hypertrophy in CKD 29

1.5.1.1 Pressure and volume overload causing LVH 31 1.5.1.2 Non haemodynamic cause of LVH 32

1.5.2 Diastolic Dysfunction in CKD 32 1.6 Diastolic function and diastolic heart failure 33 1.7 Diagnosis of diastolic dysfunction 35

1.7.1 Mitral inflow velocities 35 1.7.1.1 Clinical utility 37 1.7.1.2 Limitations 38

1.7.2 Tissue Doppler imaging to evaluate diastolic function 38 1.7.3 Left atrial volume and diastolic function 39

1.8 Strain and strain rate imaging 41 1.8.1 Left atrial strain and SR in evaluation of atrial function 44

1.8.1.1 Doppler strain and SR 44 1.8.1.2 Two dimensional strain 46

1.8.2 Clinical utility of LA Strain and strain rate 491.8.3 Left ventricular strain imaging 50

1.9 Biochemical marker of myocyte injury 51 1.10 Diagnosis of cardiomyopathy in CKD 53

1.10.1 Mitral inflow velocities in CKD 531.10.2 Tissue Doppler imaging in CKD 54 1.10.3 LA volume and CKD 541.10.4 Strain evaluation in CKD 551.10.5 BNP / NT -Pro BNP in CKD 56

1.11Future directions for risk evaluation 57 1.12 Overall Aim 58 References 61


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Chapter 2: General methodology 85 2.1 Subject groups 86 2.2 Echocardiography 87

2.2.1 Left ventricular measurements 88 2.2.2 Diastolic function 88 2.2.3 LA measurements 89 2.2.4 LA strain 89

2.2.4.1 Colour tissue Doppler strain 89 2.2.4.2 Two dimensional LA strain 90

2.2.5 Left ventricular 2D strain 90 2.3 Inter and Intra observer Variability 91 2.4 NT pro BNP assay 91 2.5 Statistical Analysis 91 Reference 93

Chapter 3. Changes in left atrial volume in diabetes mellitus: more than diastolic dysfunction? 96

3.1 Abstract 96/1016 3.2 Introduction 96/1016 3.3 Methods 96/1017 3.4 Results 96/1018 3.5 Discussion 96/1020 3.6 Limitation 96/1022 3.7 Conclusion 96/1022 3.8 Acknowledgement 96/1023 3.9 Reference 96/1023

Chapter 4: Chronic Kidney Disease is Independently Associated with Alterations in Left Atrial Function 97

4.1 Abstract 97/956 4.2 Introduction 97/956 4.3 Methods 97/957 4.4 Results 97/960 4.5 Discussion 97/962 4.6 Limitation 97/963 4.7 Conclusion 97/963 4.8 Acknowledgement 97/964 4.9 Reference 97/964

Chapter 5: Independent Echocardiographic Markers of Cardiovascular Involvement in Chronic Kidney Disease: 98 The Value of Left Atrial Function and Volume

5.1 Abstract 98/359 5.2 Introduction 98/360 5.3 Methods 98/360 5.4 Results 98/361 5.5 Discussion 98/364 5.6 Limitation 98/366 5.7 Conclusion 98/366 5.8 Reference 98/366

Chapter 6: Tissue Doppler Imaging in Echocardiography: Value and Limitations 99

6.1 TDI Measurement 99/224


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6.2Quantitative Systolic Function Assessment: s’ Velocity 99/227 6.3 Diastolic Function Assessment: e’ Velocity 99/227 6.4 Late Diastolic a’ Velocity 99/228 6.5Clinical Utility and Prognostic Implications of TDI Velocities: Systolic s’ Velocity 99/228 6.6 Stress TDI 99/228 6.7 Valvular Heart Disease 99/229 6.8 Cardiac Dyssynchrony 99/229 6.9 Early Diastolic (e’) Velocity 99/229 6.10 E/ e’ Ratio 99/229 6.11 Diastolic Stress Testing 99/229 6.12 e’ Velocity and CAD 99/230 6.13 e’ Velocity in Cardiomyopathy and Constrictive Pericarditis 99/230 6.14 a’ Velocity in Clinical Practice 99/230 6.16 Right Ventricular Function 99/230 6.17 Limitations 99/230 6.18 Conclusion 99/231 6.19 References 99/231

Chapter 7: Biomarkers of chronic kidney disease: the value of left atrial metrics 100

7.1 Abstract 101 7.2 Introduction 102 7.3 Methods 103 7.4 Results 106 7.5 Discussion 111 7.6 Limitation 114 7.7 Conclusion 115 7.8 Reference 115

Chapter 8: Conclusion 122 8.Cardiac Biomarker in CKD 123 8.1 Diastolic dysfunction 125 8.2 LV strain 126 8.3 Left atrial volume 126 8.4 LA function by strain analysis 127 8.5 NT- pro BNP 128 8.6 A ‘sensitive’ biomarker to detect cardiac involvement in CKD 128 8.7 Future direction 129 8.8 Reference 130


Declaration

ORIGINALITY ST A TEMENT

'I hereby declare that this submission is my own work and to the best of my knowledge

it contains no materials previously published or written by another person, or substantial

proportions of material which have been accepted for the award of any other degree or

diploma at UNSW or any other educational institution, except where due

acknowledgement is made in the thesis. Any contribution made to the research by

others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in

the thesis. I also declare that the intellectual content of this thesis is the product of my

own work, except to the extent that assistance from others in the project's design and

conception or in style, presentation and linguistic expression is acknowledged. '

SUPERVISOR STATEMENT

I hereby certify that all co-authors of the published or submitted papers agree to Krishna

Kishor Kadappu submitting those papers as part of his/her Doctoral Thesis.

5


6

Abstract

The majority of patients with end stage renal disease die of cardiovascular causes. Co-

morbid conditions like diabetes and hypertension are shared by both chronic kidney

disease (CKD) and cardiovascular disease. To help physicians to identify high risk CKD

patients, there is a need of sensitive biomarker to detect subclinical cardiac

abnormalities in the early stages of CKD to permit initiation of necessary therapeutic

intervention.

CKD results in several alterations in cardiovascular structure and function. We

hypothesized that left atrial (LA) volume and LA strain would be sensitive markers of

myocardial involvement in early CKD even in the presence of co existent diabetes and

hypertension. We also hypothesized that LA metrics would be more sensitive

parameters than LV parameters. We further hypothesized that LA metrics may be more

sensitive than the measurement of N terminal brain naturetic peptide (NT- ProBNP) to

detect myocardial dysfunction in CKD patients.

To prove these congruent hypotheses, we recruited three groups of patients; the first

group comprised of stage 3 CKD patients (30-59mL/min/1.73m2) with or without

hypertension and or diabetes but without any previous cardiac events. Control groups

were age and sex matched subjects with hypertension and or diabetes with normal renal

function, without any previous cardiac history and the third group comprised of healthy

adults. We additionally studied patients with diabetes and hypertension without CKD, to

examine the independent effect of these conditions on LA parameters.

We found that LA metrics were significantly reduced in both the CKD group and the

risk factor matched control group, compared with normal subjects. Importantly, LA

metrics were significantly altered in CKD patients compared to risk factor matched


7

subjects indicating these parameters are sensitive markers to detect myocardial

involvement despite the presence of coexistent hypertension and diabetes. LA volume

and strain also showed incremental value in diagnosing myocardial dysfunction in CKD

in the presence of hypertension and diabetes. Finally we compared LA parameters with

NT- ProBNP; even though NT- ProBNP was significantly elevated in CKD patients

compared to the control group, levels were below the upper normal reference range

whereas LA metrics were significantly altered compared to control group. These

findings indicate that LA metrics are a sensitive, non-invasive tool to detect myocardial

involvement in early CKD.


8

List of figures

Figure1.1 Deaths from cardiovascular disease, diabetes and

chronic kidney disease 18

Figure 1.2 Patho physiology of Cardio renal syndrome 23

Figure 1.3 LV pressure overload, LV volume overload, and myocyte

death inchronic uraemia. 24

Figure1.4 Inhibition of the renin-angiotensin system by ACE inhibitors

and angiotensin II type 1 receptor blockers 27

Figure1.5 Renin–angiotensin system cascade 28

Figure1.6 Direct and indirect actions of angiotensin-II on the atrium 29

Figure1.7 Effects of hemodynamic and non-hemodynamic factors on

the pathogenesis of LVH in CKD patients 31

Figure1.8 Pathogenesis of LVH in CKD 32

Figure1.9 Mitral inflow velocity 35

Figure1.10 Myocardial strain 42

Figure1.11 Strain rate 43

Figure1.12 LA strain by tissue Doppler imaging 45

Figure1.13 LA strain rate by tissue Doppler imaging 46

Figure1.14 LA systolic strain by speckle tracking 48

Figure1.15 LA strain rate by speckle tracking 48

Figure1.16 2 D speckle tracking Left ventricular strain analysis 51

Figure 2.1 Tissue Doppler imaging 88

Figure7.1 Left atrial 2D global strain 105


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List of Tables

Table 1.1 NKF Classification of Chronic Kidney Disease 19

Table 2.1 Grades of diastolic dysfunction 89

Table 7.1 Clinical and traditional echocardiographic characteristics of

the study population 107

Table 7.2 Left atrial and ventricular strain parameters 108

Table 7.3 Pearson correlation of parameters to NT pro-BNP 109

Table 7.4 Independent Predictors of NT pro-BNP 110

Table 7.5 Independent Predictors for CKD group 110


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Abbreviations

2D 2 dimensional

A wave Late diastolic transmitral velocity

a’ Late peak diastolic tissue velocity

ACE Angiotensin-converting enzyme

ANP Atrial natriuretic peptide

ANOVA Analysis of variance

ASE American Society of Echocardiography

BNP Brain natriuretic peptide

CAD Coronary artery disease

CHF Congestive heart failure

CKD Chronic Kidney Disease

CVD Cardiovascular disease

DT Deceleration time

E wave Early diastolic transmitral velocity

e’ Early peak diastolic tissue velocity

ESRF End stage renal failure

GFR Glomerular filtration rate

hsTnT High sensitivity troponin

LA Left atria

LAVI Left atrial volume indexed to body surface area

LV left ventricle

LVH left ventricular hypertrophy

LVMI Left ventricular mass indexed to body surface area

NKF National Kidney Foundation

NT Pro BNP N-terminal pro brain natriuretic peptide

NYHA New York heart association

PW Pulsed-wave

PVD Peripheral vascular disease


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RAAS Renin-angiotensin aldosterone system

ROI Region of interest

s’ Peak systolic tissue velocity

SD Standard deviation

SR Strain rate

SRs Systolic strain rate

SRe Early diastolic strain rate

SRa Late diastolic strain rate

TDI Tissue Doppler imaging


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Acknowledgment

It is with my great pleasure that I thank many people who made this thesis possible.

Firstly, I would like to express my sincere gratitude to my dedicated supervisor

Professor Liza Thomas. Her enthusiasm and expertise in conducting the research is

exemplary.

Her encouragement and constant guidance made this work possible. Her inspiration and

work ethics are invaluable to me. I am also indebted to my co-supervisor, Professor

John French for his support not only in guiding me through this research, but also in my

career from the beginning of my advance trainee days.

I would like to express my gratitude to the many co-authors for their invaluable

contribution to this research. My sincere appreciation goes to all the subjects who

volunteered to participate in this project spending their time. I would also like to thank

my renal colleagues especially Dr. Spicer, Dr. Aravindan and Dr. Narayan, who helped

me to recruit their patients to this study. I sincerely thank NHMRC for providing me

scholarship to conduct this research.

I would like to thank almighty God for the many good opportunity he provided to me. I

wish to express my thanks to my parents and in-laws for the love and support they

provided to me throughout this venture. A special thanks to my kids Preetham and

Priyanka for their patience and love with their hugs and laughter which made this task

easier. Last but not the least, I would like to thank my loving wife Subhashini, who had

to contribute much more time towards looking after kids and family along with her

career and for listening, persevering and loving me throughout this journey.


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Publications

During the course of this project several manuscripts and abstracts have been published

1. Kadappu KK, Cai L, Thomas D, Xuan W, French J, Thomas L. Biomarkers of

chronic kidney disease: the value of left atrial metrics (In press).

2. Kadappu KK, Abhayaratna K, Boyd A, French JK, Xuan W, Abhayaratna W,

Thomas L.J Independent Echocardiographic Markers of Cardiovascular

Involvement in Chronic Kidney Disease: The Value of Left Atrial Function and

Volume. Am Soc Echocardiogr. 2016 April ; 29(4) 359-367.

3. Kadappu KK, Thomas L. Tissue Doppler Imaging in Echocardiography: Value and

Limitations,Heart Lung Circ. 2015 Mar;24(3):224-33.

4. Kadappu KK, Kuncoro A, Hee L, Aravindan A, Spicer S, Suryanarayanan

G, Xuan W, Boyd A, French J, Thomas L. Chronic Kidney Disease is

Independently Associated with Alterations in Left Atrial Function

Echocardiography. 2014 Sep;31(8):956-64.

5. Kadappu KK, Boyd A, Haluska B, Maverick T, Thomas L. Changes in Left Atrial

volume in diabetes mellitus: More than diastolic dysfunction. Eur Heart J

Cardiovasc Imaging. 2012 Dec;13(12):1016-23.

6. Leung DY, Chi C, Allman C, Boyd A, Ng CTA, Kadappu KK, Thomas L.

Prognostic implications of left atrial volume index in patients in sinus rhythm. Am J

Cardiol 2010;105:1635-39.

7. Ng CTA, Tran DT, Newman M, Allman CJ, Vidaic J, Kadappu KK, Boyd AC,

Thomas L, Leung DY. Comparison of myocardial tissue velocities measured with

tissue Doppler imaging and two-dimensional speckle tracking. Am J Cardiol, 2008 ;

102: 784-789.

https://www.researchgate.net/researcher/38602314_Liza_Thomas

https://www.researchgate.net/publication/269173720_Tissue_Doppler_Imaging_in_Echocardiography_Value_and_Limitations?ev=prf_pub

https://www.researchgate.net/publication/269173720_Tissue_Doppler_Imaging_in_Echocardiography_Value_and_Limitations?ev=prf_pub

https://www.researchgate.net/researcher/2042643256_Ario_S_Kuncoro

https://www.researchgate.net/researcher/2013806289_Leia_Hee

https://www.researchgate.net/researcher/2042629836_Anathakrishnapuram_Aravindan

https://www.researchgate.net/researcher/7085949_Stephen_T_Spicer

https://www.researchgate.net/researcher/2035549440_Govindarajan_Suryanarayanan

https://www.researchgate.net/researcher/2042647221_Wei_Xuan

https://www.researchgate.net/researcher/39926796_Anita_Boyd

https://www.researchgate.net/researcher/39232100_John_K_French


https://www.researchgate.net/publication/259845553_Chronic_Kidney_Disease_is_Independently_Associated_with_Alterations_in_Left_Atrial_Function?ev=prf_pub

https://www.researchgate.net/publication/259845553_Chronic_Kidney_Disease_is_Independently_Associated_with_Alterations_in_Left_Atrial_Function?ev=prf_pub


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Abstracts

8. Kadappu KK, Cai L, French J, Thomas L. Left Atrial Strain an Early Marker of

Future Adverse Cardiovascular Events in Chronic Kidney Disease. ACC 2016

Chicago.

9. Kadappu KK, Cai L, Thomas D, French J, Thomas L. Left atrial strain an earlier

marker than NTproBNP to assess cardiac involvement in CKD. Heart, Lung and

circulation 2015.

10. Kadappu KK, Abayaratna W, Abayaratna K, French J, Thomas L. Left atrial and

ventricular changes in Chronic Kidney Disease. GHEART Vol 9/1S/2014 j March,

2014 e145.

11. Kadappu KK, Boyd A, French J, Thomas L. LA volume and dynamics in Chronic

Kidney Disease. Eur Heart J (2012) 33 (suppl 1): 1093.

12. Kadappu KK, Kuncoro A, Hee L, Boyd A, Aravindan A, Suryanarayanan G,

Spicer S, French J, Thomas L. Impact of Renal Dysfunction on Left Atrial

Parameters in CKD with Hypertension. Heart, Lung and Circulation, Volume 21,

Supplement 1, 2012, PageS210

13. Kadappu KK, Boyd A, Eshoo S, Haluka B, Yeo A, Marwick T, Thomas L. Left

Atrial Changes in Diabetes Mellitus More Than Diastolic Dysfunction? Heart, Lung

and Circulation, Volume 21, Supplement 1, 2012, Page S212

14. Kadappu KK, Eagale K, Rajaratnam R , Leung D et al. Can strain and strain rate

useful in assessing left ventricular filling pressure? Heart Lung and circulation 2011;

20S:S162.

https://www.researchgate.net/researcher/2042643256_Ario_S_Kuncoro





http://www.sciencedirect.com/science/article/pii/S1443950612007895

http://www.sciencedirect.com/science/article/pii/S1443950612007895


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15. Kadappu KK, Boyd A, Haluska B, Maverick T, Thomas L. Atrial Dysfunction in

diabetes mellitus using 2D strain imaging. Heart Lung and circulation

2010;19:S395.

16. Kadappu KK, Boyd A, Thomas L et al. Comparison of pulsed wave and colour

tissue Doppler derived echocardiographic estimation of left ventricular end diastolic

pressure. Heart Lung and circulation 2010;19:S406.

17. Kadappu KK, Rajaratnam R, Thomas L et al. Does time to peak E velocity versus

time to peak e’ velocity accurately predict left ventricular end diastolic pressure?

Heart Lung and circulation 2010;19:S420.

18. Kadappu KK, Boyd AC, French J, Thomas L. Can left atrial volume be used as a

surrogate marker of left ventricular end diastolic pressure? Heart Lung and

circulation 2009;18:S21.

19. Kadappu KK, Boyd AC, French J, Thomas L. Comparing tissue Doppler imaging

with speckle tracking in estimating left ventricular end diastolic pressure. Heart

Lung and circulation 2009;18:S26.

20. Kadappu KK, Boyd AC, French J, Thomas L. Comparison of tissue Doppler

“online “ versus “Offline” echocardiographic estimation of left ventricular end

diastolic pressure. Heart Lung and circulation 2009;18:S27.


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Chapter 1: Introduction and literature review


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1. Chronic Kidney Disease

Chronic Kidney disease (CKD) is one of the leading health problems in developed

countries. Almost 10-15% of the population in developed countries are at risk of

developing CKD and this percentage is much higher in people older than 65 years1.

CKD is defined as a decrease in glomerular filtration rate (GFR) and/or increase in urine

albumin excretion. Importantly, CKD is associated with a heightened risk of

cardiovascular disease (CVD) and increased all-cause as well as CVD mortality2.

1.1 Effect of CKD on Australian population

From the Kaiser permanente renal registry, which evaluated 1,120,295 from 1996 to

2000 with median follow up of 2.84 years, it was noted that in a diverse adult

population, a reduced eGFR was associated with increased risk of death, cardiovascular

events, and hospitalization independent of known traditional risk factors3. Thus, CKD

and CVD are both serious conditions, independently contributing to poor health and

affecting millions of Australians, often leading to further health complications,

disability, loss of quality of life and premature death4. In individuals where CKD is co

existent with CVD, a significant increase in adverse events is observed5.

The report from the National Centre for Monitoring Vascular Diseases at the Australian

Institute of Health and Welfare in 2014 demonstrated the following6

• In 2011, CVD, diabetes and CKD together resulted in 52,899 deaths, which is 36% of

all causes of mortality. Sixty one percentage of all deaths had at least 1 of these

conditions as an underlying or associated cause of death.

• CKD was the underlying cause of 2.1% of all deaths and was an underlying or

associated cause of 14,842 deaths, (10% of all causes of mortality).


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• Twenty seven percent of diabetes deaths were associated with CKD and 64% of

diabetes deaths were due to CVD.

• Fifty six percent of CKD deaths were due to cardiac causes; of that 29% was

associated with heart failure and cardiomyopathy, while the remaining other 27%

were due to coronary artery disease.

Fig:1.1 Deaths from cardiovascular disease, diabetes and chronic kidney disease

and their relationships listed as cause of death from 2011. The overlap between the

conditions had been demonstrated diagrammatically6 (Source AIHW national

mortality database).


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1.2 Classification of CKD

In 2002, the National Kidney Foundation (NKF) published clinical practice guidelines

on evaluation, classification, and risk stratification in CKD7. The key to any staging

system is that each stage of the disease process is associated with important prognostic

or treatment implications and in CKD patients, cardiovascular risk was one element that

decided the staging system, particularly with regard to prognosis. In these guidelines,

CKD is defined as either

(1) Kidney damage for ≥3 months, as confirmed by kidney biopsy or markers of kidney

damage, with or without a decrease in GFR,

(2) eGFR <60 mL/ min−1 per 1.73 m2 for ≥3 months, with or without kidney damage.

The NKF further classifies CKD into 5 stages of CKD, based on the level of kidney

function, regardless of the specific diagnosis. (Table1. 1)7

Stage Description GFR (mL per minute per 1.73 m2)

1 Kidney damage with normal or elevated GFR ≥90

2 Kidney damage with mildly decreased GFR 60-89

3 Moderately decreased GFR 30-59

4 Severely decreased GFR 15-29

5 Kidney failure <15

Table 1.1 NKF Classification of Chronic Kidney Disease7


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1.3 CKD and CVD: the relationship

It is a well-known fact that individuals with CKD are more likely to die of

cardiovascular causes than of end stage renal failure (ESRF)8. Forty percent of newly

diagnosed ESRF patients have coronary artery disease (CAD) and 21% have peripheral

vascular disease (PVD)9. It was noted that the risk of cardiovascular death in patients

with mild renal failure is increased 1.7-fold compared to the age adjusted normal

population3. The effect of renal failure with a 10 ml/min decrease in eGFR, is linked to

a 7% increase in the risk of de novo atherosclerosis and CVD10. It was noted that even

early stages of CKD are high-risk states for adverse CVD outcomes7. There are several

landmark publications, which have established that estimated eGFR <60 mL/min/1.73

m2 is associated with a graded increase in cardiovascular disease risk3, 11. The presence

of CKD heightens an individual’s risk for CVD incidence3, death from CVD12 and all-

cause mortality12, 13. Cardiovascular risk further increases when eGFR declines below a

threshold of 45–60 ml/min/1.73 m2 14. The presence of a low eGFR, regardless of

whether in stages 3-5 of CKD, identifies an individual with a high burden of

cardiovascular risk factors that may not otherwise be accounted for3. Hence, recognition

that these individuals are at higher risk is critical. Weiner and Sarnak in their review

noted that some cohort studies suggested that an eGFR <60 mL/min/1.73 m2 or urine

albumin creatinine ratio >30 mg/g may yield equivalent coronary risk similar to a

patient with known coronary disease or diabetes15.

1.3.1 Impact of CKD on the cardiovascular system

Some CVD events, such as myocardial infarction and stroke, can be immediate life-

threatening events, whereas a chronic condition, such as CKD, persists over a long time.

Hence CKD patients require long term monitoring and intensive management that


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impose a substantial burden on both the community and the health-care system.

Modifying and controlling risk factors early in the disease process not only reduces the

risk of adverse events but also has a favourable impact on disease progression and the

development of complications, leading to large health gains for the population.

In summary, there are complex causal relationships between CVD and CKD. These, in

combination with shared risk factors like diabetes, hypertension and

hypercholesterolemia, often result in CKD and CVD occurring together in an

individual, and may lead to more severe manifestations of both individual conditions

and an overall poorer prognosis3.

1.3.2. Underestimation of cardiovascular risk in Chronic Kidney Disease

The probability of future CVD events in the general population can be estimated with

reasonable accuracy using the Framingham equation which was derived from the

Framingham study cohort16. However, despite being robust in numerous situations, this

equation often underestimates cardiovascular events among adults with stage 3 and 4

CKD without clinical CVD17. Both “traditional” and “CKD related” (non-traditional)

CVD risk factors may contribute to this increased risk. Although CKD is strongly

linked with CVD, it remains to be determined whether this strong association is simply

due to shared CVD risk factors or due to unique traits consequential to CKD. Earlier

studies showed, classical risk factors, such as age, hypertension or diabetes do not fully

account for the increase in cardiovascular risk in CKD patients3, 12, 13.

1.4 Pathophysiology of cardio renal syndrome

CKD is associated with increased cardiovascular mortality and morbidity, particularly

related to ischemic heart disease and cardiomyopathy leading to heart failure18. Severity


22

and incidence of coronary artery disease is inversely proportional to glomerular

filtration rate19. Along with other traditional risk factors for coronary artery disease,

inflammation, oxidative stress20-23 along with mineralocorticoid excess in CKD24 are

responsible for increased severity of coronary artery disease. Abnormal bone and

mineral metabolism in CKD are also partially responsible for this25. The prevalence of

congestive heart failure increases with associated reduction in kidney function26.

Cardiomyopathy in CKD can be attributed to both pressure and volume overload, as

well as CKD associated factors which alter the myocardium. Hypertension, which is a

common cause or consequence of CKD results in significant pressure overload and

maladaptive left ventricular changes. Moreover, the potential increased circulatory fluid

overload from CKD27 would also additionally contribute to these maladaptive cardiac

changes. Associated factors like activation of the autonomic nervous system and of the

renin-angiotensin pathway5, stimulation of hyper trophic and profibrinogenic factors28

additionally contribute to the cardiomyopathy (figure 1. 2).


23

Fig: 1.2 Patho physiology of Cardio renal syndrome (Adapted from Herzog CA et

al. Kidney Int. 2011)5. ADH-antidiuretic hormone; ANP- atrial natriuretic peptide;

EPO- erythropoietin; IL1 – interleukin 1; KIM 1- kidney injury molecule 1; N-GAL-

neutrophil gelatinase associated lipocalin; OSAS- obstructive sleep apnea syndrome;

SNS- sympathetic nervous system; TNF-α- tumor necrosis factor; TZD-

thiazolidinediones; VSMC- vascular smooth muscle cell.

Histological studies have shown that there is pronounced interstitial myocardial fibrosis

in CKD5. This is due to imbalance between exaggerated collagen synthesis and

depressed collagen degradation in CKD. Increased myocardial fibrosis, in combination

with other systemic processes, including hyperparathyroidism, malnutrition and other

changes consequent to uremia, finally lead to myocyte death (Figures 1. 3). These are

discussed in details in following sections.


24

Fig:1.3 LV pressure overload, LV volume overload, and myocyte death in chronic

uraemia. Parfrey P and Foley RN. JASN; 199929.

The traditional cardiac risk factors, including hyperlipidaemia, hypertension, and

diabetes mellitus were a major focus in evaluation of CKD in the past. It was also

shown patients with 1st or 2nd degree relative with CKD have a higher incidence of

CKD30, 31. It was also shown that there is increased prevalence of CKD in females due

to better recall, familial aggregation, matrilineal, mitochondrial mutations and increased

risk for hypertension31 . A cross sectional study among 74000 patients in Norway

between 1995 and 1997 showed other cardiac risk factors like obesity, physical

inactivity and smoking are also risk factors for CKD32.

http://jasn.asnjournals.org/content/10/7/1606/F3.large.jpg


25

1.4.1 Uraemia and CVD

As mentioned above, traditional risk factors for CVD are altered by the uremic state,

such as dyslipidaemia, prothrombotic factors and hyperhomocysteinemia as well as

factors associated with chronic uraemia such as hemodynamic overload, anaemia,

increased oxidant stress, hypoalbuminemia, and divalent ion abnormalities. These

uraemia-related risk factors also contribute to cardiovascular risk as mentioned

previously29, and these co existent risk factors result in increased coronary

atherosclerosis and ischemic heart disease in CKD patients33. They also predispose to

abnormal coronary perfusion and atherosclerosis29. Disorders of coronary microvascular

perfusion predispose to the development of cardiomyopathy, which in turn worsens

microvascular disease34. It is noted that in 27% of haemodialysis patients, ischaemic

symptoms are caused by non-atherosclerotic disease 35. This may be due to underlying

small vessel disease (caused by hypertension, diabetes mellitus, and calcium phosphate

deposition), reduced capillary density, and abnormal myocyte bioenergetics36. These

maladaptive changes with consequent left ventricular hypertrophy (LVH) can

additionally predispose to ischemic symptoms with reduced coronary reserve,

consequent to the relative increase in cardiac muscle mass.

1.4.2 Cardiovascular disease due to volume overload in CKD

An increase in circulating blood volume causes not only LV remodelling but also

vascular remodelling. Continuous volume overload results in increase in myocyte length

with a consequent increase in LV volume37. Sustained fluid overload in CKD, due to

salt and water retention, anaemia, and in those on renal replacement therapy from an

arteriovenous fistula, results in eccentric LV hypertrophy29. This is initially sensed as


26

‘beneficial’ by helping to maintaining stable wall stress. However, this eventually

becomes maladaptive, and is harmful as it results in myocyte death, decrease in

capillary density with an increase in myocardial fibrosis38. The consequence of these

maladaptive cardiac changes results in both systolic and diastolic dysfunction 38. It was

also noted, that the LV volume-LV pressure curve is displaced to the left, and altered in

such a manner that small changes in LV volume result in large changes in LV pressure,

predisposing to the development of symptomatic LV failure36.

In addition to the impact on the heart, volume overload results in vascular remodelling

and arteriosclerosis with thickened, dilated, and noncompliant arteries36. Atherosclerosis

is a different pathophysiological entity from arteriosclerosis, and is characterized by

arterial plaques that are focal, intermittent in distribution, occlusive in nature, and with a

predilection for arterial bifurcation sites39. However, arteriosclerosis too predisposes to

ischemic heart disease by decreasing subendocardial coronary perfusion36.

Atherosclerosis is common in CKD, but has been attributed to the presence of other risk

factors like hypertension and diabetes, which when combined with arteriosclerosis, may

enhance the likelihood of ischemia and altered myocardial perfusion39.

1.4.3 Renin-angiotensin aldosterone system in CKD

The renin-angiotensin aldosterone system (RAAS) is a well-known regulator of blood

pressure and determinant of target-organ damage40. It controls fluid and electrolyte

balance through coordinated effects on the heart, blood vessels, and kidneys. A cascade

of intermediate peptide products that comprises the renin-angiotensin-aldosterone

system is shown in figure 1. 4.


27

Fig:1.4 Inhibition of the renin-angiotensin system by angiotensin-converting

enzyme (ACE) inhibitors and angiotensin II type 1 receptor (AT1) blockers.

Source: Thurman JM & Schrier RW Am J Med; 200341.

Synthesis commences upon the release of renin, primarily by juxtaglomerular cells but

also by other tissues42, 43. Renin is a rate-limiting enzyme whose synthesis is influenced

by kidney disease and electrolyte imbalance. Renin cleaves angiotensinogen, which is

synthesized by the liver, forming angiotensin I. Angiotensin-converting enzyme (ACE)

then converts angiotensin I to angiotensin II. ACE is found in the endothelial cells of

the lung, vascular endothelium, and cell membranes of the kidneys, heart, and brain.

This enzyme also degrades bradykinin to inactive fragments, reducing the serum level

of endogenous vasodilators. This pathway is known as the circulatory renin-

angiotensin-aldosterone system. This same cascade also resides in individual organs,

where it is known as the “tissue” renin-angiotensin-aldosterone system44. Figure 1. 5

depicts the renin angiotensin aldosterone cascade.


28

Fig:1.5 Renin–angiotensin system cascade. Source Ehrlich, Hohnloser and Nattel.

Eur Heart J; 200645 .

It is well established that the heart has angiotensin receptors and that activation of

angiotensin II results in myocardial fibrosis and consequent heart failure46-48. The

RAAS is activated in many diseased states including hypertension49, 50 diabetes51, 52

(which are common comorbidities in CKD), as well as in CKD53. In an experimental rat

model, the continuous infusion of angiotensin II resulted in left atrial (LA) fibrosis

similar to LA fibrosis that occurred in CKD54. RAAS activation has a maladaptive

impact on cardiac structure by promotion of myocardial fibrosis (Fig 1.6). This RAAS

activation may at least in part be responsible myocardial dysfunction that is evident

from an early stage of CKD and later causes overt heart failure.


29

Fig:1.6 Direct and indirect actions of angiotensin-II on the atrium. Source Ehrlich,

Hohnloser and Nattel. Eur Heart J; 200645

1.5. Myocardial involvement in CKD

As mentioned earlier, the combination of uraemia related risk factors, activation of

RAAS as well as fluid and volume overload, all consequently lead to alterations in

myocyte properties with consequent myocardial dysfunction. These alterations at a

cellular level manifest as left ventricular hypertrophy with consequent diastolic

dysfunction that in turn alters LA volume and function. Thus CKD has various effects

on cardiac structure and function.

1.5.1 Left ventricular hypertrophy in CKD

Left ventricular hypertrophy (LVH) is highly prevalent in CKD and ESRF.

Approximately 40% patients with CKD and 75% ESRF patients have LVH55, 56. The


30

prevalence and severity of LVH parallels the severity of CKD55. It has also been shown

in early CKD that together with myocyte hypertrophy and disarray, there is interstitial

fibrosis, which has been documented on endomyocardial biopsy57. LVH is an

independent risk factor for adverse future cardiovascular outcome including

arrhythmias, sudden death, heart failure and ischaemic heart disease58. In CKD patients,

LVH is the strongest predictor of cardiovascular mortality12. The pathogenesis of LVH

is multifactorial in CKD where haemodynamic as well as non-haemodynamic stimuli

act synergistically causing an increase in concentric or eccentric LVH. CKD associated

factors such as hypertension, arteriosclerosis, anaemia and hyperparathyroidism and

increased RAAS activity may all contribute and result in maladaptive LVH,

characterized by structural changes in the myocardium. These structural changes

including collagen accumulation, fibrosis and calcification, in addition to continuing LV

overload, in CKD leads to consequent LVH (Fig 1. 7 ).


31

Fig:1.7 Effects of hemodynamic and non-hemodynamic factors on the pathogenesis

of LVH and the impairment of renal function in CKD patients. Source Taddei et

al. Heart Fail Rev; 200158

1.5.1.1 Pressure and volume overload causing LVH

As was discussed earlier, CKD causes arteriosclerosis and hypertension, which opposes

LV ejection and causes pressure overload on the ventricle leading to the development of

concentric LVH. The RAAS system also plays a role by causing myocardial fibrosis,

which in turn leads to compensatory eccentric LVH58. Anaemia is highly prevalent in

CKD due to reduced erythropoietin production. This potentiates volume overload on the

heart and to compensate, there is an increase in left ventricular mass and eccentric

LVH59. Anaemia also leads to progressive cardiac damage by reducing subendocardial

perfusion, that again stimulates the development of myocardial fibrosis56, 60.


32

1.5.1.2 Non haemodynamic cause of LVH

In renal failure defective vitamin D production is responsible for hypocalcaemia and

secondary hyperparathyroidism. This causes elevated serum phosphate and an abnormal

phosphate calcium ratio leading to vascular calcification and LVH58, 61. Excess

parathyroid hormone in CKD facilitates the entry of calcium into vascular and cardiac

myocytes resulting in increased myocyte contractility and peripheral vascular resistance.

This again results in LVH, myocardial fibrosis and a consequent ‘hypertrophic

cardiomyopathy62, 63. Low vitamin D levels have also been shown to cause endothelial

dysfunction, increase vascular resistance and calcification which in turn leads to LVH64.

(fig.1.8)

Fig:1.8 Pathogenesis of LVH in CKD. Source Taddei et al. Heart Fail Rev; 200158

1.5.2 Diastolic Dysfunction in CKD

Diastolic dysfunction is characterised by alteration in ventricular relaxation and

compliance. Fifty to 65% patients with CKD have diastolic dysfunction65. Diastolic


33

dysfunction is an independent prognostic factor in CKD66. Diastolic dysfunction is even

observed in patients with early stages of CKD67. Diastolic dysfunction in CKD is

multifactorial. CKD causes an increase in circulatory preload which contributes to

diastolic dysfunction68. Activation of RAAS leads to myocardial fibrosis and diastolic

dysfunction69. Microvascular abnormalities, LVH, coronary artery disease, fluid and

electrolyte abnormalities, neurohumoral alterations and other co morbidities like

hypertension and diabetes associated with CKD are all contributors to the development

of diastolic dysfunction in CKD70. Thus, in CKD, multiple maladaptive processes

causes diastolic dysfunction that eventually progress to heart failure and leads to poor

cardiovascular outcomes. Hence it is important to diagnose this early and treat

contributory factors aggressively to prevent future adverse cardiovascular events.

1.6 Diastolic function and diastolic heart failure

Diastole is a complex process and extends from aortic valve closure to mitral valve

closure during the cardiac cycle. Diastole comprises of four phases, namely isovolumic

relaxation phase, passive filling phase (due to left ventricle relaxation), slow filling

phase (diastasis) and finally LV filling phase (consequent to active atrial contraction).

The isovolemic relaxation time is mediated by active myocardial relaxation, while early

diastolic filling is load dependent and is influenced by active as well as passive factors

such as myocardial mass, interstitial fibrosis, and chamber geometry. Normal diastolic

function is defined as the ability to accept adequate left ventricular filling, while

maintaining a low ventricular diastolic pressure. LV diastolic relaxation, even in a

healthy individual, alters as age advances 71. Abnormal diastolic relaxation is

accelerated in certain disease states which causes alteration in LV geometry and


34

structure, especially LVH can significantly alter early filling due to impaired LV

relaxation72.

Diastolic dysfunction occurs when the myocardium loses its ability to generate force

and contraction and remains at an unstressed length causing abnormal myocardial

relaxation. This will result in changes in onset, rate, and extent of ventricular pressure

decline and filling. This also in turn changes the relationship between pressure and

volume or stress and strain during diastole. This results in a decrease in ventricular

relaxation and/or an increase in ventricular stiffness. Chamber stiffness is determined

by the stiffness of myocardium, LV mass and LV mass/volume ratio. These changes

occur as a result of LV pressure and volume overload and may additionally promote

myocyte death36. Finally diastolic dysfunction presents with heart failure symptoms

with relatively preserved systolic LV function. Diastolic heart failure or ‘heart failure

with preserved ejection fraction’ refers to a condition in which abnormalities in cardiac

mechanical function are present during diastole, affecting LV relaxation properties73.

Thus the ventricular chamber is unable to accept an adequate volume of blood during

diastole, at normal diastolic pressures and at volumes sufficient to maintain an

appropriate stroke volume.

Diastolic function as previously outlined, is complex and no single measure can

quantitate diastolic dysfunction. However diastolic dysfunction can be assessed non-

invasively by incorporation of different echocardiographic parameters, including mitral

inflow Doppler velocities, tissue Doppler imaging, pulmonary vein flow and left atrial

parameters. In fact, diastolic dysfunction has been categorised as grades, using these

varying echocardiographic parameters. Biochemical abnormalities have also been

reported with diastolic dysfunction with an increase in brain natriuretic peptide73-76.


35

1.7 Diagnosis of diastolic dysfunction

1.7.1 Mitral inflow velocities

Transmitral flow velocity, one of the earliest measures of diastolic function evaluation,

often still remains the method of choice in routine clinical practice77. From the apical 4

chamber view, using pulsed-wave (PW) Doppler, mitral inflow patterns are obtained

that can be used to evaluate LV filling78. A sample volume (1 = 3-mm) is placed at the

mitral leaflet tips, and a diastolic filling profile is obtained (Figure1. 9). Mitral inflow

measurements comprise of estimating the peak early filling (E-wave) and late diastolic

filling (A-wave) velocities, the E/A ratio, deceleration time (DT) of early filling velocity

as well as mitral A-wave duration and total diastolic filling time (figure 1. 9).

Fig:1.9 Mitral inflow velocity


36

Mitral inflow patterns to grade diastolic dysfunction are identified by the peak mitral E

and A wave velocity, the E/A ratio and DT. The diastolic function grades using

transmitral Doppler inflow includes 4 grades of severity; normal, impaired LV

relaxation, pseudo normal LV filling, and restrictive LV filling79. Several diastolic

parameters, including E/A ratio and deceleration time of the early diastolic wave, have a

biphasic response to diastolic dysfunction. The normal atrial contribution to total

diastolic filling is around 30% and the peak A wave velocity is smaller than the E wave

velocity with an E/A ratio >1. In the initial stages of diastolic dysfunction, an increase

in LV filling pressure produces a low E wave and a high A wave velocity, resulting in

reversal of the E/A ratio. When diastolic dysfunction progresses and LV compliance is

reduced even further, LA pressure increases progressively in order to maintain a

transmitral pressure gradient. The E wave velocity increases and the E/A ratio can be

>1.5. This will lead to normalisation of E/A ratio despite the presence of moderate to

severe diastolic dysfunction and is referred to as a pseudo normal pattern. With

progressive worsening of diastolic dysfunction, there is slower LV relaxation with a

consequent increase in LA pressure, that results in a further increase in peak E velocity,

and a very short DT, which is called restrictive filling pattern80. However, transmitral

flow velocity is influenced by loading conditions, particularly preload. A number of

variables other than LV diastolic function and filling pressures can also affect mitral

inflow, including normal aging, heart rate and rhythm, presence of first degree heart

block, cardiac output, mitral annular size and LA function79. Normal ageing affects the

values of mitral inflow velocities and time intervals; age-related changes in diastolic

function represent a physiological alteration in myocardial relaxation. With increasing

age, the mitral E velocity and E/A ratio decrease, whereas DT and A velocities

increase79.


37

Grade 1 diastolic dysfunction is characterised by E/A ratio < 1, with a prolonged

deceleration time (>240ms). In pseudonormal filling, the E/A ratio is between 1 and 2

and the deceleration time between 160 and 240ms. In restrictive filling pattern E/A

ratio is > 2 with deceleration time is < 160ms.

The determination of pseudo normal pattern may be difficult by mitral inflow velocities

alone. Mitral E-wave velocity is preload dependent as it reflects the LA-LV pressure

gradient during early diastole.77. LV compliance and LA contractile function can affect

mitral A wave as it reflects the pressure gradient across the mitral valve in late diastole.

The peak E-wave velocity and DT are influenced by LV diastolic pressures following

mitral valve opening and also LV compliance/ relaxation. So both E velocity and DT

are affected by alterations in LV end-systolic and/or end-diastolic volumes, LV elastic

recoil, and/or LV diastolic pressures directly.

1.7.1.1 Clinical utility of diastolic function assessment

LV diastolic function using mitral in flow velocities are classified into 4 grades; normal

(DT =160-240ms, E/A ratio =0.9-1.5, e’ velocity ≥10 cm/s), impaired relaxation

(DT>240ms, E/A ratio <0.9, e’ velocity <10 cm/s), pseudo normal (DT = 160 - 240ms,

E/A ratio = 0.9 - 1.5, e’ velocity <8 cm/s) and restrictive (DT < 160ms, E/A ratio > 2.0,

e’ velocity <5 cm/s)79 based on mitral inflow Doppler along with tissue Doppler

velocity of the mitral annulus.

PW Doppler mitral flow velocity variables and filling patterns in patients with reduced

LV function correlate better with cardiac filling pressures, functional class, and

prognosis81-83. A shortened mitral DT and increased E/A velocity ratio represent

advanced diastolic dysfunction, increased LA pressure, and worse functional class. It


38

has also been shown that restrictive filling pattern is associated with a poor prognosis,

especially if it persists after preload reduction in a variety of cardiac conditions84.

1.7.1.2 Limitations of mitral inflow for evaluation of diastolic dysfunction

Even though mitral inflow velocity is easy to measure and has good reproducibility, it

has several drawbacks. Mitral inflow velocity patterns have a “U-shaped” relationship

with LV diastolic function in patients with cardiac disease. This distinction is not as

important in instances with reduced LV systolic function (when there is often coexistent

diastolic dysfunction as well), but the problem of recognizing pseudo normal filling

pattern and diastolic heart failure in patients with normal or relatively preserved LV

systolic function is often difficult, by measuring mitral inflow velocity alone. As

mentioned earlier, factors like sinus tachycardia 85, conduction system disease and

arrhythmias make mitral inflow variables more difficult to interpret. Sinus tachycardia

and first-degree AV block causes partial or complete fusion of the mitral E and A

waves. In atrial flutter, mitral inflow velocities are not accurate as LV filling is

influenced by the rapid atrial contractions86. Moreover, mitral inflow is age dependent

and exquisitely sensitive to loading conditions.

1.7.2 Tissue Doppler imaging to evaluate diastolic function

Tissue Doppler imaging (TDI) for echocardiographic evaluation of myocardial function

has revolutionised the quantitative evaluation of myocardial function. Traditional

Doppler is designed to image the high frequency, low amplitude signals caused by

blood flow in the heart. However, myocardial motion, which comprises of low velocity,

high amplitude signals, is measured by using tissue Doppler imaging87 and is obtained

by inverting the low pass filter used in traditional Doppler to a high pass filter. Tissue


39

Doppler measures myocardial contraction and relaxation velocities rather than blood

flow velocities.

Tissue Doppler imaging e’ velocity, a relatively load independent parameter, measures

LV relaxation in early diastole 88. e’ velocity is measured from both septal and lateral

mitral annulus in the apical four chamber view; as such septal e’ velocity is lower than

that of lateral annular e’ velocity79. The current recommendation of the ASE is that an

average of septal and lateral annular e’ velocity be utilised for all practical purposes79.

e’ velocity correlates inversely with early diastolic pressure (dP/dt) or tau (time constant

of LV relaxation) 89 thereby reflecting LV relaxation and elastic recoil. In healthy

adults, an average of septal and lateral e’ velocity < 8 cm/s indicates impaired LV

diastolic function, while > 8 cm/s is considered normal90. Normal ageing reduces e’

velocity91 in both the septal and lateral annulus. In more advanced diastolic dysfunction,

as mentioned previously, using mitral inflow pattern alone to identify a pseudo normal

pattern may be difficult 92; the e’ velocity is used to differentiate between normal and

pseudo normal pattern. e’ velocity is reduced even in subjects with early diastolic

dysfunction, occurring almost 10-15 years prior to reduction of mitral E velocity93.

Hence, e’ velocity is included early in the algorithm for diastolic dysfunction evaluation

in the current EAE/ASE guidelines79. Diastolic function assessment by tissue Doppler

imaging is discussed in greater detail in chapter 6.

1.7.3 Left atrial volume and diastolic function

The left atrium is most commonly thought of as a chamber receiving blood from the

pulmonary veins and conveying it to the left ventricle, through both passive and active

diastolic filling. However, the left atrium has different functions; it modulates

ventricular filling and this comprises LA reservoir function, serves as a conduit for


40

blood flow from the pulmonary veins to the LV and finally demonstrates active

contractile function in late diastole94. Early diastolic atrioventricular gradient and LA

conduit volume reduces with impaired LV relaxation, while contractile pump function

is enhanced to compensate and thereby maintain optimal LV filling.

The LA also reflects LV filling pressure and is capable of remodelling (enlarging) in

response to elevation in LV filling pressure. It is in this role, as an ongoing “biomarker”

of sustained elevation in LV filling pressures, that LA size is an important marker in

assessing diastolic function95. Doppler velocities and time intervals are instantaneous

measures and reflect filling pressures at the time of measurement, whereas LA volume

reflects long term effects of LV filling pressures. Thus LA volume is regarded as a

surrogate measure of both the severity and chronicity of diastolic dysfunction.

While early studies have used the LA diameter or area measurement, there is good

evidence to demonstrate that a biplane left atrial volume is a more accurate measure of

LA size96. The enlargement of the left atrium is not symmetrical and this is perhaps why

a biplane volume is a more accurate estimate of LA volume. A biplane LA volume,

from the apical 4-chamber and 2-chamber views, is an easy, feasible and reproducible

measure97. There is a significant relationship between LA remodelling and

echocardiographic indices of diastolic function98. Additionally, a LA volume indexed to

body surface area >34 mL/m2 was an independent predictor of adverse events,

including death, heart failure, atrial fibrillation and ischemic stroke99. An important

caveat to remember though is that LA dilatation can also be seen in athletes100 and

patients with other medical conditions in the absence of diastolic dysfunction; the

presence of atrial arrhythmias being a notable cause for LA enlargement. Therefore, it is

important to consider LA volume measurements in conjunction with a patient’s clinical

history as well as other echocardiographic parameters.


41

1.8 Strain and strain rate imaging

Strain and strain rate (SR) imaging is a new echocardiographic technique used to assess

myocardial deformation, by estimating spatial gradients of myocardial velocities. If

every part of an object moves with the same velocity, then a moving object is not

necessarily undergoing deformation. When different elements of the object move at

different velocities, the object changes shape during its movement, and this results in

deformation. The fractional change in length of an element of the object, compared to

its original length, is called Lagrangian strain101. Deformation can be expressed not only

relative to the original length, but also relative to the length at a previous moment in

time. Natural strain is the instantaneous reference strain value which changes during the

deformation process. Lagrangian and natural strain have a nonlinear relationship, so in

small deformations the two strains are approximately equal, but in large deformations

the difference becomes significant102.


42

Fig:1. 10 Myocardial strain. Pavlopoulos H and Nihoyannopoulos P. Int J

Cardiovasc Imaging; 2008101

Strain is a dimensionless parameter and deformation is expressed as a percentage. An

increase in length from original length (ie relaxation) results in “positive strain”, while a

decrease in length from original (ie contraction) is considered “negative strain”. Strain

rate is the rate at which deformation changes i.e. change of strain per unit of time. In a

beating heart, the unstressed original length is difficult to measure, so end-diastolic

length is most often used103. Thus SR describes the rate of shortening or lengthening of

an object or a part of the heart, and its measurement unit is (1/s).


43

Fig:1.11 Strain rate. Pavlopoulos H and Nihoyannopoulos P. Int J Cardiovasc

Imaging; 2008101

In cardiac muscle physiology, strain is directly related to fibre shortening and SR to the

speed of shortening, which is a measure of contractility. Any cardiac condition that

causes abnormal myocardial contraction or ‘deformation’ like left ventricular

hypertrophy, diastolic dysfunction or myocardial fibrosis, will impair strain and SR.

Alterations in LV strain have been reported in a variety of conditions that have overt or

subclinical cardiac involvement102, 104-109.

Strain measurements can be obtained from Doppler derived images (ie based on

myocardial velocity gradients)103 or using 2 dimensional speckle tracking and are

discussed later in greater detail.


44

1.8.1 Left atrial strain and SR in evaluation of atrial function

Strain and SR imaging is increasingly being used to assess LA function. There are

number of studies that have evaluated LA function using strain imaging110-114. Strain

measurements can be performed by using either tissue Doppler imaging or by 2D

speckle tracking as mentioned earlier. Strain curves are monophasic, whereas SR curves

of the LA are triphasic (fig1. 12, 1.13, 1.14 and 1.15).

LA phasic function has been described previously. LA strain can be measured

throughout the cardiac cycle and permits the evaluation of LA phasic function. Peak

LA systolic strain is a measure of LA reservoir function (global and regional LA

function), while SR can quantitate reservoir, conduit and contractile phases115. Early

diastolic SR is a measure of LA conduit function and late diastolic SR indicative of LA

contractile function. Recent reports have assessed LA strain and SR and its utility in

evaluating LA function in atrial fibrillation, heart failure and ischemic heart disease 116

110, 117. Normal values from healthy subjects derived from groups of healthy subjects

from various centres are now available118. The normal LA strain from this study in

normal individuals is reported as 45.5 +/- 11.4%.

1.8.1.1 Doppler strain and SR

Unlike, tissue Doppler velocity, Doppler derived strain parameters are relatively

unaffected by heart motion and tethering of adjacent segments104. Four and 2 chamber

images acquired at high frame rate (>100FPS) are used for evaluation of strain

parameters. An average of septal, lateral, inferior and anterior walls are typically used to

describe global LA strain. The sample volume for strain measurements are obtained

using a narrow sector because of the thin atrial wall (10 x 2 mm sample volume), placed

5 mm superior to the atrio-ventricular junction. The Doppler beam is aligned parallel to


45

atrial wall using a narrow sector angle (300) at the end of expiration so that signal noise

and angle artefacts can be minimised. Using dedicated software and an offline

measuring station, the image is tracked frame by frame, ensuring that the sample

volume for each frame is moved to its original location in the middle of the segment119.

The superiority of strain measurements has been demonstrated with strain analysis

providing better site specificity over tissue Doppler velocity data for tracking local

systolic function120, especially as strain measurements are independent of any tethering

effects. A limitation of Doppler strain imaging involves signal–noise interference, an

issue that can be addressed by increasing the sample distance, as well as angle

dependency of the technique121.

Fig:1. 12 LA strain by tissue Doppler imaging

Systolic strain


46

Fig:1. 13 LA strain rate by tissue Doppler imaging

1.8.1.2 Two-dimensional speckle tracking strain

As stated earlier, the Doppler technique is angle dependent and this is the main reason

why measurements are limited to certain segments, especially when trying to estimate

radial and circumferential function of the left ventricle. An alternative method, using B-

mode images, is the estimation of strain and SR by 2 dimensional “speckle tracking”.

The ultrasound reflected from the tissue is the result of interference by numerous

reflected wavelets from the non-homogeneous medium. The interference pattern

(resulting in bright and dark pixels in a B mode image) remains relatively constant for

any small region in the myocardium. This unique pattern is called a ‘speckle’. In the

speckle tracking analysis, a defined region is tracked, following a search algorithm

based on optical flow method, trying to recognize the most similar speckle pattern from

one frame to another122. The algorithm searches for an area with the smallest difference

in the total sum of pixel values, which is the smallest sum of absolute differences. The


47

technique is angle-independent as it is based on the displacement of speckles, defined

with respect to the wall rather than the ultrasound beam. 2D speckle tracking derived

strain has been validated by sonomicrometry 123. With respect to the left ventricle, it

provides information on longitudinal, circumferential and radial myocardial function,

estimating directly Lagrangian strain parameters with better lateral resolution compared

to tissue Doppler due to a higher density of scan lines in the grey scale images. With the

left atrium, given it’s thin walls, only longitudinal strain is currently evaluated. 2D

strain analysis is semi-automated and tracking of the sample throughout the cardiac

cycle does not need to be done manually (Fig 1.14 and 1.15); it is also angle

independent.

Although it seems to be an attractive method, limitations are also present. Strain

measurements are inherently dependent on the quality of the 2 dimensional images and

with the assumption that the speckle pattern remains constant throughout the cardiac

cycle. The re-orientation of myocardial fibres, the out-of-plane motion of scatterers, the

resemblance between subsequent images, the ability to track with sufficient temporal

resolution and the difference in axial and lateral resolution are all factors that modify the

extracted values. Moreover, 2D images for strain analysis need to be acquired at a high

frame rate (> 55-60fps). Despite these limitations, strain measurements have been

demonstrated to be reproducible118.


48

Fig:1.14 LA systolic strain by speckle tracking

Fig:1.15 LA strain rate by speckle tracking


49

1.8.2 Clinical utility of LA Strain and SR

Strain imaging is a novel echocardiographic technique, and has been used to assess LA

function in different clinical conditions; it has additionally been used as a prognostic

tool for adverse cardiovascular outcomes124-129.

Atrial function is an integral part of cardiac evaluation and has in the past been

demonstrated to be a biomarker of cardiac events. This is because LV dysfunction (both

systolic and diastolic) as well as LV hypertrophy alters atrial function. Standard

echocardiographic parameters in evaluating ventricular diastolic function are pulsed-

wave Doppler mitral inflow analysis, tissue Doppler imaging measurements and LA

volume. As mentioned earlier, LA strain and SR parameters have been validated in the

evaluation of LV diastolic function130. LA strain during atrial systole is significantly

reduced in diastolic heart failure patients secondary to LA stiffness131. Interestingly, LA

dysfunction with changes in strain and SR has been observed in patients with

amyloidosis in the absence of other echocardiographic features of cardiac

involvement115. It was also demonstrated that diastolic dysfunction and LVH secondary

to hypertension impairs LA strain parameters to a greater degree than observed in the

adaptive LVH in athletes126. Alterations in LA strain have been demonstrated in normal

ageing, prior to any alteration in LA volume132. Similar findings were reported by

another group, who demonstrated that even before LA dilatation occurs, LA 2D strain

was abnormal in patients with hypertension and diabetes133. LA deformation is impaired

in patients with hypertension or diabetes due to multiple reasons. Both conditions cause

diastolic dysfunction, but additionally activate the RAAS, that may consequently result

in myocardial fibrosis134, 135. Atrial strain has emerged as an important predictor for the

maintenance of sinus rhythm following cardioversion and AF ablation136, 137. Atrial


50

strain has also shown prognostic value as a predictor of adverse cardiovascular events in

acute myocardial infarction and hypertrophic cardiomyopathy138, 139.

1.8.3 Left ventricular strain imaging

LV systolic function is traditionally measured by evaluation of LV ejection fraction.

More recently strain analysis of LV contractile function has been reported140; shortening

of myocardium results in negative strain (Fig 1.16). LV strain too can be derived from

tissue Doppler imaging or using 2D speckle tracking. However, given its ease of

measurement and angle independence, 2D speckle tracking strain is more commonly

utilised. Normal values for LV strain have been published109 and good reproducibility of

these measurements has been reported141. LV strain is affected by both age and sex of

the individual107. LV strain correlates well with other measures of cardiac function and

can detect changes in myocardial contractility across a wide range of different

conditions including hypertension, diabetes, ischaemic heart disease and CKD66, 142-148.

Strain and SR are sensitive parameters and have been shown to detect early LV

involvement, prior to changes in LV ejection fraction149, 150 . Thus strain measurements

detect early “subclinical involvement” of myocardium.


51

Fig:1.16 2 D speckle tracking Left ventricular strain analysis. Dotted line indicates

mean systolic strain

1.9 Biochemical markers of myocyte injury

In heart failure, the cardiac endocrine system, particularly atrial natriuretic peptide

(ANP) and brain natriuretic peptide (BNP) are activated151. The natriuretic peptides are

a group of structurally similar but genetically distinct peptides that have diverse actions

in cardiovascular, renal and endocrine homeostasis.

BNP is a cardiac neurohormone secreted from the ventricles in response to ventricular

volume expansion and pressure overload152. Abnormal diastolic filling pressure, the key

functional abnormality in diastolic heart failure, also leads to release of BNP and its

biologically inactive fragment N-terminal pro BNP (NT-pro BNP) both of which are

released predominantly by the ventricles in response to stretch and are useful for the


52

diagnosis of heart failure153. BNP, as mentioned earlier, is predominantly of ventricular

origin, and is produced in cardiomyocytes, as a response to increased ventricular end-

diastolic pressure, in the form of pre-proBNP. In peripheral blood, proBNP is broken

down into the active peptide, BNP, and an inactive molecule, NT-pro BNP. BNP and

NT-pro BNP levels are known to be elevated in patients with symptomatic LV

dysfunction and correlates with NYHA class and prognosis154, 155.

BNP levels may also reflect diastolic dysfunction in patients with heart failure156. In an

earlier study of patients with normal systolic function, elevated BNP levels could

reliably detect the presence of diastolic abnormalities on echocardiography76. In a

group of CHF patients with normal LV size and contraction, in whom early diastolic

dysfunction with an impaired relaxation pattern was observed, a higher BNP value

represented a more advanced degree of diastolic dysfunction in comparison to a similar

group with normal BNP. Hence BNP can add value to evaluation of diastolic

dysfunction, which has not previously been appreciated and may provide an additional

important tool for recognizing the presence of diastolic dysfunction. It was also shown

that NT-pro BNP levels also have similar diagnostic accuracy for diastolic heart failure

as echocardiographically derived TDI measurements and is superior to conventional

Doppler echocardiographic parameters157. NT-pro BNP values correlate well with

invasive parameters of LV filling pressure75. NT- pro BNP levels are relatively easy to

obtain and can be performed serially, thereby having an extra advantage in that they

may additionally provide a surrogate end point for the evaluation of various treatments

of heart failure. It was also noted that falling BNP levels with medical treatment for

heart failure was associated with a fall in wedge pressures, a lower readmission rate to

the hospital and a better prognosis158. Thus, monitoring BNP / NT-pro BNP levels in

future treatment protocols for diastolic dysfunction may provide valuable information


53

regarding treatment efficacy and patient outcomes. Even though there is a reasonable

correlation between the values of BNP and NT-pro BNP in heart failure, it was shown

that NT-pro BNP as slightly superior to BNP in diagnosing heart failure159. It was also

shown NT-pro BNP is technically easier to measure; it could thus become the method

of choice for screening for heart failure in routine clinical practice.

1.10 Diagnosis of cardiomyopathy in CKD

As was discussed earlier, CKD commonly causes LV hypertrophy. Although diastolic

dysfunction is not uncommon in patients with normal wall thickness, LV hypertrophy is

among the most common causes for diastolic dysfunction with consequent heart failure.

Myocardial hypertrophy results in altered relaxation of myocardium, which reduces

early diastolic filling. In the presence of normal LA pressure, this shifts a greater

proportion of LV filling to late diastole, during atrial contraction. As left ventricular

pressures increase, the LA pressure gradually increases over time, in a bid to maintain

early diastolic filling. This ultimately results in enlargement of LA as well as LA

dysfunction. The LA stretch consequent to the raised LA pressure additionally results in

secretion of natriuretic peptide including BNP.

1.10.1 Mitral inflow velocities in CKD

In CKD, earlier reports have shown that mitral E velocity was lower and A velocity was

higher, resulting in a decreased E/A ratio, which increases in parallel with the severity

of renal dysfunction67. It was also shown that there is a reduction in the E wave

deceleration time in CKD. However, CKD also causes a change in intravascular

volume; hence mitral inflow Doppler when used alone is less reliable to diagnose

diastolic function in CKD patients, as it is exquisitely volume dependent and is


54

therefore altered by loading79. Most CKD patients are elderly and also have associated

conditions like hypertension and diabetes, which in themselves alter myocardial

relaxation. These coexistent conditions thereby compound the diastolic dysfunction in

CKD by their additive effect, resulting in mitral inflow velocities being a less reliable

tool to detect diastolic dysfunction in CKD.

1.10.2 Tissue Doppler imaging in CKD

Various studies have shown that TDI is superior method for evaluation of diastolic

function in patients with CKD regardless of the mitral inflow velocity flow pattern and

is more sensitive for detecting diastolic dysfunction compared with conventional

echocardiography67, 72. CKD results in altered loading conditions and transmitral flow

is very dependent on loading. As TDI is less load dependent, it is more accurate in

diagnosing diastolic dysfunction in CKD patients59. It was also shown that TDI has a

prognostic role in detecting diastolic dysfunction in CKD160. e’ velocity also had

independent prognostic value in ESRF patients161. There are few studies that have

concluded that E/e’ ratio >15 is an independent predictor of general and cardiovascular

mortality in end stage CKD patients162, 163. However, its role in early CKD is not

delineated in the literature.

1.10.3 LA volume and CKD

It has also been previously reported that LA diameter has independent prognostic value

and provides a small but significant incremental value to clinical variables in predicting

CVD mortality in patients with CKD with preserved left ventricular systolic function164.

More recently, it was demonstrated that LA volume indexed to body surface area

(LAVI), was a predictor of adverse cardiac events in early CKD165. Abnormal diastolic


55

function, while almost always present, may not be accurately estimated and have

reduced predictive value for determining of adverse cardiac events in CKD patients,

because of fluctuating filling pressure in ESRF 164. On the other hand, LA size which is

a robust correlate of LV diastolic dysfunction may be a more stable measurement that is

relatively preload independent166. Barberato and colleagues showed that fluctuations in

LA size were less pronounced than changes in Doppler indices of diastolic filling during

haemodialysis167. Indexed LA diameter >24 mm/m2 had incremental predictive value

for adverse CV outcome 164 in 200 CKD patients and stage 3 and 4 CKD subjects with

LAVI >32 ml/m2 had significantly lower event-free survival165. A possible explanation

for its additional prognostic ability is that LA size provides a composite measure of the

total haemodynamic burden that would reflect both LV systolic dysfunction and

diastolic dysfunction. It was also documented that the progressive increase in left atrial

volume (LAV) predicts incident cardiovascular events in dialysis patients independent

of the corresponding baseline measurement of LAV and of LV mass and function168.

This finding indicates that monitoring LA size by echocardiography provides

independent prognostic information in patients with ESRF. Such data is not available in

early CKD patients.

1.10.4 Strain evaluation in CKD

LV strain and SR are of prognostic significance in patients with late and end-stage

CKD66. Edwards and colleagues showed reduced LV strain even in asymptomatic

individuals with early CKD without clinical evidence of heart disease and hypothesised

that this may be secondary to myocardial fibrosis resulting in abnormal myocardial

deformation142. Given that the atrium has thinner myocardial walls, involvement of LA


56

myocardium should be detected earlier than in the ventricle; however, there are only

limited data in the literature regarding LA strain parameters in early CKD.

As mentioned earlier, LA strain is also reduced in conditions commonly associated with

CKD like hypertension and diabetes133, 169. However, the independent additive value of

CKD if any, has not been evaluated. Strain and strain rate are very sensitive parameters

that need to be evaluated in greater detail in CKD patients; importantly its prognostic

value in CKD needs to be determined.

1.10.5 BNP / NT-pro BNP in CKD

Sakuma and co-workers showed that CKD patients with the highest plasma BNP

quartile had a 4- to 5-fold higher CV risk, including heart failure, stroke, myocardial

infarction and sudden cardiac death compared with the subgroup with the lowest plasma

BNP quartile170. It has also been shown that a plasma naturetic peptide level was a

strong and independent predictor of CKD progression171. Even though, BNP is excreted

by the kidney172, BNP levels within the upper reference limit are seen in most stage 3

CKD patients, despite having a decreased eGFR173. Hence, altered cardiac function is

the more likely explanation for elevated BNP levels in patients with CKD174 rather than

as a consequence of altered renal function. NT-pro BNP has also demonstrated

prognostic utility for adverse cardiovascular events in advanced renal failure175, 176.

Bruch and colleagues showed that CKD patients with NT-pro BNP >1400pg/ml had

poor cardiovascular outcomes177. Pfister and colleagues reported that NT-pro BNP was

a sensitive marker for detection of systolic and diastolic heart failure157. However, there

is no accepted standard cut off values for NT-pro BNP or BNP, as indicators of early

myocardial involvement in CKD which could potentiate their use as biomarkers for

adverse cardiovascular events.


57

Future directions for risk evaluation

Patients with CKD, irrespective of the cause, are at increased risk of CVD, including

coronary artery disease, cerebrovascular disease, PVD and heart failure. In fact, all

CKD patients should be considered as “highest risk” group for cardiovascular disease,

irrespective of levels of traditional CVD risk factors as mentioned earlier. All CKD

patients are recommended to undergo assessment for CVD risk factors; including

measurement of “traditional” CVD risk factors as well as “CKD-related” CVD risk

factors. This is due to the exceptionally high cardiovascular risk in CKD, including the

identification of traditional and non-traditional risk factors.

Given the poor performance of the Framingham equation in adults with CKD, there is a

need of future studies exploring risk equations, which include traditional CVD risk

factors, incorporating additionally unique comorbidities associated with CKD, for

prediction of adverse cardiovascular events in this group of patients. Included among

these, is the improved understanding of the critical role of vascular stiffness in

individuals with CKD and how this pathophysiology may contribute to heightened

cardiovascular disease risk, with multiple trials focusing on cardiovascular disease risk-

factor modification in individuals with CKD15. Roberts and colleagues showed by

improving pre dialysis cardiovascular disease care, a decrease in cardiovascular

mortality was seen in dialysis patients, thereby reflecting future directions regarding

early diagnosis of cardiovascular involvement in CKD. The aggressive management of

risk factors in this high risk group may provide improved cardiovascular outcomes178. It

is therefore important to develop novel non-invasive markers that may be predictors for

adverse cardiovascular events in CKD patients.


58

1.12 Overall Aim

Cardiovascular disease is common in CKD patients; the majority of patients with ESRF

die of cardiovascular events rather than renal failure179. Diastolic dysfunction and LVH

is commonly seen in ESRF67. However, these overt cardiac abnormalities are usually

manifest at advanced stages of renal disease, when the patient’s prognosis is poor.

While there are a few reports related to cardiac involvement in CKD, such data are

limited. Early identification of cardiac involvement in CKD patients could lead to

altered management and therapeutic strategies that may improve their longer term

outcomes. Thus, the overall aim of this doctoral research project was to identify a

sensitive biomarker to recognise early cardiac involvement and diagnosis of early

cardiomyopathy in CKD.

We selected echocardiography, as it is a noninvasive cardiac investigation and NT-pro

BNP as a biochemical parameter and sought to determine which of these would be the

more sensitive biomarker to detect cardiac involvement in early CKD.

Echocardiography is easily available, does not expose an individual to radiation making

serial evaluation safe and echocardiographic parameters are reproducible; moreover an

echocardiogram is routinely performed in almost all CKD patients as part of their

routine clinical care. Hence utilising an echocardiographic marker to identify CKD

patients at risk is a very attractive option.

NT-pro BNP is a powerful prognostic and diagnostic non-invasive tool in heart failure

management, which is again relatively inexpensive, widely available and reproducible.

There are various studies that have previously examined the utility of a variety of

echocardiographic parameters including mitral inflow Doppler study, TDI180, left atrial

volume181, left ventricular strain142 as well as biochemical parameters like BNP and NT-

pro BNP170, 175 in patients with ESRF. These parameters have also been evaluated for


59

their prognostic utility to assess adverse cardiovascular outcomes. However, there is

paucity in the literature the evaluation of these parameters in early CKD, when

aggressive management and therapeutic intervention may significantly impact on long

term adverse events.

It is a well-known fact that diabetes and hypertension are co-existent conditions in most

CKD patients. Both diabetes and hypertension cause CVD independently and contribute

to adverse cardiovascular outcomes, but more importantly can alter echocardiographic

LV and LA parameters. What needs to be established if there is an independent and

incremental effect of CKD in addition to diabetes and hypertension on cardiac structure

and function and whether echocardiographic LV and LA parameters can detect this

independent effect.

Many studies have previously shown the high prevalence of diastolic dysfunction in

patients with diabetes182-184. In fact, diastolic dysfunction is considered the earliest

marker of diabetic cardiomyopathy182, 185. Most of the previous studies to evaluate

diastolic dysfunction in diabetes are based on mitral inflow pattern186, 187, Doppler tissue

imaging182, 183 or left ventricular strain188 and these reports are in normotensive diabetic

patients. Even though diastolic dysfunction causes LA enlargement and dysfunction79,

there is paucity in the literature regarding LA volume and function in diabetes alone or

associated with hypertension.

Hypertension is also a well-known factor contributing to diastolic dysfunction.

Contractile alterations in myocytes, structural ventricular hypertrophy, extracellular and

perivascular fibrosis and myocardial ischemia are implicated as the factors causing

diastolic dysfunction in hypertension189, 190. TDI e’ velocity was shown to be a good

indicator to detect diastolic dysfunction in hypertensive patients even in the absence of

LVH191. LA enlargement has been previously reported in hypertension192. Recently it


60

was shown that LA function is abnormal in hypertensive patients193. However, there are

limited data regarding LA size and function as evaluated by strain parameters in

hypertensive patients, especially associated with CKD.

We hypothesised that LA volume and function would be a sensitive marker of

myocardial involvement in early CKD and would have independent incremental value,

permitting its use as a biomarker even in the presence of diabetes and hypertension. We

further hypothesised that alteration in LA parameters might occur early thereby

rendering this as a sensitive biomarker to detect cardiovascular involvement in early

CKD.

In order to examine the above mentioned hypotheses, the following sub studies were

designed to address specific issues as outlined below

1. To investigate the changes in LA volume and LA function assessed by strain in

patients with diabetes and hypertension, with normal renal function, individually

or in combination.

2. To investigate the changes in LA size and function by strain in patients with

CKD and hypertension as compared to patients with hypertension, with normal

renal function.

3. To determine which echocardiographic parameter is the most sensitive

parameter to detect cardiovascular involvement in CKD in the presence of

diabetes and or hypertension

4. To evaluate whether NT-pro BNP or previously identified echocardiographic

parameters would be the most sensitive measure of cardiac involvement in stage

3 CKD patients.

By addressing the above mentioned specific aims, we sought to determine the most

effective biomarker to detect cardiac involvement in early CKD.


61

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function. Circ Cardiovasc Imaging. 2009;2:93-9.


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Chapter 2: General methodology


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General methodology

Outlined below is the general methodology that has been used throughout the conduct

of the various sub studies that comprise this body of research.

2.1 Subject groups

Study approval was obtained from the Human Research and Ethics Committee South

Western Area Health Service (HREC/09/LPOOL/53). All participants provided written

informed consent.

One hundred subjects with stage 3 chronic kidney disease (CKD), (eGFR of 30-59

ml/min/1.73m2) by modified diet in renal disease formula were recruited from

Liverpool Hospital, Sydney, Australia. Staging of CKD was done as per National

Kidney Foundation criteria1. Patients were identified from the renal outpatient clinics.

All patients had renal function checked for the previous six month to ensure no acute

deterioration in renal function due to any cause and that stable renal dysfunction was

present over the 6 month period prior. Risk factor matched controls were recruited from

Liverpool Hospital from among patients screened as part of the chest pain pathway.

Additionally, age, gender and risk factor matched controls with normal renal function,

were randomly selected from a patient data base from the Canberra Hospital, ACT.

All subjects had detailed medical history including cardiovascular symptoms,

medication history, family history and risk factors. They all underwent detailed clinical

examination including obtaining height, weight and blood pressure, as well as a

systemic examination. All recruited subjects had a baseline ECG, baseline blood for

renal function, full blood count, hsTnT, NT- pro BNP and glycosylated haemoglobin

where appropriate. They also had urine examination for albumin, protein and creatinine.


87

All patients had a comprehensive baseline echocardiographic examination and

proceeded to a stress echocardiogram to rule out ischaemic heart disease. They also had

cardiac biomarkers tested; hsTnT and NT- proBNP were evaluated at baseline,

immediately after and 2 hours post exercise. All blood samples were spun and serum

was stored at -800 freezer for analysis by batch processing.

Exclusion criteria:

1. Patients with a history of previous cardio vascular disease, including coronary

artery disease, valvular heart disease, cardiomyopathy or any cardiac arrhythmia.

2. Patients who had more than mild valvular regurgitation or stenosis or significant

mitral annular calcification, were excluded from the study.

3. Patients who had positive stress echocardiogram for exercise induced ischemia

were excluded from the study.

2.2 Echocardiography

A comprehensive transthoracic echocardiogram, including 2 dimensional, colour

Doppler and tissue Doppler imaging, was performed in all recruited patients.

Commercially available ultrasound machines (Vivid 7 and vivid E9, General Electric

Medical Systems, Milwaukee, WI, USA) equipped with a 2.5-MHz variable frequency

transducer was used for echocardiographic evaluation. M mode, 2D and colour Doppler

images were obtained from standard echocardiographic views, including parasternal and

apical views with subjects in the left lateral decubitus position. Zoomed views of the

LA were obtained in 4 and 2 chamber views at high frame rate (>70fps) and an average

of 3 cardiac cycles was stored for off line measurements. Tissue Doppler imaging of the

LA was performed and images were acquired at high frame rates (~110 fps) and stored

digitally for offline analysis.


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2.2.1 Left ventricular measurements

LV end systolic and end diastolic volumes were measured by Simpson’s biplane

method from the apical 4 and 2 chamber views and the LV ejection fraction was

calculated. Left ventricular wall thickness, LV end diastolic and end systolic diameters

were measured using M mode from the parasternal long axis view and LV mass index

(LVMI) was calculated using the LV end diastolic diameter, interventricular septal and

posterior wall thickness as per ASE criteria2, 3.

2.2.2 Diastolic function

Transmitral flow velocities were obtained by placing a pulsed Doppler sample volume

at the mitral leaflet tips in the apical 4-chamber view. Peak velocity in early (E-wave)

and late diastole (A-wave) and the E-wave deceleration time (DT) were measured and

E/A ratio calculated (Fig1.9).

Pulsed wave Doppler tissue imaging was used to measure peak velocity in systole (s’)

early (e’) and late (a’) diastole with the sample volume placed at the septal and lateral

annulus 4. An average of the septal and lateral e’ velocities were calculated as per ASE

recommendations5 (Fig.2.1).

Fig. 2.1. Tissue Doppler imaging


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Left ventricular diastolic function was classified using standard echocardiographic

parameters, including transmitral peak E velocity, peak A velocity, the E/A ratio and

deceleration time. Patients were divided into groups based on diastolic function as per

ASE criteria 5 (Table 2.1).

Group Deceleration time(ms) E/A ratio e’ velocity(cm/s)

Normal 160-240 0.9-1.5 ≥10

Impaired relaxation >240 <0.9 <10

Pseudo normal 160 - 240 0.9 - 1.5 <8

Restrictive < 160 > 2.0 <5

Table 2.1 Grades of diastolic dysfunction6

2.2.3 LA measurements

Maximal LA volume was measured at end systole from zoomed images of the LA in the

apical 4 and 2 chamber views using Simpson’s biplane method; LA volume was

indexed to BSA (LAVI)7, 8. An average of 3 measurements was used for all parameters.

2.2.4 LA strain

LA strain was obtained by using two technique; tissue Doppler derived strain and 2D

speckle tracking strain.

2.2.4.1Colour tissue Doppler Strain

Colour Doppler tissue images were obtained in both the apical 4 and 2 chamber views

(septal, and lateral, inferior and anterior walls) with sector width selected to maintain

frame rates >100 fps and were analysed off-line using commercially available software

(Echo PAC version 6.2)9, 10. LA global strain and SR were calculated as an average of


90

strain measured from 4 sites (anterior, inferior, septal and lateral walls), with particular

emphasis to maintain an angle of interrogation of less than 30° with the atrial walls

(Figure 1.12 and 1.13). The sample volume (10x2mm) was placed in the superior

segments of the septal, lateral, inferior and anterior walls and tracked frame by frame, to

maintain its position within the LA wall. A Gaussian 60 smoothing was used and the

peak systolic strain and SR were measured in each segment. SR is the rate of change in

strain and is measure throughout the cardiac cycle; SR was measured in systole (SRs),

early diastole (SRe), as well as in late diastole (SRa). GS and SR for final analysis were

calculated by averaging values from the septal, lateral, inferior, and anterior walls.

2.2.4.2 Two dimensional LA strain

2D LA strain analysis was performed using customized computer software (Echo PAC,

Vingmed, General Electric, Horten, Norway), from 4- and 2-chamber LA images

acquired at high frame rates (>70 fps)11. The endocardial border was manually traced in

end-systole and the software automatically tracked the myocardial region of interest

(ROI), with QRS gating as previously accepted12. The width of the ROI was manually

adjusted (by decreasing the ROI for the thin walled atrium) to ensure proper tracking of

the myocardial wall. Peak systolic strain measurement was obtained (Figure1. 14). SRs,

SRe and SRa were measured (Figure1.15).

2.2.5 Left ventricular 2D strain

LV myocardial strain was similarly measured from apical 4- and 2-chamber images,

obtained at high frame rates (>70fps) (Figure 12). Unlike the LA, the region of interest

(ROI) used for LV strain measurement was significantly thicker. An average of 3 values

was calculated as a measure of LV strain.


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2.3 Inter and Intra observer Variability

We randomly selected 10 studies for inter and intra observer variability. LA volume,

strain and SR were analysed by 2 different individuals and by the same individual on a

different day using offline images, to evaluate inter and intra observer variability. Inter

and intra observer variability was evaluated by estimating intra class correlation

coefficients.

2.4 NT- pro BNP assay

Blood samples were collected from all subjects using a wide bore cannula from the

anticubital fossa vein. These samples were centrifuged for 20 minutes at 2000 rpm and

the serum was extracted and was stored at -800C for batch analysis. NT-pro BNP

immunoassay (Roche Mannheim, Germany) was performed by using standard

diagnostic techniques13. A cut off value of >100pg/ml, for the particular kit used

indicates cardiac involvement with left ventricular dysfunction (which includes either

systolic and/ or diastolic cardiac)14.

2.5 Statistical Analysis

All continuous variables are expressed as mean ± SD, while categorical variables are

expressed as a percentage. We used log transformation of NT-pro BNP for the statistical

calculation. An independent samples t-test analysis was performed to evaluate

differences between the CKD group and risk factor matched controls. Differences

among groups were examined by one way ANOVA with post hoc Bonferroni analysis.

Correlation between variables was analysed using Pearson’s correlation. Multiple linear

regression or logistic regression model was used to determine independent predictors as

appropriate. In order to compare the incremental predictive value of various


92

echocardiographic parameters, a baseline model containing significant

echocardiographic co-variates was constructed, and a logistic regression model was

used to obtain the ‘c’ value. Inter and intra observer variability was assessed by

intraclass correlation coefficient. Data were analysed by either Statistical Package for

Social Sciences for Windows, version 22 (SPSS, Chicago, Illinois) or SAS 9.2 (Cary,

North Carolina, USA).


93

Reference:

1. K/doqi clinical practice guidelines for chronic kidney disease: Evaluation,

classification, and stratification. American journal of kidney diseases.

2002;39:S1-266

2. Devereux RB, Alonso DR, Lutas EM, Gottlieb GJ, Campo E, Sachs I, Reichek

N. Echocardiographic assessment of left ventricular hypertrophy: Comparison to

necropsy findings. The American journal of cardiology. 1986;57:450-458

3. Foppa M, Duncan BB, Rohde LE. Echocardiography-based left ventricular mass

estimation. How should we define hypertrophy? Cardiovascular ultrasound.

2005;3:17

4. Ommen SR, Nishimura RA, Appleton CP, Miller FA, Oh JK, Redfield MM,

Tajik AJ. Clinical utility of doppler echocardiography and tissue doppler

imaging in the estimation of left ventricular filling pressures: A comparative

simultaneous doppler-catheterization study. Circulation. 2000;102:1788-1794

5. Nagueh SF, Appleton CP, Gillebert TC, Marino PN, Oh JK, Smiseth OA,

Waggoner AD, Flachskampf FA, Pellikka PA, Evangelista A.


echocardiography. Journal of the American Society of Echocardiography.

2009;22:107-133

6. Nagueh SF, Appleton CP, Gillebert TC, Marino PN, Oh JK, Smiseth OA,

Waggoner AD, Flachskampf FA, Pellikka PA, Evangelisa A. Recommendations

for the evaluation of left ventricular diastolic function by echocardiography.

European journal of echocardiography. 2009;10:165-193

7. Lang RM, Badano LP, Mor-Avi V, Afilalo J, Armstrong A, Ernande L,

Flachskampf FA, Foster E, Goldstein SA, Kuznetsova T, Lancellotti P, Muraru


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D, Picard MH, Rietzschel ER, Rudski L, Spencer KT, Tsang W, Voigt JU.

Recommendations for cardiac chamber quantification by echocardiography in

adults: An update from the american society of echocardiography and the

european association of cardiovascular imaging. Journal of the American

Society of Echocardiography. 2015;28:1-39 e14

8. Lang RM, Bierig M, Devereux RB, Flachskampf FA, Foster E, Pellikka PA,

Picard MH, Roman MJ, Seward J, Shanewise J, Solomon S, Spencer KT, St

John Sutton M, Stewart W. Recommendations for chamber quantification.

European journal of echocardiography. 2006;7:79-108

9. Eshoo S, Boyd AC, Ross DL, Marwick TH, Thomas L. Strain rate evaluation of

phasic atrial function in hypertension. Heart. 2009;95:1184-1191

10. Kadappu KK, Kuncoro AS, Hee L, Aravindan A, Spicer ST, Suryanarayanan G,

Xuan W, Boyd A, French JK, Thomas L. Chronic kidney disease is

independently associated with alterations in left atrial function.

Echocardiography. 2014;31:956-964

11. Kadappu KK, Boyd A, Eshoo S, Haluska B, Yeo AE, Marwick TH, Thomas L.

Changes in left atrial volume in diabetes mellitus: More than diastolic

dysfunction? European heart journal cardiovascular Imaging. 2012;13:1016-

1023

12. Hoit BD. Left atrial size and function: Role in prognosis. Journal of the

American College of Cardiology. 2014;63:493-505

13. Yeo KT, Dumont KE, Brough T. Elecsys nt-probnp and bnp assays: Are there

analytically and clinically relevant differences? Journal of cardiac failure.

2005;11:S84-88


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14. Pfister R, Scholz M, Wielckens K, Erdmann E, Schneider CA. Use of nt-probnp

in routine testing and comparison to bnp. European journal of heart failure.

2004;6:289-293


Chapter 3: Changes in left atrial volume in diabetes mellitus more than diastolic dysfunction?

Publication 1

Kadappu KK, Boyd A, Eshoo S, Haluska B, Yeo A, Marwick T and Thomas L. Changes in left atrial volume in diabetes mellitus: more than diastolic dysfunction?

European Heart Journal-Cardiovascular Imaging (2012) 13, 1016-1023

Declaration

I certify that this publication was a direct result of my research towards this PhD and that reproduction in this thesis doesn't breach copyright regulations


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. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Changes in left atrial volume in diabetesmellitus: more than diastolic dysfunction?†

Krishna Kishor Kadappu1, Anita Boyd1, Suzanne Eshoo2, Brian Haluska3,Anthony E.T. Yeo4, Thomas H. Marwick5, and Liza Thomas1,6*

1South Western Sydney Clinical School, University of New South Wales and Liverpool Hospital, NSW, Australia; 2University of Western Sydney and Campbelltown Hospital, NSW,Australia; 3Princess Alexandra Hospital, University of Queensland, Brisbane, Australia; 4Ingham Institute for Applied Medical Research, Liverpool, NSW, Australia; 5Cleveland Clinic,Cleveland, USA; and 6University of Sydney, NSW, Australia

Received 18 January 2012; revised 23 March 2012; accepted after revision 28 March 2012; online publish-ahead-of-print 27 April 2012

Aim To evaluate left atrial (LA) volume and function as assessed by strain and strain rate derived from 2D speckle trackingand their association with diastolic dysfunction (DD) in patients with diabetes mellitus (DM).

Methodsand results

Seventy three patients with DM were compared with age- and gender-matched normal controls; 30 patients with DMalone were compared to those with hypertension (HT) alone. The maximum LA volume, traditional measures ofatrial function, 2D strain and strain rate were analysed. The LA indexed volume (LAVI) was larger in DM groupthan that in normal controls (38.2+ 9.9 vs. 20.5+4.8 ml/m2, P , 0.0001), as well as in DM alone compared withhypertensive patients (33.9+ 10 vs. 25.7+8 ml/m2, P , 0.0001). Global strain was significantly reduced in theDM group compared with that in normal controls (22.5+8.67 vs. 30.6+8.27%; P , 0.0001) but was similarwith HT. There was a weak correlation between LAVI and global strain with increasing grades of DD (r ¼ 0.439,P , 0.0001 and r ¼ 2 0.316, P , 0.0001, respectively) in the diabetic group. However, there was no significant dif-ference in LAVI between these groups. A logistic regression analysis for predictors of LAVI demonstrated that onlydiabetes was a determinant of LAVI. Patients with diabetes showed a significant reduction in global strain comparedwith normal controls but no difference with increasing grades of diastolic function.

Conclusions LA enlargement in DM is independent of associated HT and diastolic function. LA enlargement is associated with LAdysfunction as evaluated by 2D strain. It is likely that a combination of DD and a diabetic atrial myopathy contributeto LA enlargement in patients with DM.

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Keywords Left atrium † Diabetes mellitus † 2D speckle tracking † Strain † Strain rate

IntroductionDiastolic heart failure with preserved left ventricular (LV) systolicfunction is a well-recognized entity.1 The presence of type 2 dia-betes mellitus (DM) in general has a significant association withthe development of diastolic dysfunction (DD) and subsequentheart failure.2 Moreover, the prevalence of LV DD in patientswith DM is significantly greater than that in the general populationand is reported between 43 and 75%.3,4

The ‘booster pump’ effect of left atrial (LA) contraction in thelate diastole contributes up to 30% of cardiac output5 and is of

particular importance in patients with LV dysfunction or heartfailure. Additionally, LA enlargement and dysfunction have beenconsidered surrogate markers of the chronicity and severity ofDD.6 Thus, the evaluation of LA function in patients with DM isimportant as it may reflect underlying DD while at the sametime estimating atrial contractile function contribution to cardiacoutput.

Structural and functional changes in the left atrium have beenpreviously demonstrated in patients with DM albeit in smallnumbers.7,8 Hypertension (HT), a common coexistent cardiacrisk factor is also associated with altered LA size and function.9

†Institution of study: Liverpool Hospital NSW and Princess Alexandra Hospital Brisbane.

* Corresponding author. Tel: +61 2 87383070, Email: [email protected]

Published on behalf of the European Society of Cardiology. All rights reserved. & The Author 2012. For permissions please email: [email protected]

European Heart Journal – Cardiovascular Imaging (2012) 13, 1016–1023doi:10.1093/ehjci/jes084

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mailto:[email protected]


It has been established that tissue Doppler-derived strain imagingcan assess LA function in varying conditions with LA dysfunc-tion.10– 13 However, tissue Doppler-derived strain measurementsare time intensive and limited by angle dependency.14 LA straincan also be derived from two-dimensional (2D) images byspeckle tracking which is a semi-automated process not limitedby angle dependency.15

The aim of the present study was to (i) evaluate the LA size inpatients with type 2 DM and evaluate the independent effect ofDM on the LA size compared with controls and those with HTalone, (ii) evaluate LA function by 2D speckle tracking-derivedstrain compared with a group of age-matched normal subjectsand those with HT alone and (iii) to evaluate the LA volumechange with varying grades of DD in patients with DM. We add-itionally hypothesized that LA dysfunction would be present inpatients with DM due to the increased prevalence of DD in DMwith increasing LA size with worsening grades of diastolic function.

Methods

Study populationSeventy-six subjects with type 2 DM were recruited from the Prin-cess Alexandra Hospital, Brisbane. Patients were identified fromthe cardiology and endocrinology department; 43 of the 76patients had coexistent mild HT (mean systolic BP: 140+14 mmHg and mean diastolic BP: 81+ 8 mmHg). Three patientswere excluded from the final analysis due to suboptimal imagequality. All recruited patients were on therapy for DM includingdiet control, oral hypoglycemic agent or insulin. Study approvalwas obtained from the human research and ethics committeeand all recruited patients provided written consent. A comprehen-sive transthoracic echocardiogram was performed in all recruitedpatients. There was no ECG or echocardiographic evidence of cor-onary artery disease and all patients underwent a stress echocar-diogram to rule out latent ischaemia. Patients were excludedfrom the study, if they had greater than mild mitral or aortic regur-gitation or aortic stenosis or any degree of mitral stenosis. None ofthe recruited patients or controls had any history of congestiveheart failure and all patients had a normal LV ejection fraction.

Age-matched ‘normal’ subjects were identified from a depart-mental database at Liverpool Hospital, Sydney. These healthyvolunteers were recruited from the community and were careful-ly screened for a history of cardiovascular, peripheral vascular orcerebrovascular disease and for the presence of cardiovascularrisk factors including HT, DM, hypercholesterolemia. They hadno abnormal findings on routine physical examination, werenormotensive and had a normal ECG and echocardiogram andwere not receiving any cardio-active medications. Thirty patientswith mild HT were identified from a departmental database andrecruited as a comparator group. These subjects had systolicpressure .140 but ,160 mmHg and diastolic pressure .90but ,100 mmHg. Blood pressure recordings were performedon three separate times and all previously recorded measure-ments were ,160/100 mmHg. The HT group had no other asso-ciated cardiac risk factor. A subgroup comparison of the 30

patients with DM alone was performed with the 30 patientswith HT.

Conventional echocardiographyA commercially available ultrasound machine (Vivid 7, GeneralElectric Medical Systems, Milwaukee, WI, USA) equipped with a2.5-MHz variable frequency transducer was used for echocardio-graphic evaluation. 2D and colour Doppler images were obtainedfrom standard echocardiographic views, including parasternal andapical views with patients and subjects in a left lateral decubitusposition. Tissue Doppler imaging was used to obtain systolic anddiastolic velocities from the mitral annulus. 2D images wereacquired at high frame rates (�70 fps) and stored digitally foroffline strain analysis.

Left ventricular measurementsLeft ventricular wall thickness, LV end diastolic (LVEDD) and endsystolic (LVESD) diameters were measured using M mode fromthe parasternal long axis view. LV end systolic and end diastolicvolumes were measured by Simpson’s biplane method from theapical four- and two-chamber views and the LV ejection fractionwas calculated. LV mass index (LVMI) was calculated using the dia-stolic measurements of left ventricular internal diameter, interven-tricular septal thickness and posterior wall thickness.16

Transmitral flow velocities were obtained by placing a pulsedwave Doppler sample volume at the mitral leaflet tips in theapical four-chamber view. Peak velocity in early (E-wave) andlate diastole (A-wave) and E-wave deceleration time (DT) weremeasured and E/A ratio calculated. Pulsed wave Doppler tissueimaging was used to measure the peak velocity in early (E′) andlate (A′) diastole with the sample volume placed at the septaland lateral annulus.17 An average of the septal and lateral E′ veloci-ties were calculated as per ASE recommendation.18 The E/E′ ratiowas calculated as an estimate of LV diastolic pressure.17

Diastolic classificationLV diastolic function was classified as normal (DT ¼ 160–240 ms,E/A ratio ¼ 0.9–1.5, E′ velocity ≥ 10 cm/s), impaired relaxation(DT . 240 ms, E/A ratio , 0.9, E′ velocity , 10 cm/s), pseudo-normal (DT ¼ 160–240 ms, E/A ratio ¼ 0.9–1.5, E′ velocity ,

8 cm/s) and restrictive (DT , 160 ms, E/A ratio . 2.0, E′

velocity , 5 cm/s) as per previously defined criteria.18,19 In threepatients, E′ velocity was between 8 and 10 with DT 160–240and the E/A ratio ¼ 0.9–1.5, with a E/E′ of ,10. These patientswere grouped under the normal diastolic function group. The DMgroup was divided into groups based on diastolic function: Group1, normal (n ¼ 16); Group 2, impaired relaxation (n ¼ 33); Group3, pseudo normal (n ¼ 23) and restrictive (n ¼ 1). As only onepatient had restrictive filling, this patient was combined with the 23patients with pseudonormal filling pattern to comprise Group 3.

Traditional LA measurementsThe LA volume was measured using the prolate ellipse method20

incorporating LA diameters from three planes; the maximum LAvolume was indexed to body surface area (LAVI).

Atrial function was estimated using traditional measures includ-ing the peak transmitral A-wave velocity, A-wave velocity time

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integral (VTI) and the atrial fraction (A-wave VTI/total mitral inflowVTI).

An average of three measurements was used for the finalanalysis.

2D speckle tracking strain imagingOf the 76 recruited patients with DM, strain measurements couldonly be obtained in 73 (96%). 2D speckle tracking strain and strainrate (SR) analysis, using customized computer software (EchoPAC,Vingmed, General Electric, Horten, Norway) was performed usinga zoomed view of the LA from the apical four chamber acquired at�70 fps. The LA endocardium was manually drawn in end systole;thereafter the endocardial borders were automatically tracked bythe computer software throughout the cardiac cycle. The LA myo-cardial width was adjusted by varying the thickness of the ROIapplied to track the LA borders. The LA myocardium wasdivided into six segments (basal, mid-, and apical segments of theseptum and lateral wall, respectively). The software displayedpeak longitudinal systolic strain (S) (Figure 1A), systolic (S-SR),early diastolic (E-SR), and late diastolic (A-SR) atrial strain ratesfor each of the six individual segments (Figure 1B).

LA S-SR is measured during the passive stretching of the LAduring left ventricular systole and is thus an index of LA reservoirfunction.21 Similarly, the E-SR and A-SR have been used as indicesof LA conduit and LA contractile function, respectively.22 Data pre-sented are an average of three measurements.

Statistical analysisAll values are expressed as mean+ SD. An independent samples‘t’-test analysis was performed to evaluate the differencesbetween the DM group and normal controls. Differences amongthose with DM alone (n ¼ 30), HT group and normal controlswere examined by one-way ANOVA with post hoc Bonferroni ana-lysis. Data were considered significant if P , 0.05. Spearman’s rankcorrelation was used to assess the correlation between LAVI andglobal strain with grades of DD. Differences among the DMgroup based on diastolic function grade were examined byone-way ANOVA with post hoc Bonferroni analysis. Data wereconsidered significant if P , 0.05. Data were analysed using SPSS(version 17.0, SPSS, Inc., Chicago, Illinois). A logistic regression ana-lysis was performed using SAS 9.2 (Cary, NC, USA) to examine therelationship between LAVI and global strain with other covariatesincluding age, diastolic grade, E/E′ ratio, LVMI, the presence of HTand patient group (i.e. the presence of diabetes).

ResultsA total of 73 DM patients and an equal number of age-matchedcontrols were included in the final analysis. Demographic data ofthe DM group vs. controls are presented in Table 1. As expected,the DM group weighed more than controls (92.3+ 20.3 vs.74.2+14.6 kg, P , 0.0001) and had a higher BSA (2.1+ 0.25 vs.1.86+0.21 m2, 0.0001). In the DM group, 16 subjects hadnormal diastolic function (Group 1), 33 impaired relaxation(Group 2) and 23 pseudonormal or restrictive filling (Group 3)as stated earlier. Thus, 78% of the DM group had some form ofDD, while 33% had Grade 2 or more DD. In contrast 89% patients

in the control group had normal diastolic function and the remain-ing 11% (8 patients) had impaired relaxation. Forty-three of the 73patients had mild HT: 12 in Group 1, 16 in Group 2, and 15 inGroup 3 had coexistent mild HT.

Demographic data in the subgroup with DM alone vs. patientswith HT and controls are presented in Table 2. The HT groupwas older, and not surprisingly had a higher systolic and diastolicblood pressure. The DM group weighed more than both healthycontrols and HT group and consequently had a higher BSA.

LV systolic and diastolic parametersLV end diastolic and end systolic diameters were similar in the DMgroup and controls. Although LV ejection fraction was in thenormal range in both groups, the LV ejection fraction was higherin the DM group (Table 1). The LV mass was higher in the DMgroup but when indexed to BSA (LVMI), no statistically significantdifferences were observed between groups (Table 1). As expected,traditional LV diastolic function parameters including peak E and Avelocities, E/A ratio, DT, and E/E′ were abnormal in patients withDM compared with controls (Table 1).

Comparison between the subgroup of patients with DM alonevs. HT group and normal controls demonstrated LV wall thicknesswas increased in the HT group, with a significantly greater indexedLV mass. LVEF was in the normal range in the three groups withLVEF higher than controls in both the DM and HT groups. Trad-itional LV diastolic parameters were altered in the DM and HTgroups (Table 2).

LA volume and functionThe LA maximum volume and LAVI were significantly larger in theDM group than that in normal controls (Table 1). The peak A vel-ocity was higher in the DM group. Although the A-wave VTI wassimilar, a higher atrial fraction as well as the A′ velocity wasobserved in the DM group (Table 1). In the subgroup comparison,LAVI increased only in the DM group compared with both thegroups with HT and normal controls. Parameters of atrial functionincluding A-wave VTI, atrial fraction, and A′ velocity were similar inthe DM and HT groups.

Atrial strain measurementsPeak positive 2D strain was reduced in the DM group across all sixsegments (Table 3). Global strain, derived as an average of six seg-ments, was 22.5+8.7% in the diabetic group vs. 30.6+ 8.3% inthe normal control group (P value , 0.0001; Table 3). Patients inthe DM group had altered phasic LA function with impaired LAreservoir and conduit functions as indicated by a reduction in LAS-SR and LA E-SR, respectively. LA A-SR, an indicator of LA con-tractile function, was also reduced in the DM group (Table 3). Inthe subgroup comparison between the DM and HT groups vs.controls, LA strain was similar in the DM and HT groups with asignificant reduction in S-SR, E-SR, and A-SR in the DM group(Table 4).

Determinants of LAVI in DMWe examined the relationship between LAVI to age, group (DMand control groups), E/E′ ratio, LVMI, diastolic grade, LVEF, and

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presence of HT to determine univariate predictors of LAVI. Thesepredictors were entered into a logistic regression analysis(Table 5). In this model, a statistically significant relationship was

only present between LAVI and presence of diabetes (P ,

0.0001), adjusting for all other covariates including the diastolicgrade and presence of HT. The logistic regression model

Figure 1 (A) Global strain of the left atrium obtained from the apical four-chamber view and (B) strain rate obtained from the four-chamberview demonstrating systolic (S-SR) and diastolic strain rate (E-SR and A-SR).


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demonstrated a predictive value (power) of 0.88 for the patientgroup (i.e. presence of diabetes) to LAVI.

LA volume and dysfunction in the DMgroup based on severity of diastolicdysfunctionA weak correlation was observed between varying grades of DDand LAVI by Spearman’s rank correlation (r ¼ 0.439, P , 0.0001).Similarly, a weak negative correlation was seen with global strainand grades of DD (r ¼ 2 0.316, P , 0.0001).

A subgroup analysis for varying grades of LVDD was performedwithin the DM group using ANOVA with post hoc Bonferoni cor-rection. However, there was no significant difference in LAVI,global strain or systolic or diastolic SR measurements amongvarying grades of diastolic function in the DM group (Table 6).

DiscussionOur study confirms the high prevalence of DD in DM, with 78% ofpatients with DM manifesting some diastolic abnormality. We de-liberately included a significant proportion with coexistent mild HTas would be seen in the routine clinical scenario. We demon-strated LA enlargement in patients with DM that was independentof the effects of HT and grade of DD. There was associated atrialdysfunction that was also independent of the grades of DD in thisgroup. The subgroup analysis performed between patients withDM alone and a group with HT additionally demonstrated a signifi-cantly larger LAVI in the DM group.

LA sizeLA enlargement has previously been reported in subjects with DM.Poulsen et al.1 demonstrated moderate-to-severe LA enlargement(LA volume index . 32 ml/m2) in a third of their study populationcomprising 305 subjects with DM. However, only 40% had abnor-mal diastolic function in their study group. In our study population,two-thirds of the DM group had DD and more than half had asso-ciated HT. LA enlargement is a surrogate marker of LVDD6 andgiven the high prevalence of DD in the DM group is a likely con-tributor. LAVI was larger in the patients with DM alone thanthose in HT.

In the current DM group, 16 patients were classified as having‘normal’ diastolic function; interestingly LA enlargement waspresent in this group as well. Further, no significant differencewas noted in the LA volume across the three grades of diastolicfunction. These observations are similar to that reported byJarnert.8 In that study, mean LAVI was increased even in the sub-group with normal diastolic function. Despite a significant increasein the maximum LAV with grades of DD, LAVI failed to demon-strate any significant difference between grades of DD. This sug-gests that an altered LV diastolic function in DM onlycontributes in part to observed LA changes. Thus, it is likely thatan independent atrial cardiomyopathy associated with DM maybe a likely contributor to LA enlargement.

LA functionEchocardiographic parameters to measure LA function are stillevolving. Global and phasic LA function using 2D strain and SRparameters are feasible and have been used to assess LAdysfunction.14,15

2-D speckle tracking-derived strain analysis was demonstratedto be a feasible method to assess LA longitudinal strain inhealthy subjects.23 2D strain measurements are semi-automatedwith less variability compared with tissue Doppler-derivedstrain.24 In the current study, both global and segmental systolicstrains were significantly reduced in the DM group as previouslydemonstrated using TDI7 and velocity vector imaging (VVI)-derivedstrain.8 Global strain was also similarly reduced in the group withHT.

Muranaka et al.7 suggested that the fibrotic change in the atriumin diabetes is responsible for the reduction in atrial phasic functionas measured by SR parameters. Asbun et al.25 also demonstratedthat diabetic cardiomyopathy causes atrial fibrosis with a conse-quent reduction in LA compliance.25 Thus, atrial fibrosis may

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Table 1 Demographic and echocardiographic (leftventricular and left atrial) parameters

Parameters DM group(n 5 73)

Normal(n 5 73)

P value

Age (years) 43+11 43+10 0.79

Height (cm) 168.1+9.4 170.6+9.1 0.10

Weight (kg) 92.25+20.30 74.19+14.61 ,0.0001*

BSA (m2) 2.09+0.25 1.86+0.21 ,0.0001*

Co-existenthypertension

43 (59%) 0

Smokers 35 (48%) 0

LVEDD (cm) 4.7+0.56 4.7+0.79 0.7

LVESD (cm) 2.8+0.52 2.9+0.47 0.8

LVEF (%) 67+5 61+4 0.01*

Peak E velocity (m/s) 0.69+0.14 0.73+0.03 0.03*

Peak A velocity (m/s) 0.7+0.15 0.59+0.19 ,0.0001*

E/A ratio 1.02+0.26 1.34+0.41 ,0.0001*

DT (ms) 224.9+35.5 208.2+37.5 0.006*

S′ velocity (cm/s) 6.9+1.4 7.4+1.4 0.02*

E′ velocity (cm/s) 6.5+1.9 9.5+2.2 ,0.0001*

E/E′ ratio 11.34+3.4 8.07+2.1 ,0.0001*

LV mass (g) 177.9+50.5 153.3+58.5 0.008*

LVMI (g/m2) 85+21 81+27 0.37

LAV (ml) 79.8+29.3 38.2+9.9 ,0.0001*

LAVI (ml/m2) 38.2+9.9 20.5+4.8 ,0.0001*

A VTI (cm) 7.8+1.9 7.6+2.3 0.59

A′ velocity (cm/s) 9.5+1.8 8.8+1.6 0.029*

Atrial fraction (%) 38.19+7.59 35.48+8.15 0.04*

A velocity, late mitral inflow velocity; A′ velocity, late diastolic mitral annular tissueDoppler velocity; BSA, body surface area; DT, deceleration time; E velocity, earlymitral inflow velocity; E′ velocity, early diastolic mitral annular tissue Dopplervelocity; LAV, maximum left atrial volume; LAVI, maximum left atrial volumeindexed to BSA; LV, left ventricle; LVEDD, left ventricular end diastolic diameter;LVEF, left ventricular ejection fraction; LVESD, left ventricular end systolicdiameter; LVMI, left ventricular mass indexed to BSA; S′ velocity, systolic mitralannular tissue Doppler velocity; VTI, velocity time integral.*P value , 0.05 compared with normal.


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alter LA compliance with a reduction in reservoir function asobserved by the reduced S-SR. E-SR was reduced and is the reflec-tion of altered LV relaxation with a consequent reduction in the LAconduit function. Thus, it is likely that atrial fibrosis is greater in theDM as both S-SR and E-SR were higher in the HT group.

Traditional parameters including transmitral A velocity, atrialfraction, and A′ velocity were increased in subjects with DM aswell as in the group with HT. These indicate a compensatory in-crease in blood flow in late diastole given the reduced early diastol-ic filling consequent to LV DD. The increased LA volume wouldadditionally result in increased flow during atrial contraction.However the A-SR was decreased, suggesting altered intrinsic LAfunction with a reduction in atrial deformation during its contract-ile phase even compared with the HT group.

LA changes and grades of diastolicdysfunctionLA enlargement was present in the DM group even in patients withnormal diastolic function; only a weak correlation was observedbetween LAVI and varying diastolic grades. Despite the presence

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Table 2 Demographic and echocardiographic parameters in diabetes mellitus subgroup vs. hypertension group vs.controls

Parameters DM only (n 5 30) Normal (n 5 73) HT group (n 5 30) P value

Age (years) 49+12† 43+10 56+13* ,0.0001

Height (cm) 167.1+8 170.6+9.1 168.5+11 0.22

Weight (kg) 94+20*,† 74.19+14.61 81.5+13 ,0.0001

BSA (m2) 2.12+0.3*,† 1.86+0.21 1.95+0.2 ,0.0001

Systolic BP (mm Hg) 118.5+11*,† 125.5+11 145.7+17* ,0.0001

Diastolic BP (mm Hg) 74.2+7.5† 77.8+6.9 84.4+9.6* ,0.001

LVEDD (cm) 4.6+0.53 4.7+0.79 4.8+0.4 0.65

LVESD (cm) 2.7+0.54 2.9+0.47 2.9+0.51 0.16

LVEDV(ml) 85+18.7 89+21.4 94+19.5 0.09

LVESV(ml) 29+9.6* 35+10.4 33+10.9 0.001

LVEF (%) 63+13.7 61+4 66+6* 0.001

Peak E velocity (m/s) 0.66+0.13* 0.73+0.03 0.71+0.15 0.05

Peak A velocity (m/s) 0.7+0.17* 0.59+0.19 0.73+0.26* 0.002

E/A ratio 0.98+0.27* 1.34+0.41 1.05+0.36* ,0.0001

DT (ms) 230.1+38.9 208.2+37.5 240.4+40.2* 0.002

S′ velocity (cm/s) 6.4+0.9* 7.4+1.4 7.2+1.4 0.002

E′ velocity (cm/s) 5.9+1.9*† 9.5+2.2 7.3+2* ,0.0001

E/E′ ratio 12.03+3.7* 8.07+2.1 10.67+4.7* ,0.0001

LVMI (g/m2) 82+26† 81+27 98+13* 0.007

LAV (ml) 71.4+21.6*,† 38.2+9.9 50.2+16.5* ,0.0001

LAVI (ml/m2) 33.9+10.5*,† 20.5+4.8 25.7+8.1* ,0.0001

A VTI (cm) 7.3+1.8 7.6+2.3 8.3+2.9 0.23

A′ (cm/s) 9.2+2.1 8.8+1.6 10+2* 0.02

Atrial fraction (%) 36.84+8.57 35.48+8.15 39.67+11.12 0.11

A velocity, late mitral inflow velocity; A′ velocity, late diastolic mitral annular tissue Doppler velocity; BSA, body surface area; DT, deceleration time; E velocity, early mitral inflowvelocity; E′ velocity, early diastolic mitral annular tissue Doppler velocity; LAV, maximum left atrial volume; LAVI, maximum left atrial volume indexed to BSA; LVEDD, leftventricular end diastolic diameter; LVEDV, left ventricular end diastolic volume; LVEF, left ventricular ejection fraction; LVESD, left ventricular end systolic diameter ,LVESV, leftventricular end systolic volume; LVMI, left ventricular mass indexed to BSA; S′ velocity, systolic mitral annular tissue Doppler velocity; VTI, Velocity time integral.*P , 0.05 compared with normal; †P , 0.05 compare with the HT group.

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Table 3 2D strain and strain rate in patients withdiabetes and normal controls

Parameters DM group(n 5 73)

Normal(n 5 73)

P value

Basal septum strain (%) 31.5+16.3 42.9+17.9 ,0.0001*

Mid septum strain (%) 31.1+13.6 42.4+15.9 ,0.0001*

Apical septum strain (%) 22.2+13.5 28.5+14.6 0.008*

Basal lateral strain (%) 35.4+17.4 49.9+20 ,0.0001*

Mid lateral strain (%) 21.6+12.7 28.3+13 0.002*

Apical lateral strain (%) 10.9+14.9 17.3+12.4 0.005*

Global strain (%) 22.5+8.7 30.6+8.3 0.0001*

S-SR (s-1) 1.1+0.4 1.7+0.4 ,.0001*

E-SR (s-1) 0.9+0.4 1.6+0.6 ,.0001*

A-SR (s-1) 1.1+0.5 1.6+0.6 ,.0001*

A-SR, late diastolic strain rate; DM, diabetes mellitus; E-SR, early diastolic strainrate; S-SR, systolic strain rate.*P value , 0.05 compared with normal.


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of HT in �60% of the diabetic patients, we observed no differencein LAVI or global or phasic atrial function as demonstrated by strainand SR parameters between varying grades of DD.

Jarnert et al.8 examined 87 patients, the majority (n ¼ 60) ofwhom had normal diastolic function. They observed no significantdifference in LAVI or in systolic strain rate between groups.However, they demonstrated a reduction in systolic strainbetween the normal and moderate DD groups (n ¼ 14). In our

group of patients, we observed no difference in global or phasicatrial function as demonstrated by strain and SR parametersbetween varying grades of DD. This would suggest that a coexist-ent atrial cardiomyopathy might independently alter the LA sizeand function in diabetes with the additive effects of LVDD.

Study limitationThe sample size of the study is modest and our findings need to bevalidated in a larger population. A significant number of DMpatients had coexistent mild HT; however, a subgroup comparisonbetween patients with DM alone to the group with mild HT wasperformed to examine these differences. Failure to observe differ-ences in the LA volume and function between varying grades ofDD may represent a beta error.

The normal controls did not undergo a stress test or stressechocardiogram to rule out latent ischemia. However, none ofthe controls had significant cardiac risk factors.

The use of another imaging modality such as magnetic reson-ance imaging to assess the LA size and function was consideredbeyond the scope of the present study.

2D speckle tracking strain imaging is reliant on image quality andframe rate, even though this is angle independent. Patients withpoor imaging windows (n ¼ 3) were excluded based on poorimage quality as measurements could not be adequately inter-preted. Hence, the results are representative of the populationwhere 2D speckle tracking is possible.

Left atrial volume and function may be affected by patient medi-cation especially beta blockers. Only three patients in the DMgroup and two in the HT group were on beta-blockers. Renal func-tion too could alter left atrial parameters; however, in our diabeticpatient group, only three patients had mild renal impairment (cre-atinine of 168, 130, and 110 mmol/L). Given the small number ofpatients with renal impairment and relatively small numbers onbetablockers, performing subgroup analysis would not be possible.

ConclusionDiabetes causes LA enlargement that is independent of the effectsof coexistent HT and DD. Thus, LA enlargement with associatedLA dysfunction is likely due to the combination of DD and a coex-istent atrial myopathy consequent to DM. Longitudinal studies

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Table 4 Differences in strain and strain rate in thediabetes mellitus only group vs. the hypertension groupvs. controls

Parameters Normal(n 5 73)

DM(n 5 30)

HT(n 5 30)

P value

Global strain (%) 30.7+8.1 25.2+10.5* 24.4+8.6* 0.001

S-SR (s-1) 1.7+0.4 1.2+0.6*,† 1.5+0.4 ,0.0001

E-SR (s-1) 1.6+0.5 1+0.4*,† 1.4+0.6 ,0.0001

A-SR (s-1) 1.6+0.6 1.2+0.5*,† 1.7+0.5 ,0.0001

SR, late diastolic strain rate; DM, diabetes mellitus; E-SR, early diastolic strain rate;HT, hypertension; S-SR, systolic strain rate.*P , 0.05 compared with normal.†P , 0.05 compared with the HT group.

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Table 5 Logistic regression analysis for predictors ofleft atrial indexed volume

Parameter Beta Odds ratio 95% CI P value

DM group 3.36 28.85 5.0–166.47 0.0002

E/E′ . 8, ,15 -0.39 0.68 0.17–2.71 0.58

E/E′ . .15 -0.47 0.63 0.09–4.33 0.64

HT 0.35 0.62 0.42–4.77 0.57

Diastolic grade 1 1.06 2.89 0.77–10.76 0.11

Diastolic grade 2 0.74 2.1 0.5–8.33 0.31

Predictive power, c, is 0.88. DM, diabetes mellitus; E velocity, early mitral inflowvelocity; E′ velocity, early diastolic mitral annular tissue Doppler velocity; HT,hypertension.

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Table 6 Differences in left atrial and left ventricular parameters in patients with diabetes based on diastolic functiongrade

Parameters Normal (n 5 16) Impaired (n 5 33) Pseudonormal (n 5 24) P value

LAVI (ml/m2) 38.5+12.2 37.4+14 39.2+14.9 0.11

Global strain (%) 23.5+1.9 22.5+1.7 22.2+1.8 0.87

S-SR (s-1) 1.1+0.3 1.2+0.5 1+0.4 0.4

E-SR (s-1) 0.8+0.4 0.9+0.4 0.9+0.4 0.81

A-SR (s-1) 1.1+0.4 1.1+0.5 1.1+0.5 0.98

LVMI (g/m2) 73.9+13.8 87.1+21.5 89.1+22.2 0.06

A-SR, late diastolic strain rate; E-SR, early diastolic strain rate; LAVI, indexed maximum left atrial volume; LVMI, indexed left ventricular mass; S-SR, systolic strain rate.


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including larger patient numbers are required to ascertain if para-meters of atrial size and function may predict future adverse car-diovascular outcomes in a diabetic population.

AcknowledgementK.K.K. is currently receiving National Health and Medical ResearchCouncil (NHMRC) scholarship.

Conflict of interest: none declared.

FundingNational Health and Medical Research Council (NHMRC) scholarshipNo. APP1018215.

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Chapter 4: Chronic Kidney Disease is Independently Associated with Alterations in Left Atrial Function

Publication 2

Kadappu KK, Kuncoro A, Hee L, Aravindan A, Spicer S, Suryanarayanan G, Xuan W, Boyd A, French J, and Thomas L.

Chronic Kidney Disease is Independently Associated with Alterations in Left Atrial Function Echocardiography. 2014 Sep;31(8):956-64.

Declaration


Krishna Kishor Kaclappu

97

Chronic Kidney Disease is Independently Associatedwith Alterations in Left Atrial Function

Krishna K. Kadappu, M.D.,*,†,‡ Ario S. Kuncoro, M.D.,§ Leia Hee, Ph.D.,†,¶ Anathakrishnapuram Aravindan, M.D.,‡,**Stephen T. Spicer, Ph.D.,*,** Govindarajan Suryanarayanan, M.D.,‡,** Wei Xuan MAppStat, Ph.D.,*,††Anita Boyd, Ph.D.,* John K. French, Ph.D.,*,† and Liza Thomas, Ph.D.*,†,¶

*South Western Sydney Clinical School, The University of New South Wales, Sydney, Australia; †CardiologyDepartment, Liverpool Hospital, Liverpool, Australia; ‡Cardiology Department, Campbelltown Hospital,University of West Sydney, Campbelltown, Australia; §Department of Cardiology and Vascular Medicine,University of Indonesia National Cardiovascular Centre Harapan Kita, Jakarta, Indonesia; ¶University ofSydney, Sydney, Australia; **Renal Department, Liverpool Hospital, Liverpool, Australia; and ††InghamInstitute of Applied Medical Research, Liverpoool, Australia

Background: Chronic kidney disease (CKD) is associated with increased cardiovascular morbidity andmortality; hence detection of early cardiovascular involvement in CKD is important to prevent futureadverse cardiovascular events. Left atrial (LA) enlargement and dysfunction has been reported in endstage renal disease. However, there is a paucity of published data regarding the evaluation of LA func-tion in CKD using noninvasive imaging parameters. In this study, we evaluated biplane LA volume aswell as LA function (LA global systolic strain (GS) and strain rate [SR]) in stage 3 CKD patients (eGFR 30–59 mL/min per 1.73 m2) to determine if LA function parameters are more significantly altered by thepresence of CKD in addition to changes due to hypertension alone. Methods: Thirty-three CKD patients(eGFR 30–59 mL/min per 1.73 m2) with hypertension were compared to 33 normal controls and 34hypertensive (HT) subjects with normal renal function; all participants underwent a detailed transtho-racic echocardiogram. Indexed biplane LA volume (LAVI), LA segmental function, and GS and SR (sys-tolic, early, and late diastole) derived from tissue Doppler imaging (TDI) were measured. Univariatepredictors of LA strain were determined. Multiple logistic regression analysis was used to examine theeffect of patient group (i.e. CKD) on GS and SR as well as LAVI. Results: Left atrial volume indexed wassignificantly increased in both the HT and CKD with HT group compared to normal controls(28 � 9 mL/m2 vs. 28 � 9 mL/m2 vs. 23 � 5 mL/m2, respectively, P = 0.02). However, LAVI was simi-lar in the HT and CKD with HT group (28 � 9 mL/m2 vs. 28 � 9 mL/m2; P = NS). LA GS and SR werereduced in both the CKD with HT and HT group, compared to controls. However, a significantly lowerLA GS was present in the CKD with HT group (Controls vs. HT vs. CKD with HT: 54.9 � 14.5% vs.34.5 � 6.2% vs. 25.7 � 9.3%, respectively; P = 0.001). To examine the effect of group, (i.e. presenceof CKD) multiple logistic regression analysis was performed with univariate predictors including indexedleft ventricular mass (LVMI), LV diastolic grade, LAVI, peak A-wave velocity, b-blocker therapy, GS andSR; this demonstrated that CKD had an independent effect on LA GS and SR (systolic, early, and late dias-tole). GS demonstrated moderate correlation with systolic blood pressure (r = �0.5, P = 0.01), diastolicgrade (r = �0.5, P = 0.01), E′ velocity (r = 0.6, P = 0.0001), peak A velocity (r = �0.5, P = 0.004), andLAVI (r = �0.6, P = 0.002). Conclusions: Left atrial dysfunction is evident in stage 3 CKD with associ-ated LA enlargement. This study demonstrates that LA GS and SR were reduced in the CKD groupdespite similar LAVI in the CKD with HT and HT group. Hence LA GS and SR may be a more sensitivenoninvasive tool to detect cardiovascular involvement in CKD. (Echocardiography 2014;31:956–964)

Key words: color Doppler tissue imaging, diastolic function, left atrial volume, strain, chronic kidneydisease, strain rate imaging

Chronic kidney disease (CKD) is associatedwith increased cardiovascular morbidity includ-

ing coronary artery disease,1 heart failure2 as wellas atrial fibrillation.3 CKD is an independent riskfactor for cardiovascular disease (CVD) and clini-cal cardiovascular risk calculators such as the Fra-mingham predictive instrument under estimatefuture cardiac events in stage 3 CKD (eGFR 30–59 mL/min per 1.73 m2).4 Hence there is a need

Address for correspondence and reprint requests: Liza Tho-mas, Ph.D., Cardiology Department, Liverpool Hospital, Eliza-beth Street, Liverpool, NSW 2170, Australia.Fax: +61 2 87383054;E-mail: [email protected]

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for noninvasive cardiac markers over and aboveclinical risk factors to estimate individual patientrisk to predict future adverse cardiac events inCKD patients. Identification of patients at riskcould alert physicians to monitor cardiovascu-lar risk and implement aggressive risk factorcontrol.

Left atrial (LA) enlargement has beenreported in end stage renal disease (ESRD) andLA volume is an independent prognostic factorin ESRD.5 Changes that may cause alterationsin LA size and function are multifactorial inESRD. Left ventricular (LV) hypertrophy andsystolic dysfunction5 are reported as major con-tributors. Diastolic dysfunction due to LVhypertrophy is also reported in early stages ofrenal disease.6 However, LA involvement inCKD is not well described. CKD is commonlyassociated with hypertension (HT) and diabetesmellitus, both of which may independentlyalter LA properties.7,8 CKD also results inchanges in the renin-angiotensin-aldosteronesystem (RAAS), which may enhance atrial fibro-sis 3,9,10 with consequent LA enlargement anddysfunction.

The LA has multiple functions; it acts as a res-ervoir for blood during ventricular systole, as aconduit for the passage of blood from the pul-monary veins to the LV in early diastole and as acontractile chamber to augment LV filling in latediastole.11 Tissue Doppler imaging (TDI) strain(GS) and strain rate (SR) techniques, which evalu-ate myocardial deformation,12 enable the evalua-tion of atrial deformation throughout the cardiaccycle, providing a sensitive and accurate assess-ment of global and phasic atrial function.13 TDIallows noninvasive assessment of global and seg-mental LA function.14 TDI-derived GS and SR is afeasible technique and has been used to assessLA function in a variety of conditions with LA dys-function.15–18

The overall aim of this study was to evaluatethe independent effect of mild CKD (stage3–eGFR 30–59 mL/min per 1.73 m2) and HT onLA size and function. This was determined byspecific aims to (1) evaluate LA size in patientswith stage 3 CKD with associated HT and evalu-ate the independent effect of renal dysfunctionon LA size by comparison to a group of normalcontrols and a group with HT with normal renalfunction; (2) evaluate LA function by tissueDoppler derived strain in stage 3 CKD patientswith HT compared to a group of age-matchednormal subjects and patients with HT with nor-mal renal function. We hypothesized that thepresence of CKD would have an additive effect,independent of HT, resulting in greater LAenlargement and consequent greater degree ofLA dysfunction.

Methods:Thirty-three stage 3 CKD patients (eGFR 30–59 mL/min per 1.73 m2) with hypertension werecompared to 33 normal controls and 34 HT sub-jects with normal renal function.

Study Population:Thirty-three subjects with stage 3 CKD (eGFR of30–59 mL/min per 1.73 m2 by modified diet inrenal disease formula) were recruited from Liver-pool Hospital, Sydney, Australia. Staging of CKDwas done as per standard criteria.19 We onlyincluded patients with an eGFR <60 mL/min per1.73 m2 as this is the cutoff value by definitionfor CKD where there is increased prevalence ofCVD risk factors.20 We also excluded stage 4 CKDas there is an increased incidence of fluid over-load and LV hypertrophy,21 which in turn altersLA size and function. Patients were identifiedfrom the renal outpatient department; allpatients had coexistent mild HT (mean systolicBP = 133 � 4.6 mmHg and mean diastolicBP = 74 � 2.1 mmHg) and were on antihyper-tensive medication. The causes for renal impair-ment are as listed: HT (n = 19), drug induced,renal calculus, chronic inflammatory nephropa-thy, glomerulo nephritis, ischemic nephropathyand chronic granulomatous nephropathy (n = 2in each category), hepatitis, single kidney, andpoly cystic kidney disease (n = 1 in each cate-gory). Study approval was obtained from theHuman research and ethics committee SouthWestern Area Health Service (HREC/09/LPOOL/53), and all recruited patients provided writteninformed consent.

A comprehensive transthoracic echocardio-gram including two-dimensional, 2D, colorDoppler, and TDI was performed in all recruitedpatients. There was no ECG or echocardiographicevidence of coronary artery disease and allpatients underwent a stress echocardiogram torule out occult ischemia; one patient wasexcluded due to evidence of ischemia on stresstesting. Patients with greater than mild mitral oraortic regurgitation, aortic stenosis or any degreeof mitral stenosis were excluded from the study.No patient had more than mild mitral annularcalcification. None of the patients or controls hada previous history of congestive heart failure oratrial fibrillation and had a normal LV ejectionfraction.

Age-matched “normal” control subjects(n = 33) were obtained from a departmentaldatabase. These healthy volunteers wererecruited from the community and were carefullyscreened for a history of cardiovascular, periph-eral vascular or cerebrovascular disease, and forthe presence of cardiovascular risk factors includ-

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ing HT, diabetes mellitus, and hypercholesterol-emia. They had no abnormal findings on routinephysical examination, were normotensive andhad a normal ECG (Philips Medical Systems,Andover, MA, USA) and echocardiogram. Theywere not receiving any cardio-active medications.Thirty-four age- and gender-matched patientswith mild HT were also identified from a depart-mental database and recruited as a comparatorgroup. These subjects had systolic pressure >140but <160 mmHg and diastolic pressure >90 but<100 mmHg. Blood pressure recordings wereperformed at 3 separate times and all previouslydocumented blood pressure measurements were<160/100 mmHg. All the patients were on anti-hypertensive medication. The HT group had noother associated cardiac risk factor, in particular,diabetes mellitus and had no previous history ofcardiovascular, peripheral vascular or cerebrovas-cular disease.

Echocardiography:Commercially available ultrasound machines(Vivid 7 and Vivid E9, General Electric Healthcare,Horten, Norway) equipped with a 2.5 MHzvariable frequency transducer was used for echo-cardiographic evaluation. 2D and color Dopplerimages were obtained from standard echocardio-graphic views, including parasternal and apicalviews with subjects in the left lateral decubitusposition. Zoomed views of the LA were obtainedin four- and two-chamber views and an averageof 3 cardiac cycles was stored. TDI of the LA wasperformed and images were acquired at highframe rates (~110 fps) and stored digitally foroffline strain analysis.

Left Ventricular Measurements:Left ventricular end-systolic (LVESV) and end-dia-stolic volumes (LVEDV) were measured by Simp-son’s biplane method from the apical four- andtwo-chamber views and the LV ejection fractionwas calculated. LV wall thickness, LV end-diastolic(LVEDD) and end-systolic (LVESD) diameterswere measured using M mode from the paraster-nal long-axis view and LV mass index (LVMI) wascalculated using the LV end-diastolic diameter,interventricular septal and posterior wall thick-ness as per ASE criteria.22

Transmitral flow velocities were obtained byplacing a pulsed-Doppler sample volume at themitral leaflet tips in the apical four-chamber view.Peak velocity in early (E-wave) and late diastole(A-wave) and the E-wave deceleration time (DT)were measured and the E/A ratio calculated.Pulsed-wave Doppler tissue imaging was used tomeasure peak velocity in early (E′) and late (A′)diastole with the sample volume placed at theseptal and lateral annulus.23 An average of the

septal and lateral E′ velocities was calculated asper ASE recommendations.24 The E/average E′ratio was calculated as an estimate of LV fillingpressure.23 LV diastolic function was classifiedusing standard echocardiographic parameters,including peak E-wave velocity, peak A-wavevelocity, the E/A ratio, and DT. Patients weredivided into groups based on diastolic functionas (1) normal (DT = 160 � 240 ms, E/A ratio =0.9 � 1.5, E′ velocity ≥ 10 cm/sec); (2) impairedrelaxation (DT > 240 ms, E/A ratio < 0.9, E′velocity < 10 cm/sec); (3) pseudonormal (DT =160 – 240 ms, E/A ratio = 0.9 � 1.5, E′ veloc-ity < 8 cm/sec) and (4) restrictive (DT < 160 ms,E/A ratio > 2.0, E′ velocity < 5 cm/sec) as perpreviously defined criteria.24

LA Measurements:Traditional Measurements: Maximal LA volumewas measured at end systole from zoomedimages of the LA in the apical four- and two-chamber views using Simpson’s biplane method;LA volume was indexed to body surface area(BSA) (LAVI). Atrial function was estimated by tra-ditional atrial parameters including peak transmi-tral A-wave velocity, A-wave velocity timeintegral (VTI) and the atrial fraction (A-wave VTI/total mitral inflow VTI). An average of 3 measure-ments was used for all parameters.

LA Strain: Left atrial GS and SR were measured aspreviously described.25 Briefly, color Dopplertissue images were obtained in both the apicalfour- and two-chamber views (septal, and lateral,inferior and anterior walls) with sector widthselected to maintain frame rates >100 fps andwere analyzed off line using commercially avail-able software (Echo PAC version 6.2, General Elec-tric Healthcare). LA GS and SR were measuredfrom 4 sites with particular emphasis to maintainan angle of interrogation of less than 30° with theatrial walls (Figs. 1 and 2). The sample volume(10 9 2 mm) was placed in the superior seg-ments of the septal, lateral, inferior, and anteriorwalls and tracked frame by frame to maintain itsposition within the LA wall. A Gaussian 60smoothing was used and the peak systolic GS andSR were measured in each segment. The SR wasmeasured in systole (S-SR), early diastole (E-SR), aswell as in late diastole (A-SR). GS and SR for finalanalysis were calculated by averaging values fromthe septal, lateral, inferior, and anterior walls.

Inter-Observer and Intra-Observer Variability:Inter- and intra-observer variability was evaluatedin 10 subjects; a single observer performedrepeat measurements at a different time pointand a second observer, blinded to the initial mea-surements, performed measurements indepen-

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dently at a later date. Investigator 1, who wasblinded to the clinical details of patients andsubjects, performed LA GS measurements.This investigator performed a second set of

measurements on a subsequent day, selectingthe best 3 cardiac cycles, blinded to the previousresults, as well as to the group that the patientand subject belonged to. A second investigator

Figure 1. Color tissue Doppler strain from the inferior basal atrial segment. The sample volume (10 9 2 mm) was manuallytracked, throughout the cardiac cycle to ensure that blood pool was not sampled. SS = systolic strain; ROI = region of interest.

Figure 2. Color tissue Doppler SR imaging of the inferior basal segment. The sample volume (10 9 2 mm) was manually trackedthroughout the cardiac cycle. The trace demonstrates phasic atrial SR in systole (S-SR) and diastole (E-SR and A-SR).S-SR = systolic strain rate; E-SR = early diastolic strain rate; A-SR = late diastolic strain rate; ROI = region of interest.

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independently selected the best 3 cardiac cyclesand performed measurements blinded to theprevious investigators measurements as well as tothe group of the patient. An average of 3 mea-surements was used for the final analysis. Test–retest variability was performed on ten subjectsby repeating their imaging later that day.

Statistical Analysis:All values are expressed as mean � SD. Datawere analyzed using SPSS (version 19.0, SPSSInc., Chicago, IL, USA). Differences among thethree groups for continuous variables were exam-ined by one-way ANOVA with post hoc Bonfer-roni analysis. Data were considered significant ifP < 0.05. Categorical variables were comparedusing a chi-square test. Univariate predictors forgroup were determined by simple logistic regres-sion. These variables were entered into a multiplelogistic regression model to determine the effectof renal dysfunction. Logistic regression analysiswas performed using SAS 9.2 (Cary, NC, USA).This analysis was performed separately for GSand SR with other covariates to eliminate theeffect of colinearity between strain and SR. Pear-son’s correlation was used to determine clinicaland echocardiographic predictors of GS andLAVI. Intra-class correlation was used to measureinter- and intra-observer variability.

Results:A total of 100 patients and control subjects com-prised the study group; 33 CKD patients with HT,33 age-matched normal controls and 34 subjectswith mild HT and normal renal function wereincluded in the final analysis. Demographic datafor the 3 groups are presented in Table I. Themean age was 64 � 11 years in the CKD groupand was similar in normal controls and the HTgroup. Twenty-one of 33 subjects in the CKD

group and 18/34 in HT group were men. MeanBSA was similar in all 3 groups. 73% of CKDpatients were on angiotensin receptor blockers(ARB) as compared to 62% in the HT group(P = 0.24) while 21% in the CKD group and 41%in the HT group were on angiotensin-convertingenzyme inhibitors (ACEI). A small percentage inboth the CKD and HT groups were on b-blockersand diuretics, but neither of them was on spiron-olactone (Table I).

LV Systolic and Diastolic Parameters:As expected LVEDV was larger in the CKD group(P = 0.03) (Table II). LV ejection fraction was inthe normal range in all 3 groups. LV massindexed to BSA LVMI was significantly higher inthe HT group (P < 0.0001). LV diastolic functionparameters including the E/A ratio (P = 0.02), E′velocity (P = 0.03), and E/E′ (P = 0.001) weresignificantly different in patients with CKD andthe HT group compared to controls, but notbetween HT and HT with CKD group (Table II).However, there was no significant difference inpeak E-wave velocity (P = 0.06) and DT(P = 0.23) among groups (Table II).

LA Volume and Function:Left atrial maximum volume was larger in theCKD group compared to controls. However,when LA volume was indexed to BSA (LAVI), itwas significantly larger in both the CKD as well asHT groups compared to controls (P = 0.02); LAVIwas similar between the CKD and HT groups.Peak A-wave velocity was significantly higher inthe CKD group compared to both controls andthe HT group (P = 0.002). A-wave VTI was similarin all 3 groups. There was moderate correlationbetween LAVI with systolic BP (r = 0.5, P = 0.01)and GS (r = �0.6, P = 0.002) and low correla-tion with LVMI (r = 0.4, P = 0.05) (Table III).

TABLE I

Demographic Parameters in CKD Group versus HT Group versus Controls

ParametersControls(n = 33)

CKD + HT(n = 33)

HT Group(n = 34) P-Value

Age (years) 65 � 11 64 � 11 64 � 11 0.85Sex (male %) 12 (37%) 21 (63%) 18 (53%) 0.08BSA (m2) 1.86 � 0.23 1.9 � 0.23 1.96 � 0.25 0.28Systolic BP (mm Hg) 124 � 13 133 � 27 136 � 19 0.07Diastolic BP (mm Hg) 75 � 9 74 � 12 80 � 10 0.06b-blocker 0 8 (24%) 2 (6%) 0.03*ACEI 0 7 (21%) 14 (41%) 0.07ARB 0 24 (73%) 21 (62%) 0.24Diuretics 0 7 (21%) 8 (24%) 0.53

ACEI = angiotensin converting enzyme inhibitor; ARB = angiotensin receptor blocker; BSA = body surface area; HT = hyperten-sive; CKD = chronic kidney disease.*P < 0.05 compared to HT group.

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Atrial Strain Measurements:Color tissue Doppler GS, derived as an average of4 segments, was significantly reduced in the CKDgroup compared to both the HT group and con-trols (P < 0.001) (Table IV). A statistically signifi-cant difference was also present between the HTgroup and controls (P = 0.001). Patients in theCKD group additionally had altered phasic LAfunction with impaired LA reservoir and conduitfunction as demonstrated by a reduction in LAS-SR (P < 0.0001) and LA E-SR (P < 0.0001)compared with both the HT group and controls.No difference was observed between the HTgroup and controls. LA A-SR, a measure of LAcontractile function, was also reduced in the CKDgroup (P < 0.0001) (Table IV). There was

moderate correlation between GS and systolic BP(r = �0.5, P = 0.01), diastolic grade (r = �0.5,P = 0.01), E′ velocity (r = 0.6, P = 0.0001), peakA-wave velocity (r = �0.5, P = 0.004), and LAVI(r = �0.6, P = 0.002) (Table III).

Effect of Renal Dysfunction on LV and LAParameters:To examine the effect of group (i.e. presence ofrenal dysfunction vs. HT) on LV and LA parame-ters that were significantly different betweengroups, we performed logistic regression analysis(Table V). LVMI, LV diastolic grade, LAVI, peakA-wave velocity, b-blocker therapy, and GS wereentered into the model. Similar analysis was per-formed using SR (S-SR, E-SR, and A-SR) instead of

TABLE II

Conventional Echocardiographic Parameters in CKD Group versus HT Group versus Controls

ParametersControls(n = 33)

CKD + HT(n = 33)

HT Group(n = 34) P-Value

LVEDD (cm) 4.8 � 0.5 4.8 � 0.5† 5.3 � 0.4* 0.001LVEDV(mL) 94 � 21 106 � 31† 90 � 25 0.034LVESV(mL) 38 � 10 42 � 13 37 � 11 0.25LVEF (%) 60 � 5 62 � 5 59 � 6 0.07Peak E-wave velocity (m/s) 0.63 � 0.1 0.7 � 0.1 0.7 � 0.2 0.06Peak A-wave velocity (m/s) 0.66 � 0.2 0.79 � 0.2*† 0.67 � 0.2 0.002E/A ratio 1.0 � 0.2 0.92 � 0.2† 1.1 � 0.3 0.02DT (ms) 226 � 50 207 � 43 221 � 50 0.23E′ velocity (cm/sec) 8 � 2 7 � 2* 7 � 2 0.03E/E′ ratio 8 � 2 10 � 3* 10 � 3* 0.001LVMI (g/m2) 93 � 30 106 � 33† 137 � 43* <0.0001LAV (mL) 43 � 9 54 � 20* 52 � 17 0.02LAVI (mL/m2) 23 � 5 28 � 9* 28 � 9* 0.02A VTI (cm) 8.7 � � 2.4 8.2 � 2.1 8.5 � � 2.4 0.69Atrial fraction (%) 41.6 � 6 38.1 � 7.6 38 � 9 0.11A′ velocity (cm/sec) 10 � 2 12 � 2 9 � 2 0.54

A velocity = late mitral inflow velocity; A′ = late diastolic mitral annular tissue Doppler velocity; BSA = body surface area;DT = deceleration time; E velocity = early mitral inflow velocity; E′ velocity = early diastolic mitral annular tissue Doppler velocity;LAV = maximum left atrial volume; LAVI = maximum left atrial volume indexed to BSA; LVEDD = left ventricular end-diastolicdiameter; LVEDV = left ventricular end-diastolic volume; LVEF = left ventricular ejection fraction; LVESV = left ventricular end-sys-tolic volume; LVMI = left ventricular mass indexed to BSA; VTI = velocity time integral; HT = hypertensive; CKD = chronic kidneydisease.*P < 0.05 compared to normal.†P < 0.05 compare to HT group.

TABLE III

Correlation between LAVI (mL/m2) and GS (%) with Clinical and Echocardiographic Parameters

E′ velocity (cm/sec) LVMI (g/m2)

Peak A-wave(cm/sec)

Sys BP(mmHg)

Diastolicgrade GS (%)

r P r P r P r P r P r P

LAVI �0.3 0.36 0.4 0.05 0.3 0.38 0.5 0.01 �0.2 0.8 �0.6 0.002GS 0.6 0.0001 �0.4 0.11 �0.5 0.004 �0.5 0.01 �0.5 0.01

E′ = early diastolic tissue Doppler velocity at mitral annulus; LVMI = left ventricular mass indexed to BSA; peak A = late diastolicmitral inflow velocity; LAVI = left atrial volume indexed to BSA; GS = global systolic strain.

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GS (both parameters were not entered into a sin-gle model due to effects of colinearity as SR is aderivative of GS). LVMI (odds ratio 0.97[0.96–0.99], P = 0.03), GS (odds ratio 0.87[0.81–0.95],P = 0.002), and SR in all phases were influencedby the presence of renal dysfunction. While GSand SR parameters were lower in the CKD group,a paradoxical finding of a lower LVMI in the CKD

as compared to the HT group was observed.Thus, despite a relatively lower LVMI in the CKDgroup compared to the HT group, significantlylower atrial GS measurements were observedsuggesting an independent effect of renal diseaseon atrial function. Similar analysis was also per-formed between the CKD and controls and dem-onstrated a similar effect of CKD on atrial GS andSR.

Observer Variability:Intra-observer variability for S-SR by inter-classcorrelation was 0.99, 0.97 for E-SR, 0.95 for A-SR,and 0.97 for GS. Inter-observer variability byinter-class correlation was 0.99 for S-SR, 0.94 forE-SR, and 0.94 for A-SR, and 0.94 for GS.

Discussion:In this study, we recruited stage 3 CKD patientswith HT (n = 33) and compared these patientsto age-matched patients with HT and normalrenal function (n = 34) and normal healthy con-trols (n = 33). We specifically used a comparatorgroup with HT alone to evaluate the effect ofconcomitant renal dysfunction, as HT indepen-dently causes LA changes.5,7 While LAVI wasincreased in both CKD and HT groups com-pared to controls, it failed to discriminatebetween the CKD and HT groups. LA GS wasreduced in both the HT and CKD groups com-pared to controls with a significant differenceamong the 3 groups implying an additive effectof renal disease on LA function. This reductionin LA function was evident before significant LAenlargement had occurred (i.e. LAVI similarbetween the CKD and HT group), suggestingthat LA functional changes may precedechanges in LA volume.

LA Function and CKD:Evaluation of global and phasic LA function usingGS and SR parameters is feasible and theseparameters have been established as a sensitive

TABLE IV

Differences in GS and SR in CKD Group versus HT Group versus Controls

ParametersControls(n = 33) CKD (n = 33) HT (n = 34) P-Value

GS (%) 54.9 � 14.5 25.7 � 9.3*† 34.5 � 6.2* 0.001S-SR (/sec) 2.4 � 0.7 1.2 � 0.3*† 2.2 � 0.6 <0.0001E-SR (/sec) 1.9 � 0.6 1.1 � 0.5*† 1.8 � 0.5 <0.0001A-SR (/sec) 3.3 � 0.6 1.7 � 0.5*† 3.1 � 0.8 <0.0001

A-SR = late diastolic strain rate; CKD = chronic kidney disease; E-SR = early diastolic strain rate; GS = global systolic strain;HT = hypertension; S-SR = systolic strain rate; CKD = chronic kidney disease.*P < 0.05 compared to normal.†P < 0.05 compared to HT group.

TABLE V

Logistic Regression Analysis: (a) HT Patients with or withoutCKD as the Dependent Variable and Echo Parameters as

Explanatory Variables. (b) HT Patients with or without CKD asthe Dependent Variable and Subindex of Global Strain (GS) as

Explanatory Variables

ParameterAdjusted Odds Ratio*,† (95%

Confidence Interval) P-Value

(a)GS (%) 0.87 (0.81–0.95) 0.002LAVI (mL/m2) 0.94 (0.91–1.05) 0.64Peak A (cm/sec) 9.15 (0.26–326) 0.22Diastolic grade 1.04 (0.29–3.74) 0.94LVMI (g/m2) 0.97 (0.96–0.99) 0.03b-Blocker 9.6(0.91–10.1) 0.06

(b)S-SR (/sec) 0.003 (0.001–0.051) <0.0001E-SR (/sec) 0.08 (0.02–0.32) 0.0004A-SR (/sec) 0.024 (0.004–0.154) <0.0001

Peak A = late mitral inflow velocity; GS = global systolicstrain; LAVI = maximum left atrial volume indexed to BSA;LVMI = left ventricular mass indexed to BSA; S-SR = systolicstrain rate; E-SR = early diastolic strain rate; A-SR = late dia-stolic strain rate; HT = hypertensive; CKD = chronic kidneydisease.*All the five predictors were simultaneously included into thelogistic regression model with CKD versus HT as the depen-dent variable, adding b-blockers as another confounder.†Subindex of global strain, S-SR E-SR and A-SR, were used sep-arately in a Logistic Regression model with HT patients with orwithout CKD as the dependent variable. Each of the aboveLogistic Regression model also included LAVI, peak A, diastolicgrade and LVMI as covariates.

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measure to assess LA function.15–17,26 A tradi-tional parameter of LA function, the peak A-wavevelocity, was increased in the CKD group andrepresents the compensatory increase in late dia-stolic filling, given the reduced early LV diastolicfilling. Altered LA compliance with a reduction inreservoir function was present, as observed byreduced GS and S-SR. Altered LV relaxation witha consequent reduction in the LA conduit func-tion is likely responsible for the reduced E–SR.Atrial contractile function also was decreased inthe CKD group. Thus, one could postulate thatperhaps atrial fibrosis consequent to RAAS activa-tion in the CKD group results in an additivereduction in LA function over that observed as aconsequence of HT alone.

Despite similar LAVI in the HT and CKDgroups, a reduction in LA GS measurements wasobserved in the CKD group. Boyd et al.,26 previ-ously demonstrated normal LAVI despite reduc-tion in strain measurements in a group of normalvolunteers. Thus, LA functional changes may pre-cede overt LA enlargement even in diseasedstates.

Mechanisms for Altered Atrial Function inCKD:There are multiple mechanisms by which CKDcan potentially alter LA properties. HT per seincreases LVMI with a consequent increase in dia-stolic dysfunction and resultant enlargement ofthe LA with associated dysfunction. The develop-ment of HT and fluid overload in CKD addition-ally results in the activation of the intra-renalRAAS that in turn activates inflammatory fac-tors.27 Cardiac fibroblast proliferation is regu-lated by angiotensin II,28 through theangiotensin II type 1 receptor, which in turn pro-motes TGF-b1 synthesis.29 TGF-b1 stimulatesfibrous tissue formation and this effect has previ-ously been demonstrated within the atrium.30

Kokubu et al.18 used atrial S-SR to assess LAfunction in HT patients; they demonstrated thatS-SR was reduced in HT subjects even prior to thedevelopment of LA enlargement. However, whenRAAS inhibitors (ACEI/angiotensin receptorblocker) were used to treat HT, subjects with anon-dilated LA demonstrated an improvement inLA S-SR with values posttherapy being similar tonormotensive controls. They therefore postulatedthat RAAS activation in HT subjects is responsiblefor atrial dysfunction consequent to atrial fibrosis.The presence of CKD with concomitant HT willlikely enhance this RAAS activation. From litera-ture pertaining to clinical trials, there is evidenceof benefit from RAAS blockade on the progres-sion of CKD.10 Although not demonstrated inthis study, it is likely that RAAS pathway inhibitioncould reduce atrial fibrosis with the potential for

improvement in atrial function as demonstratedby Kokubu et al.

LA Volume in CKD:Tripepi et al.5,31 reported LA enlargement inde-pendent of LVMI and diastolic dysfunction inESRD. They further demonstrated that in ESRD,LAVI was an independent predictor of futureadverse cardiovascular outcomes. Similar dataregarding LA size in patients with CKD are lack-ing. We found that LAVI was significantlyincreased in the CKD group compared to age-matched normal controls, but was similar to HTpatients with normal renal function. Hence LAVIcould not discriminate between the effects of HTalone and HT associated with renal dysfunctionin CKD.

However, a significant reduction in GS and SR(S-SR, E-SR, and A-SR) was observed in the CKDgroup compared to the HT group with normalrenal function; despite a similar degree of LAenlargement. Future studies incorporating bothLAVI and LA function are needed to evaluate itsrole as a predictor of adverse cardiovascularevents.

Study Limitations:The sample size of the study is modest and thesefindings need to be validated in a larger popula-tion; however, significant differences wereobserved among the 3 groups. We have postu-lated that the decreased GS and SR are due to LAfibrosis, secondary to RAAS activation as a conse-quence of CKD and HT. We were unable to cor-roborate this with tissue histology demonstratingincreased atrial fibrosis in CKD patients, whichwas beyond the scope of this study. There issome variability in GS measurements; however,our results are similar to those reported previ-ously and reflect an intrinsic limitation of thetechnique. Longitudinal follow-up is required todetermine the clinical implication of this finding(i.e. Does reduced LA GS in CKD patients predis-pose development of atrial fibrillation?) andfuture studies aim to examine clinical outcomesin this high risk group.

Conclusion:Cardiovascular involvement is a common causeof morbidity and mortality in CKD. LA involve-ment with an increase in atrial fibrillation occur-rence is well documented in ESRD. We havedemonstrated changes in LA size and function inpatients with stage 3 CKD and HT and have dem-onstrated an additive effect of CKD on LA func-tion. Even though we have not directlydemonstrated the association between RAAS acti-vation and LA GS, reduction in GS and SR is likely

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due to atrial fibrosis that in turn is mediated viaRAAS activation. GS and SR were reduced beforeLA enlargement occurred and could be used todetect atrial dysfunction in CKD. Future longitu-dinal studies are required for evaluating theeffects of RAAS inhibitor therapy on LA GS and SRand to evaluate its utility as a prognostic markerof adverse cardiovascular events.

Acknowledgments: Krishna K. Kadappu is currently receivingNational Health and Medical Research Council (NHMRC)scholarship.

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8. Kadappu KK, Boyd A, Eshoo S, et al: Changes in leftatrial volume in diabetes mellitus: More than diastolicdysfunction? Eur Heart J Cardiovasc Imaging2012;13:1016–1023.

9. Ehrlich JR, Hohnloser SH, Nattel S: Role of angiotensinsystem and effects of its inhibition in atrial fibrillation:Clinical and experimental evidence. Eur Heart J 2006;27:512–518.

10. Siragy HM, Carey RM: Role of the intrarenal renin-angio-tensin-aldosterone system in chronic kidney disease. AmJ Nephrol 2010;31:541–550.

11. Blume GG, McLeod CJ, Barnes ME, et al: Left atrial func-tion: Physiology, assessment, and clinical implications.Eur J Echocardiogr 2011;12:421–430.

12. Fontana A, Zambon A, Cesana F, et al: Tissue Doppler, tri-plane echocardiography, and speckle tracking echocardiog-raphy: Different ways of measuring longitudinal myocardialvelocity and deformation parameters. A comparative clinicalstudy. Echocardiography 2012;29:428–437.

13. Pavlopoulos H, Nihoyannopoulos P: Strain and strain ratedeformation parameters: From tissue Doppler to 2Dspeckle tracking. Int J Cardiovasc Imaging 2008;24:479–491.

14. Mor-Avi V, Lang RM, Badano LP, et al: Current and evolv-ing echocardiographic techniques for the quantitativeevaluation of cardiac mechanics: aSE/EAE consensusstatement on methodology and indications endorsed bythe Japanese Society of Echocardiography. J Am Soc Echo-cardiogr 2011;24:277–313.

15. Abd El Rahman MY, Hui W, Timme J, et al: Analysis ofatrial and ventricular performance by tissue Dopplerimaging in patients with atrial septal defects before andafter surgical and catheter closure. Echocardiography2005;22:579–585.

16. Di Salvo G, Caso P, Lo Piccolo R, et al: Atrial myocardialdeformation properties predict maintenance of sinusrhythm after external cardioversion of recent-onset loneatrial fibrillation: A color Doppler myocardial imagingand transthoracic and transesophageal echocardio-graphic study. Circulation 2005;112:387–395.

17. Inaba Y, Yuda S, Kobayashi N, et al: Strain rate imagingfor noninvasive functional quantification of the leftatrium: Comparative studies in controls and patients withatrial fibrillation. J Am Soc Echocardiogr 2005;18:729–736.

18. Kokubu N, Yuda S, Tsuchihashi K, et al: Noninvasiveassessment of left atrial function by strain rate imaging inpatients with hypertension: A possible beneficial effect ofrenin-angiotensin system inhibition on left atrial function.Hypertens Res 2007;30:13–21.

19. Levey AS, Eckardt KU, Tsukamoto Y, et al: Definition andclassification of chronic kidney disease: A position state-ment from Kidney Disease: improving Global Outcomes(KDIGO). Kidney Int 2005;67:2089–2100.

20. Sarnak MJ, Levey AS, Schoolwerth AC, et al: Kidney dis-ease as a risk factor for development of cardiovasculardisease: A statement from the American Heart Associa-tion Councils on Kidney in Cardiovascular Disease, HighBlood Pressure Research, Clinical Cardiology, and Epide-miology and Prevention. Circulation 2003;108:2154–2169.

21. Levin A, Singer J, Thompson CR, et al: Prevalent left ven-tricular hypertrophy in the predialysis population: Identi-fying opportunities for intervention. Am J Kidney Dis1996;27:347–354.

22. Foppa M, Duncan BB, Rohde LE: Echocardiography-based left ventricular mass estimation. How should wedefine hypertrophy? Cardiovasc Ultrasound 2005;3:17.

23. Ommen SR, Nishimura RA, Appleton CP, et al: Clinicalutility of Doppler echocardiography and tissue Dopplerimaging in the estimation of left ventricular filling pres-sures: A comparative simultaneous Doppler-catheteriza-tion study. Circulation 2000;102:1788–1794.

24. Nagueh SF, Appleton CP, Gillebert TC, et al: Recommen-dations for the evaluation of left ventricular diastolic func-tion by echocardiography. J Am Soc Echocardiogr 2009;22:107–133.

25. Eshoo S, Boyd AC, Ross DL, et al: Strain rate evaluation ofphasic atrial function in hypertension. Heart 2009;95:1184–1191.

26. Boyd AC, Richards DA, Marwick T, et al: Atrial strain rateis a sensitive measure of alterations in atrial phasic func-tion in healthy ageing. Heart 2011;97:1513–1519.

27. Hohnloser SH, Connolly SJ: Atrial fibrillation, moderatechronic kidney disease, and stroke prevention: New anti-coagulants, new hope. Eur Heart J 2011;32:2347–2349.

28. McEwan PE, Gray GA, Sherry L, et al: Differential effectsof angiotensin II on cardiac cell proliferation and intra-myocardial perivascular fibrosis in vivo. Circulation 1998;98:2765–2773.

29. Dostal DE: Regulation of cardiac collagen: Angiotensinand cross-talk with local growth factors. Hypertension2001;37:841–844.

30. Verheule S, Sato T, Everett Tt, et al: Increased vulnerabil-ity to atrial fibrillation in transgenic mice with selectiveatrial fibrosis caused by overexpression of TGF-beta1. CircRes 2004;94:1458–1465.

31. Tripepi G, Benedetto FA, Mallamaci F, et al: Left atrial vol-ume monitoring and cardiovascular risk in patients withend-stage renal disease: A prospective cohort study. J AmSoc Nephrol 2007;18:1316–1322.

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Chapter 5: Independent Echocardiographic Markers of Cardiovascular Involvement in Chronic Kidney Disease: The Value of

Left Atrial Function and Volume.

Publication 3

Kadappu KK, Abhayaratna K, Boyd A, French J, Xuan W, Abhayaratna W, Thomas L. Independent Echocardiographic Markers of Cardiovascular Involvement in

Chronic Kidney Disease: The Value of Left Atrial Function and Volume. Am Soc Echocardiogr. 2016 April; 29(4) 359-367.

Declaration



98

CARDIAC INVOLVEMENT IN
CHRONIC KIDNEY DISEASE
From the Sou

Sydney, Austr

Hospital, Live

Campbelltown

Western Syd

Health Servic

Sydney, Aust

Research, Liv

Independent Echocardiographic Markers ofCardiovascular Involvement in Chronic Kidney

Disease: The Value of Left Atrial Function and Volume

Krishna K. Kadappu, MD, Katrina Abhayaratna, BSc, Anita Boyd, PhD, John K. French, PhD,Wei Xuan, MAppStat, PhD, Walter Abhayaratna, PhD, and Liza Thomas, PhD, Sydney, Liverpool,

Campbelltown, and Canberra, Australia

Background: Chronic kidney disease (CKD) is associated with increased cardiovascular mortality andmorbidity, particularly ischemic heart disease and cardiomyopathy. Newer echocardiographic techniquessuch as myocardial strain analysis provides the opportunity to detect early myocardial dysfunction. The aimof this study was to examine echocardiographic parameters, in particular left atrial (LA) function and volume,in patients with CKD. A further aimwas to determine echocardiographic parameters that are sensitive to detectcardiovascular involvement in early CKD.

Methods: Seventy-six patients with stage 3 CKD (estimated glomerular filtration rate, 30–59 mL/min/1.73 m2)with hypertension and/or diabetes mellitus, without any previous cardiac illness, were prospectively recruited.These patients were compared with subjects matched for age, sex, and risk factors (hypertension and/or dia-betes mellitus) with normal renal function and 76 healthy age-matched control subjects. Two-dimensionalstrain analyses of the left atrium and left ventricle were performed. Comprehensive echocardiographic exam-inations were performed in all participants, and traditional echocardiographic parameters including indexedLA volume (LAVI) and two-dimensional strain analysis of the left ventricle and left atrium were performed inall participants. Differences among the three groups on demographic, clinical, and echocardiographic param-eters were examined.

Results: LA systolic strain (20.96 6.3% vs 27.46 7.9%, P < .0001) and systolic and late diastolic strain rateswere altered in the CKD group, while early diastolic strain rate was similar to that in the risk factor–matchedgroup. LAVIwas significantly larger in theCKDgroupcomparedwith the risk factor–matched groupandhealthycontrol subjects (38.56 10 vs 31.26 9 vs 22.36 5mL/m2, P < .0001). LV strain as well as LV systolic and earlydiastolic strain rateswere similar in theCKD and risk factor–matched groups. LV late diastolic strain rate, a sur-rogate measure of LA contractile function, was, however, reduced in the CKD group. Forward logistic regres-sion analysis showed LA global strain to be the most sensitive predictor for the presence of CKD, followed byLAVI; though LV late diastolic strain rate was reduced in the CKD group, it was not an independent predictor.Furthermore, the addition of LA strain to traditional echocardiographic parameters significantly increased thepredictive power to detect cardiovascular involvement (C statistic = 0.65 vs C statistic = 0.84, P < .0001).Increased LAVI, reduced left ventricular global strain, and the presence of CKD were independent predictorsof LA strain, while left ventricular mass index, E/e0 ratio, and the presence of CKD were predictors of LAVI.

Conclusion: LA strain and LAVI are more sensitive parameters than traditional echocardiographic parame-ters as well as left ventricular strain in patients with early CKD. LA strain and LAVI may be useful to detectmyocardial involvement in stage 3 CKD, and LA alterations may be consequent to increased activation ofthe renin-angiotensin-aldosterone pathway, causing myocardial fibrosis in CKD. (J Am Soc Echocardiogr2016;29:359-67.)

Keywords: Left atrium, Chronic kidney disease, Left atrial volume, Left atrial strain, Left ventricular strain

th Western Sydney Clinical School, University of New South Wales,

alia (K.K.K., J.K.F., W.X., L.T.); theCardiology Department, Liverpool

rpool, Australia (K.K.K., J.K.F., L.T.); the Cardiology Department,

Hospital, Campbelltown, Australia (K.K.K.); the University of

ney, Campbelltown, Australia (K.K.K.); Canberra Hospital and

e, Canberra, Australia (K.A., W.A.); the University of Sydney,

ralia (A.B., L.T.); and the Ingham Institute of Applied Medical

erpool, Australia (W.X.).

Dr Kadappu received a National Health andMedical Research Council scholarship

(GTN 1018215) to conduct this research.

Reprint requests: Liza Thomas, PhD, Liverpool Hospital, Cardiology Department,

Elizabeth Street, Liverpool, NSW 2170, Australia (E-mail: [email protected]).

0894-7317/$36.00

Copyright 2016 by the American Society of Echocardiography.

http://dx.doi.org/10.1016/j.echo.2015.11.019

359

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Delta:1_surname

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http://dx.doi.org/10.1016/j.echo.2015.11.019

Table 1 Classification of CKD

Stage Description eGFR(mL/min/1.73 m2)

1 Kidney damage with normal

or increased GFR

$90

2 Kidney damage with mildreduced GFR

60–89

3 Moderately decreased GFR 30–59

4 Severely decreased GFR 15–29

5 Kidney failure <15

GFR, Glomerular filtration rate.

Abbreviations

ACE = Angiotensin-converting enzyme

CKD = Chronic kidneydisease

CVD = Cardiovascular

disease

DM = Diabetes mellitus

DTI = Doppler tissue imaging

eGFR = Estimated glomerularfiltration rate

ESRF = End-stage renalfailure

HT = Hypertension

ICC = Intraclass correlationcoefficient

LA = Left atrial

LAVI = Left atrial volumeindexed to body surface area

LV = Left ventricular

LVEF = Left ventricularejection fraction

LVMI = Left ventricular massindexed to body surface area

RAAS = Renin-angiotensin-aldosterone system

SRa = Late diastolic strain

rate

SRe = Early diastolic strain

rate

SRs = Systolic strain rate

2D = Two-dimensional

360 Kadappu et al Journal of the American Society of EchocardiographyApril 2016

Chronic kidney disease (CKD),an important emerging globalhealth issue, is associated withincreased cardiovascular mortal-ity and morbidity,1 particularlyrelated to ischemic heart diseaseand cardiomyopathy.2

Cardiovascular risk in patientswith CKD is multifactorial. BothCKD and cardiovascular disease(CVD) share the common tradi-tional risk factors, such as diabetesmellitus (DM) and hypertension(HT). Importantly, traditional riskfactors, such the Framinghamrisk score, often underestimatecardiovascular risk in patientswith CKD.3 Underestimation oftrue cardiovascular risk in patientswith CKD can be explained bynontraditional risk factors; struc-tural and biochemical abnormal-ities occur more commonly inpatients with CKD and increasethe risk for CVD.

We used themodifiedNationalKidney Foundation classificationof CKD, based on estimatedglomerular filtration rate (eGFR)4,5

(Table 1). All stages of kidney dis-ease have a high risk for thedevelopment of adverse CVD1;however, >11% risk for adversecardiovascular has been reportedin stage 3 CKD.1

Conventional echocardiogra-phy evaluates cardiac structureand function and remains a com-mon examination performed inalmost all patients with CKD.However, conventional echocar-

diographic parameters have limited sensitivity, with changes evidentonly once overt cardiac involvement has occurred. It is well docu-mented that left ventricular (LV) hypertrophy and coronary artery dis-ease are common in patients with end-stage renal disease.6 LV strainwas also shown to be reduced in patients with CKD, mainly in end-stage renal failure (ESRF).7,8 Tripepi et al.9 demonstrated that changesin left atrial (LA) volume predict cardiovascular events in dialysis pa-tients, independent of baseline LAvolume or LVmass. They concludedmonitoring LA size is useful for monitoring cardiovascular risk in pa-tients with ESRF. However, there are limited data regarding LA func-tion assessed by strain parameters and LA volume in early CKD.

Activation of the renin-angiotensin-aldosterone system (RAAS) inCKD caused myocardial fibrosis in an animal model.10 Saito et al.11

demonstrated that myocardial fibrosis can be detected by two-dimensional (2D) strain. Given that the atrium has thinner wallsthan the ventricle, it is possible that alterations in myocardial deforma-tion may be detected earlier in the atrium using strain analysis.

Two-dimensional strain is an angle-independent, semiautomatedtechnique that evaluates LA function.12 The aim of our study wasto investigate the value of LA volume and 2D strain analysis in the

detection of myocardial involvement in early CKD in patients withcoexistent DM and/or HT. We hypothesized that atrial dysfunctionin patients with CKD can be detected at an early stage and thatCKDmay result inmyocardial dysfunction, independent and additiveto the effects of coexistent DM and HT.We also hypothesized that LAstrain analysis may be more sensitive than LA volume indexed tobody surface area (LAVI) or LV strain parameters in patients withCKD to detect myocardial involvement.

METHODS

Seventy-six patients with stage 3 CKD (eGFR, 30–59 mL/min/1.73 m2 by the Modification of Diet in Renal Disease formula) withHT or DM (or both) and without any previous cardiac illness wereprospectively recruited and compared with subjects matched forage, sex, and risk factors (HTand/or DM) with normal renal functionand 76 healthy age-matched control subjects.

Study Population

The final study group comprised 228 subjects. Patients with CKDwith HT and/or DM (n = 76) were recruited prospectively fromthe renal outpatient clinic at Liverpool Hospital (Sydney,Australia). CKD staging was done according to standard criteria4,5;the etiology for CKD was HT (n = 29), diabetic nephropathy(n = 31), drug related, renal calculus, chronic inflammatorynephropathy, glomerulonephropathy, ischemic nephropathy, chronicgranulomatous nephropathy, and single kidney (n = 2 for each) andhepatitis and polycystic kidney disease (n = 1 each). We selectedpatients with stage 3 CKD because patients with eGFRs < 60 mL/min/1.73 m2 have previously been shown to have an increasedprevalence of CVD.1,13 Two patients with CKD were excludedfrom the final analysis because they had positive results on stresselectrocardiography for exercise-induced ischemia, and 74 patientswere used in the final analysis.All patients with CKD were screened for coexistent HT and/or

DM. None of these patients had previous cardiovascular, peripheralvascular, or cerebrovascular disease. All study subjects were in sinusrhythm, and none had any histories of atrial fibrillation. The patientswith CKD were regularly followed by their renal physicians andwere optimally treated for their blood pressure and DM. All patientswith HTwere on one or more antihypertensive medications, with sys-tolic pressure < 140 mm Hg and diastolic pressure < 90 mm Hg. Alldiabetic patients were either on oral hypoglycemic agents and/or in-sulin, and their glycated hemoglobin levels were <7%. All patientswith CKD underwent baseline transthoracic echocardiography to

Journal of the American Society of EchocardiographyVolume 29 Number 4

Kadappu et al 361

assess LV function, LV mass, and valvular abnormalities in addition tostress echocardiography to rule out latent ischemia.Because patients with CKD commonly have a high prevalence

of HTand/or DM, a risk factor–matched control group was identifiedfrom a clinical database at Canberra Hospital. These patients weresubjects with HT and/or DM with normal renal function, who werealso age and gender matched to the CKD group. These patientswere on antihypertensive agents and oral hypoglycemic agents or in-sulin. None of these patients had histories of CVD, including specif-ically atrial arrhythmias or ischemic heart disease. These subjectswere treated for their HT and DM by their treating physicians, andrecruitment into this study did not alter their management.The healthy control subjects were selected from a population-based

cohort study, who were carefully screened for histories of cardiovas-cular, peripheral vascular, or cerebrovascular disease and for the pres-ence of cardiovascular risk factors including HT and DM. They werenormotensive and had normal results on electrocardiography andechocardiography, and they were not receiving any cardioactive med-ications. Using a computer-based program, suitable subjects from thedatabase were randomly selected to match the CKD study group.This studywas approved byHumanResearch and EthicsCommittee

South Western Area Health Service (HREC/09/LPOOL/53). All par-ticipants provided written informed consent.

Echocardiography

Comprehensive transthoracic echocardiographic examinationswere performed using a Vivid 9 (GE Healthcare, Little Chalfont,United Kingdom) system with subjects in the left lateral position.Images obtained included 2D, color, pulsed- and continuous-waveDoppler, and Doppler tissue imaging (DTI) according to standardpractice.14 Zoomed left atrium and left ventricle were obtained infour- and two-chamber views at high frame rates (>70 frames/sec),and three consecutive cardiac cycles were stored. LVejection fraction(LVEF) was calculated using Simpson’s biplane method. LV mass wascalculated per American Society of Echocardiography criteria and in-dexed to body surface area (LVMI).15 Patients with greater than mildmitral or aortic valve disease were excluded. None of the patients hadmore than mild mitral annular calcification.All transthoracic echocardiograms were analyzed at Liverpool

Hospital, and all measurements were performed by two readers(K.K.K. and L.T.), blinded to patient groups. All echocardiographic ex-aminations were performed on a similar ultrasound platform (Vivid9), and similar comprehensive protocols were used. Similar echocar-diographic exclusion criteria were applied to all three groups.

Traditional Measurements

Pulsed Doppler transmitral flowwas obtained with the sample vol-ume placed at the mitral leaflet tips in the apical four-chamber view.Peak E and A velocity and the E-wave deceleration time weremeasured, and the E/A ratio was calculated.16 DTI velocities s0 (sys-tolic), e0 (early diastole), and a0 (late diastole) were measured withthe sample volume placed at the septal and lateral mitral annulus,and averages were calculated.17 Patients were classified intodifferent groups on the basis of diastolic function using standardechocardiographic parameters, including peak E velocity, peak e0 ve-locity, the E/A ratio, and deceleration time. Patients were dividedinto four groups on the basis of diastolic function, (1) normal, (2)impaired relaxation, (3) pseudonormal, and (4) restrictive, per stan-dard criteria.18

Apical four- and two-chamber zoomed LA images were used tomeasure maximum LA volume using Simpson’s biplane method atend-systole. LA volume was indexed to body surface area (LAVI).Averages of three measurements were used for all parameters.

Two-Dimensional Speckle-Tracking LA and LV StrainImaging

Two-dimensional LA strain analysis was performed using custom-ized computer software (EchoPAC; GE Vingmed Ultrasound AS,Horten, Norway) from four- and two-chamber LA images acquiredat high frame rates (>70 frames/sec), as reported previously.19 Theendocardial border was manually traced in end-systole, and the soft-ware automatically tracked the myocardial region of interest, withQRS gating as has been previously described.20,21 The width of theregion of interest was manually adjusted (by decreasing the regionof interest for the thin-walled atrium) to ensure proper tracking ofthe myocardial wall. Peak systolic strain measurement was obtained(Figure 1A). Systolic strain rate (SRs), early diastolic strain rate(SRe), and late diastolic strain rate (SRa) were measured (Figure 1B).LV myocardial strain was similarly measured from apical four- and

two-chamber images (six segments in each view), obtained at highframe rates (>70 frames/sec) (Figure 2). An average of segmentalstrain from 12 LV segments was calculated as a measure of LV strain.

Statistical Analysis

All continuous variables are expressed as mean 6 SD, while cate-gorical variables are expressed as percentages. An independent-samples t test was performed to evaluate differences between theCKD group and risk factor–matched control subjects. Differencesamong the three groups (patients with CKD, risk factor–matchedcontrol subjects, and healthy subjects) were examined using one-way analysis of variance with post hoc Bonferroni analysis.Significant univariate predictors for the effect of group (i.e., presenceof CKD) were entered into a logistic regression model to determineindependent predictors in CKD. Logistic regression analysis was per-formed using SAS version 9.2 (SAS Institute Inc, Cary, NorthCarolina) to determine the significant echocardiographic predictorsfor patients with CKD. To further compare the incremental predictivevalue of LA strain over traditional echocardiographic parameters, abaseline model containing significant echocardiographic covariateswas constructed, and a logistic regression model was used to obtainthe C statistic. Analysis was performed separately for strain and strainrate with univariate correlates, to eliminate the effect of colinearity be-tween LA strain and strain rate. Inter- and intraobserver variability wasassessed using intraclass correlation coefficients (ICCs) with SPSS forWindows version 22 (SPSS, Inc, Chicago, Illinois).

RESULTS

Baseline characteristics of the three groups are presented in Table 2.Two thirds of patients (67%) in the CKD group (n = 74) and risk fac-tor–matched control group (n = 76) were men, compared with 27(36%) in the healthy control group (n = 76). The mean age of the pa-tients with CKD was 65 6 16 years, similar to the two comparatorgroups. As expected, the CKD group and risk factor–matched grouphad higher body surface areas and body mass indexes compared withhealthy control subjects, with no significant difference between theCKD and risk factor–matched control groups (Table 2). The risk

Figure 1 (A) LA global 2D strain. (B) LA 2D strain rate including sytolic SRs and diastolic SRe and SRa measurements.

Figure 2 LV global strain. LVGLS, Peak systolic LV global longitudinal strain.


factor–matched control group had higher blood pressure comparedwith both the CKD and normal groups. More patients in theCKD group were on b–blockers (18 vs 11, P = .002) as well asangiotensin-converting enzyme (ACE) inhibitors (25 vs 17,P = .007) compared with the risk factor–matched group. Six patientswith CKD were on spironolactone; however, none in the risk factor–matched control group were on spironolactone.

Traditional Echocardiographic Parameters

LVEFs were normal in all three groups; LVMI was 97 6 32 g/m2 inthe CKD group, 1046 31 g/m2 in the risk factor–matched control

group, and 85 6 28 g/m2 in healthy control subjects, which wasalso within the normal range (43–95 g/m2 in women and 49–115 g/m2 in men). Even though LVMI was similar between patientswith CKD and risk factor–matched control subjects, LVMI washigher than in healthy control subjects (Table 2). Only four subjectsin CKD group had normal diastolic function; 35 had impairedrelaxation, 33 had pseudonormal relaxation, and two had restric-tive patterns. In contrast, 18% of patients in the risk factor–matchedcontrol group had normal diastolic function, 45% had impairedrelaxation, 37% had pseudonormal relaxation, and none had arestrictive pattern. The healthy control subjects had either normaldiastolic function or impaired relaxation patterns. DTI s0 velocity

Table 2 Clinical and traditional echocardiographic characteristics of the study population

Parameter CKD group Risk factor–matched group Healthy control subjects P

Age (y) 65.5 6 16 65.3 6 10 61.7 6 8 .08

Men 48 (65%) 50 (65%) 26 (34%) <.001*

Systemic HT 69 (93%) 70 (92%) 0 .59

DM 35 (47%) 36 (47%) 0 .98

Body surface area (m2) 1.94 6 0.24 1.97 6 0.24 1.82 6 0.22 <.0001*

Body mass index (kg/m2) 29.9 6 6.7 30.1 6 5.3 26 6 4.5 <.0001*

Systolic blood pressure (mm Hg) 127 6 18 150 6 18 123 6 12 <.0001†

Diastolic blood pressure (mm Hg) 72 6 8 85 6 9 75 6 9 <.0001†

Peak A (m/sec) 0.78 6 0.17 0.75 6 0.2 .68 6 0.17 .003*

A VTI (cm) 8.8 6 2.3 8.9 6 2.3 9.3 6 2.9 .5

LVEF (%) 65.8 6 6.5 65.8 6 6.5 60 6 5 <.0001*

LVMI (g/m2) 97.1 6 31.7 104.7 6 30.9 85.1 6 27.6 <.0001*

LAVI (mL/m2) 38.5 6 10.3 31.2 6 8.6 22.3 6 4.5 <.0001*†

s0 (cm/sec) 7 6 1.5 7.3 6 1.8 7.5 6 1.5 .16

e0 (cm/sec) 6.3 6 1.6 6.9 6 2.6 8 6 2 <.0001*

a0 (cm/sec) 9.4 6 2.1 9.5 6 2 10.3 6 1.9 .009*

E/e0 12 6 3.8 11.1 6 4.9 8.9 6 2.5 <.0001*

E/A ratio 0.94 6 0.24 0.99 6 0.39 1.03 6 0.24 .19

VTI, Velocity-time integral.Data are expressed as mean 6 SD or as number (percentage).

*P < .05 versus healthy control subjects.†P < .05 versus risk factor–matched group.

Table 3 LA strain parameters

LA strain

parameter CKD group

Risk

factor–matched

group

Healthy

control

subjects P

LA GS (%) 20.9 6 6.3 27.4 6 7.9 36.8 6 9 <.0001*†

LA SRs (sec�1) 1.1 6 0.3 1.2 6 0.3 1.9 6 0.5 <.0001*†

LA SRe (sec�1) 1 6 0.3 1.1 6 0.4 1.6 6 0.5 <.0001*


Kadappu et al 363

was similar in the three groups, but both early (e0) and late (a0) dia-stolic velocities on DTI were significantly different between healthycontrol subjects and patients with CKD and risk factor–matchedcontrol subjects. E/e0 ratios were higher in the CKD group thanthat observed in risk factor–matched control or healthy controlsubjects (Table 2). However, none of these parameters could differ-entiate patients with CKD from the risk factor–matched controlsubjects.

LA SRa (sec�1) 1.5 6 0.4 1.8 6 0.6 2.3 6 0.8 <.0001*†

GS, Global strain.Data are expressed as mean 6 SD.

*P < .05 versus healthy control subjects.†P < .05 versus risk factor–matched group.

LA Parameters

LA strain, SRs (reservoir function), and SRa (contractile function) werereduced in the CKD group (Tables 3 and 4), while LA conduitfunction (as measured by SRe) was similar to that in the comparatorgroup. LAVI was significantly larger in the CKD group, comparedwith both risk factor–matched and healthy control subjects. Weused current reported values of increased LAVI14 (>34 mL/m2) andthe lower limit for LA strain (<34%) reported in the literature.22,23

When applying these normal cutoffs to the CKD group, 29 patients(38%) with CKD had normal LA volumes (<34 mL/m2),14 whereasonly two patients (3%) had normal LA global strain of >34%.23

We further analyzed LV longitudinal strain, SRs, SRe, and SRa inthe CKD and risk factor matched control groups (Table 4). LV sys-tolic strain as well as LV SRs and SRe were similar between patientswith CKD and risk factor–matched control subjects, demon-strating that LV contractile function as well as early diastolic relax-ation were altered by the presence of DM and/or HT but thatcoexistent renal dysfunction did not additionally alter LV strain.Only LV SRa, a surrogate measure of LA contractile function,was reduced in the CKD group compared with the risk factor–matched control group (Table 4).

Logistic Regression Analysis

Forward logistic regression analysis was performed to determine in-dependent predictors of CKD. LA global strain, LAVI, LVMI, dia-stolic grade, E/e0 ratio, LV strain, and age were used as covariatesafter adjusting for medications including b-blockers and ACE inhib-itors. We also substituted LV SRa instead of LV strain in the samemodel, but this was not shown to be an independent predictor ofCKD. LA global strain (P < .0001) was the first predictor in thismodel, indicating that it is the most sensitive echocardiographicparameter in CKD, followed by LAVI (P = .005). We also performedlogistic regression model to evaluate the incremental value of LAstrain over the traditional echocardiographic parameters, includingdiastolic grade, LVMI, and E/e0, as the baseline model. The indepen-dent and incremental value of LA strain, LAVI, and LV SRa overbaseline was assessed individually as well as in an incrementalmodel. LA strain had significant predictive value when added to

Table 4 LA and LV strain parameters between CKD and riskfactor–matched control groups

Strain parameter CKD group Risk factor–matched group P

LA GS (%) 20.9 6 6.3 27.4 6 7.9 <.0001*

LA SRs (sec�1) 1.1 6 0.3 1.2 6 0.3 .03*

LA SRe (sec�1) 1 6 0.3 1.1 6 0.4 .54

LA SRa (sec�1) 1.5 6 0.4 1.8 6 0.6 .01*

LV GS (%) 15.6 6 3.7 16.8 6 3.6 .05

LV SRs (sec�1) 0.84 6 0.2 0.84 6 0.2 .92

LV SRe (sec�1) 0.81 6 0.3 0.9 6 0.3 .09

LV SRa (sec�1) 0.82 6 0.3 0.95 6 0.3 .006*

Data are expressed as mean 6 SD.

*P < .05 versus risk factor–matched group.


traditional echocardiographic parameters, as did LAVI. However, LVSRa had no additional benefit to predict cardiovascular involvementin CKD (Figure 3). We also performed analysis to determine inde-pendent determinants of LA strain and LAVI. Presence of CKD,LAVI, LVMI, diastolic grade, E/e0 ratio, LV strain, and b-blocker ther-apy, along with age, were used as covariates in the model for LAstrain. Increased LAVI and reduced LV global strain were predictorsof reduced LA strain. Importantly, presence of CKD was also an in-dependent predictor for reduced LA strain. When a similar analysiswas performed to determine independent predictors of increasedLAVI, presence of CKD along with LVMI and E/e0 ratio were shownto be predictors (Table 5).

Inter- and Intraobserver Variability

LA strain and strain rate were analyzed by two different individualsand by the same individual on a different day to evaluate inter- andintraobserver variability. Inter- and intraobserver variability wasevaluated by estimating ICCs; ICCs for LA strain were 0.97(0.92–0.99) and 0.98 (0.95–0.99), respectively. Inter and intraob-server ICCs for LA SRs were 0.95 (0.88–0.98) and 0.98 (0.96–0.99), for LA SRe were 0.96 (0.90–0.98) and 0.99 (0.98–0.99),and for LA SRa were 0.97 (0.91–0.99) and 0.99 (0.97–0.99),respectively.

DISCUSSION

We have demonstrated that patients with CKD have altered LA func-tion and LA enlargement compared with risk factor–matched controlsubjects and healthy normal subjects. Importantly, traditional param-eters of LV function as well as LV longitudinal strain, LV SRs, and LVSRe, although altered in the presence of DM and/or HT, were notfurther altered by early renal impairment. The presence of CKD,however, had a differential effect on LA function and LAVI, thusdemonstrating that monitoring LA characteristics may be importantin patients with CKD. Diastolic dysfunction is commonly present inpatients with CKD and as a consequence may additionally contributeto LA changes.

Traditional risk factors are important predictors of adverse cardio-vascular events in the general population24; however, calculation ofthe Framingham risk score underestimates cardiac events in patientswith CKD.3 Identification of a sensitive noninvasive biomarker for

cardiovascular involvement and possibly as a predictor for adverseoutcomes would be useful in patients with CKD.

We included only patients with stage 3 CKD in our study for mul-tiple reasons. A number of studies have demonstrated increased car-diovascular mortality in ESRF1,2,7,9,25,26; however, there is a paucityof data regarding LA characteristics (both function and volume) inpatients with stage 3 CKD, even though there is evidence todemonstrate that the myocardium is already involved in stage 3CKD.1 Additionally, in patients with eGFRs < 30 mL/min/1.73 m2

(stages 4 and 5), there is increased fluid overload and LV hypertro-phy,26 conditions that independently alter LA size and function.

The aim of this study was specifically to detect early and subtle car-diac involvement using newer echocardiographic parameters thatmay be more sensitive compared with traditional echocardiographicparameters. Patients with stages 4 and 5 CKD have already beenshown to have abnormalities in traditional echocardiographic param-eters,27 and hence inclusion of this group will not provide any newinformation than what has been previously reported. Moreover, noprevious studies have examined the incremental effect of CKD onLA characteristics, beyond the influence of traditional cardiovascularrisk factors such as HT and DM. Patients with CKD often have asso-ciated HT and/or DM, and as such, both may independently be riskfactors for the development of myocardial dysfunction. Thus, weconsidered patients with stage 3 CKD as a good cohort to identify car-diac involvement in early CKD.

The pathogenesis of cardiomyopathy and alteration of LA func-tion (in this instance measured by LA strain) and volume in patientswith CKD is multifactorial.9,28-30 LA volume changes may occurbecause of pressure and volume overload. Coexistent coronaryartery disease may also contribute to LA enlargement.31 Pressureoverload in CKD can be due to valvular heart disease, HT, and alter-ations in LV compliance due to LV hypertrophy (diastolic dysfunc-tion) as well as systolic dysfunction. CKD also causes fluidoverload, which in turn may lead to LA dilatation. Most patientswith CKD have associated HT and DM, both conditions againknown to cause reduced LA strain and increase in LA volume. LAcharacteristics were altered in the risk factor–matched control groupas well. However, no studies have specifically examined LA enlarge-ment and LA dysfunction in patients with early CKD. In this study,we have demonstrated that the presence of CKD has an additionalimpact on LA volume and function, over and above that of risk fac-tors such as HTand DM. Previously it was also noted that LAvolumewas independently related to LV mass, LVEF, and E/A ratio in pa-tients with ESRF.30 We hypothesized that this may be secondary toincreased activation of the RAAS, with resultant myocardial fibrosisthat in turn alters LA function and LA volume. We have not beenable to specifically measure RAAS activation in the CKD group,but we have demonstrated that LA strain is affected earlier thanLA volume in stage 3 CKD,32 which indirectly supports this hypoth-esis, as myocardial fibrosis would alter LA strain earlier than LA dila-tation, which is a more chronic process.

We specifically sought to identify echocardiographic parametersthat are sensitive to detect myocardial involvement in early CKDand that could be a discriminator for the effects of renal diseasebeyond those of associated risk factors such as HT and/or DM. Ithas been previously demonstrated that LA enlargement in CKD isa predictor of patients who progress to dialysis.33 In our study, despitenormal LVMI and LVEF, the CKD group showed impaired LA func-tion, and the presence of CKD was an independent predictor of bothLAVI and LA strain. There was a significant reduction in e0 velocity,while E/e0 was elevated in both patients with CKD and the risk

Figure 3 Incremental diagnostic value of LA strain in CKD (C statistic). LAGS, LA global strain.

Table 5 Multivariate analysis to determine independentpredictors of LAVI and LA global strain

Predictor

LAVI LA global strain

b P b P

Group �0.38 <.0001 0.28 <.0001

LVMI 0.27 <.0001 �0.03 .70

LA strain �0.08 .30 — —

LAVI — — �0.18 .01

Diastolic grade 0.01 .89 �0.05 .48

E/e0 ratio 0.17 .01 �0.09 .20

LV strain �0.09 .27 0.43 <.0001

Age 0.09 .24 �0.10 .22

b-blocker 0.02 .84 �0.06 .40


Kadappu et al 365

factor–matched group. However, there was no significant differencebetween the CKD and risk factor–matched control groups. Hence,DTI may not be useful to differentiate cardiovascular involvementin patients with CKD in the presence of HT and/or DM.

Studies have previously demonstrated that 2D LV strain is reducedin patients with CKD and ESRF7,8; Edwards et al.34 demonstrated thatsubclinical LV dysfunction is present even in early CKD that can bediagnosed by LV strain measurements. It was also demonstrated inESRF that reduction in LV strain predicts adverse cardiac events, despitenear normal standard echocardiographic measurements.35 LV strain isalso reduced in patients with HT and DM.11,36 However, in our study,LV strain, SRs, and SRe were similar in the CKD and risk factor–matched control groups. LV SRa, an indicator of LA contractilefunction, was significantly reduced in the CKD population, furtherdemonstrating differential atrial involvement in CKD.

We have demonstrated that alterations in LA strain are more sen-sitive and precede changes observed in the left ventricle in patientswith CKD. These atrial changes are likely multifactorial, including dia-stolic dysfunction, the effects of DM and HT, as well as increasedRAAS activation in patients with CKD with consequent promotionof myocardial fibrosis. It appears that these changes are detectedearlier in the left atrium than the left ventricle and could be due tothe relatively small mass of myocardium in the left atrium.

Both b-blockers and ACE inhibitors can affect LA strain and LAVI,with treatment resulting in an increase in LA strain with a reduction inLAVI. However, despite more patients in the CKD group being ontreatment with b-blockers and ACE inhibitors, patients in this groupshowed significantly decreased LA strain and increased LAVI. Thus,despite treatment, alterations in LA strain and LAVI are present andthus may be useful to detect cardiovascular involvement in CKD.Importantly, we also adjusted for the effect of medications in statisti-cal analysis, and in the presence of CKD, there was no independenteffect of treatment with b-blockers or ACE inhibitors.

Measurement of LAVI and LV strain parameters is simpler and lesstime consuming than measurement of LA strain. However, our aimwas to find the most sensitive parameter to detect involvement ofthe cardiovascular system in early CKD. Hence we determined thevarious echocardiographic parameters that are significantly alteredin early CKD. We performed forward logistic regression analysis tospecifically determine which parameter was the more sensitive mea-sure and to determine independent predictors in patients with CKD.This analysis showed that LA strain was the most significant and sen-sitive parameter to detect myocardial involvement. We also demon-strated the incremental predictive value of LA strain when added totraditional echocardiographic parameters (Figure 3). Altered LAstrain has been shown to be a predictor of adverse cardiac outcomesin varying conditions in earlier studies,21,37,38 and although this studylacks longitudinal data, extrapolation from other reports would


suggest that altered LA strain may be a predictor of adverseoutcomes in the CKD group as well. Thus, LA strain may helpclinicians to identify which patients with CKD require carefulmonitoring and aggressive medical therapy. It has been previouslyreported that reduction in LA strain parameters can be reversed, iftreated early with ACE inhibitors.39,40 Thus it is likely that LAstrain is altered early, at a stage when aggressive therapy canreverse the changes observed.

LV SRa, though significantly different between the CKD and riskfactor–matched groups, was not an independent predictor of CKD,and it did not add any additional predictive value to other echocardio-graphic parameters (Figure 3) in patients with CKD. Hence, althoughit is easier tomeasure, it is less sensitive for the detection of myocardialinvolvement in CKD.

Strengths and Limitations

In this prospective study, we could select the CKD cohort using strictinclusion and exclusion criteria. Although these results are cross-sectional, we are presently following patients longitudinally to deter-mine the value of LA strain and LAVI on adverse cardiac outcomes.We also chose the risk factor–matched group from a different hospi-tal. This was to done to widen the demography and to reduce selec-tion bias. Importantly, echocardiography was performed using similarcomprehensive protocols at both sites, with all measurements beingperformed at a single core laboratory from digital images.

We assessed diastolic dysfunction by using mitral inflow Dopplervelocity and tissue Doppler. We did not, however, measure pulmo-nary vein Doppler parameters.

Image quality is important for strain analysis, and poor image qual-ity may underestimate strain parameters. In this study, we includedonly patients in whom image quality was adequate to measure 2Dstrain. EchoPAC is not specifically designed for LA strain measure-ment, but earlier studies confirmed that it is feasible to use this soft-ware for the measurement of LA strain.22

Although we included more sensitive echocardiographic measuresto assess myocardial function, the quantification of myocardial fibrosisby magnetic resonance imaging and of RAAS activation usingbiochemical markers was beyond the scope of our study.

CONCLUSIONS

In patients with CKD, LA function (as evaluated by strain) and LAVIare altered earlier than LV parameters, including LVEF, LV strain, andLV SRa. Accordingly, LA strain and strain rate are useful parameters todetect myocardial involvement in early stages of CKD and may helpidentify patients who need monitoring and targeted medical therapy.Although we postulate that our findings may represent the effect ofincreased RAAS activity on the myocardium in patients with CKD,future studies specifically evaluating the effect of RAAS inhibitorson LA strain and strain rate are required to determine the role ofRAAS in the promotion of myocardial fibrosis in CKD.

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15. Foppa M, Duncan BB, Rohde LE. Echocardiography-based left ventricularmass estimation. How should we define hypertrophy? Cardiovasc Ultra-sound 2005;3:17.

16. Appleton CP, Jensen JL, Hatle LK, Oh JK. Doppler evaluation of left andright ventricular diastolic function: a technical guide for obtaining optimalflow velocity recordings. J Am Soc Echocardiogr 1997;10:271-92.

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32. Kadappu KK, Kuncoro AS, Hee L, Aravindan A, Spicer ST,Suryanarayanan G, et al. Chronic kidney disease is independently associ-ated with alterations in left atrial function. Echocardiography 2014;31:956-64.

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Chapter 6: Tissue Doppler Imaging in Echocardiography: Value and Limitations.

Publication 4

Kadappu KK and Thomas L. Tissue Doppler Imaging in Echocardiography: Value and Limitations.

Heart Lung Circ. 2015 Mar;24(3):224-33.

Declaration



99

Heart, Lung and Circulation (2015) 24, 224–233

1443-9506/04/$36.00

http://dx.doi.org/10.1016/j.hlc.2014.10.003

REVIEW

Tissue Doppler Imagin
g in Echocardiography: Value and Limitations
Krishna K. Kadappu, MBBS, MDa,b,c, Liza Thomas, MBBS, PhD a,b*

aSouth Western Sydney Clinical School, The University of New South Wales, University of Western Sydney, NSW, AustraliabCardiology Department, Liverpool Hospital, University of Western Sydney, NSW, AustraliacCardiology Department, Campbelltown Hospital, University of Western Sydney, NSW, Australia

Received 15 October 2014; accepted 15 October 2014; online published-ahead-of-print 28 October 2014

Tissue Doppler imaging (TDI) is a useful echocardiographic technique to evaluate global and regional

myocardial systolic as well as diastolic function. It can also be used to quantify right ventricular and left

atrial function. Recent studies have demonstrated its utility as a diagnostic as well as prognostic tool in

different cardiac conditions including coronary artery disease, heart failure (both systolic and diastolic),

valvular heart disease, cardiomyopathies as well as constrictive pericarditis. TDI measurements are also

helpful to identify patients who will benefit from cardiac resynchronisation therapy. Even though it is

reproducible and relatively easy to obtain, it is underutilised in routine clinical practice. TDI is readily

available on most commercially available echocardiographic systems, and we recommend that TDI be used

for routine clinical echocardiographic evaluation of patients.

Keywords Tissue Doppler imaging � Colour tissue Doppler imaging � Myocardial contraction velocity� Left ventricular systolic function � Left ventricular diastolic function

Tissue Doppler imaging (TDI) for echocardiographic evalua-

tion of myocardial function was first described in 1989, [1] and

has revolutionised the quantitative evaluation of myocardial

function. Doppler ultrasound relies on detection of a fre-

quency shift of ultrasound signals reflected from moving

objects. In the heart, both blood flow and myocardial contrac-

tion result in velocity changes. Blood flow causes high fre-

quency, low amplitude signals that are obtained using

traditional Doppler. Tissue Doppler imaging is designed to

characterise low velocity, high amplitude signals from myo-

cardial motion [2], and are obtained by inverting the low pass

filter used in traditional Doppler to a high pass filter.

The myocardium has subendocardial and epicardial

layers, with the former having longitudinally arranged myo-

fibres [3]. During ventricular contraction, various layers

exert varying tension with the endocardium moving greater

distances. Tissue Doppler imaging examines the longitudi-

nal component of myocardial contraction throughout the

cardiac cycle.

© 2014 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) a

Inc. All rights reserved.

*Corresponding author. Cardiology Department, Liverpool Hospital, Elizabeth Stree

Email: [email protected]

Tissue Doppler imaging is obtained using pulsed wave

tissue Doppler or colour tissue Doppler imaging (CTDI).

Pulsed wave TDI measures peak longitudinal myocardial

velocity from a single segment, but has to be performed

‘on line’. Colour tissue Doppler imaging is performed ‘off

line’, and can interrogate velocities from multiple sites simul-

taneously [4]. However, CTDI represents the mean peak

velocity, and are �25% lower than pulsed wave Doppler

[5]. The two methods are therefore not interchangeable.

The major disadvantage of TDI is its angle dependence i.e.

if the angle of incidence exceeds 15 degrees, there is �4%

underestimation of velocity [6]. Accurate TDI imaging addi-

tionally requires high frame rates (>100fps) for image acqui-

sition with excellent temporal resolution.

TDI MeasurementThe TDI signal over a cardiac cycle has three peaks, a positive

systolic peak and two negative diastolic peaks (Fig. 1A & B).

nd the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier

t, Liverpool, NSW 2170, Australia Tel.: +61 2 87383070; fax: +61 2 87383054.,

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http://dx.doi.org/10.1016/j.hlc.2014.10.003

Figure 1 (A) Pulsed wave tissue Doppler Imaging from the apical 4 chamber view sampling from the septal mitral annulus(B) Colour Tissue Doppler Imaging from the apical 4 chamber view sampling from the septal mitral annulus.

Tissue Doppler Imaging in Echocardiography 225

The positive systolic wave (s’ velocity, Sa or Sm) represents

myocardial contraction. The negative waves represent the

early diastolic myocardial relaxation (e’ velocity, Ea or Em)

and active atrial contraction in late diastole (a’ velocity, Aa or

Am) (Fig. 1 A & B). The time to peak s’ velocity can be

measured and segmental heterogeneity can be ascertained

using CTDI [7] (Fig. 2). Additionally, isovolaemic contraction

and relaxation periods can also be identified. (Fig. 3) Pulsed

wave TDI velocity measurements are obtained by placing the

sample volume at the mitral annular level (denoted Sa/s’ or

Ea/e’ or Aa/a’) or within the basal LV myocardial segment

(denoted Sm or Em or Am). Tissue Doppler imaging velocities

can be measured either from the septal or lateral annulus, but

the current recommendation is that e’ velocity is expressed as

the average of septal and lateral measurements [8]. The current

accepted nomenclature favours denoting TDI velocities as s’, e’

and a’, although the other abbreviations are also commonly

used. Normal pulsed TDI values are given in Table 1.

Normal ageing can alter TDI derived myocardial veloci-

ties. There is a decrease in s’ and e’ velocities with ageing,

Figure 3 IVCT and IVRT measurements from pulsed wave TDI trace. IVCT = isovolumetric contraction time; IVRT = iso-volumetric relaxation time.

Figure 2 Colour tissue Doppler image from the apical 4 chamber view sampling from the septal and lateral mitral annulusillustrating dyssynchronous contraction of the LV.

226 K.K. Kadappu, L. Thomas

with a corresponding increase in a’ velocity [8]. Nagueh and

colleagues have reported age-based normal cut-off values for

basal septal and lateral segments [8] (Table 2)

TDI measurements are reported in varying cardiac condi-

tions with validation as a marker of LV systolic dysfunction

[9,10], diastolic dysfunction [8,11], LV dyssynchrony [12–14],

right ventricular [15] and atrial function [16]. It is useful in the

evaluation of coronary artery disease [17] and has prognostic

implications [15,18–21]. Tissue Doppler imaging measure-

ments are more sensitive than conventional echocardiography

Table 2 Normal age related values for Doppler-derived diastolic measurements.

16-20(yrs.) 21-40 (yrs.) 41-60 (yrs.) >61(yrs.)

Septal e (cm/s) 14.9 � 2.4 15.5 � 2.7 12.2 � 2.3 10.4 � 2.1

Septal e/a ratio 2.4 1.6 � 0.5 1.1 � 0.3 0.85 � 0.2

Lateral e (cm/s) 20.6 � 3.8 19.8 � 2.9 16.1 � 2.3 12.9 � 3.5

Lateral e/a ratio 3.1 1.9 � 0.6 1.5 � 0.5 0.9 � 0.4

Modified from Nagueh, S. F., C. P. Appleton, et al. 2009. Eur J Echocardiogr 10(2): 165-193.

Table 1 Normal reference range of TDI values in healthy adults (mean � SD).

s’(cm/s) e’ (cm/s) a’ (cm/s) E/e’ e’/a’

Septal velocity 8.1 � 1.5 8.6 � 1.9 9.5 � 2.4 8.7 � 2.2 1 � 0.7

Lateral velocity 10.2 � 2.4 12.2 � 3 11.3 � 2.9 6.3 � 1.9 1.5 � 0.6

Average septal + lateral 9.2 � 1.7 10.4 � 2.2 10.4 � 2.7 7.5 � 1.9 1.3 � 0.7

Adapted from Chahal N.S, Lim T.K et al. Eur J Echocardiogr 2010, Garcia, M. J, Rodriguez L et al AHJ 1996, Pai R.G and Gill K.S JASE 1998.


for detecting early myocardial alterations in primary myocar-

dial (eg hypertrophic and dilated cardiomyopathies) and sec-

ondary myocardial disorders (eg ischaemia) [18,19,22–28].

Hence TDI is useful for screening and detection of subclinical

myocardial dysfunction, and for evaluating the efficacy of

therapeutic interventions [23,29].

Quantitative Systolic FunctionAssessment: s’ Velocitys’ velocity measures longitudinal LV contraction and is a

surrogate of LV systolic function. s’ velocity (average of four

basal segments) demonstrated good correlation with LV

ejection fraction (LVEF) [30]; s’ �7.5 cm/s had a sensitivity

of 79% and a specificity of 88% in predicting LVEF � 50%.

Similarly, s’ (average of six basal segments) > 5.4 cm/sec, had

a sensitivity of 88% and specificity of 97% for identifying

normal LVEF [31]. Endocardial longitudinal fibre contraction

is largely responsible for long axis function, which is suscep-

tible in a variety of cardiac conditions with either resultant

LV hypertrophy or dilatation. Early myocardial damage

often involves the subendocardial fibres, particularly in myo-

cardial ischaemia, with impairment in long-axis contraction

evident before changes in short-axis function. Hypertension,

coronary artery disease (CAD), cardiomyopathies and heart

failure have all been shown to alter subendocardial fibre

function with a reduction in s’ velocity [18,29], despite pre-

served LVEF. Fang and colleagues screened 101 asymptom-

atic patients with diabetes mellitus who underwent detailed

evaluation including echocardiography and exercise stress

testing, excluding those with cardiac dysfunction or ischae-

mia. Subclinical LV systolic dysfunction with a reduced s’

was noted in 24% [32]. In primary cardiomyopathic condi-

tions like hypertrophic cardiomyopathy (HCM), s’ velocity

was reduced in mutation positive individuals without LVH

[25].

Ischaemic heart disease constitutes a significant proportion

of patients reviewed in routine cardiology practice. The s’

velocity is reduced in ischaemic and infarcted segments [33].

Tissue Doppler imaging has been utilised in dobutamine

stress echocardiography (DSE), to objectively quantify

ischaemia and will be addressed in the stress echocardiogra-

phy section. [34,35]. However, TDI is limited by its inability

to differentiate active myocardial contraction from the teth-

ering effects of adjacent myocardium (i,e. TDI measures

tissue velocity in relation to the transducer rather than to

adjacent myocardium), thus lacking site specificity.[36]

Diastolic Function Assessment:e’ VelocityAging, even in healthy adults, results in altered LV diastolic

relaxation [8]. Tissue Doppler imaging e’ velocity is a mea-

sure of LV relaxation in early diastole and is relatively load

independent [37]. e’ velocity can be measured from the septal

or lateral annulus in the apical four chamber view [2,8].

However, there is regional variation, and e’ is higher in

the lateral, inferior and posterior basal segments compared

to anterior and septal segments. e’ velocity correlates

inversely with early diastolic pressure (dP/dt) or tau (time

constant of LV relaxation) [38] thereby reflecting LV relaxa-

tion and elastic recoil. In adults, a lateral e’ velocity > 12 cm/s

represents normal LV diastolic function [39] and < 8 cm/s

indicates impaired LV diastolic function[5], while a septal e’

of > 8 cm/s is considered normal [40].

In normal subjects, transmitral E velocity is higher than A

velocity; this pattern reverses in early diastolic dysfunction

(DD). However, in advanced DD, E velocity again becomes


higher than the A wave (pseudonormal pattern), making it

difficult to use mitral inflow pattern to evalute DD [41].

However, e’ velocity is reduced even in subjects with early

DD, occurring almost 10-15 years prior to reduction of mitral

E velocity [42]. Its utility is evident from its inclusion in the

EAE/ASE guidelines for assessment of diastolic dysfunc-

tion [8].

Late Diastolic a’ VelocityLate diastolic TDI a’ (a’/Aa/Am) velocity is useful in assessing

atrial function. The a’ velocity is a marker of global atrial

function [43]. a’ velocity increases with age [8], with no signif-

icant regional variation in a’ velocity (septum or lateral wall)

[44]. a’ velocity correlates with other measures of left atrial

function including transmitral peak A velocity, atrial fraction

and atrial ejection force [43,45]. Colour tissue Doppler imaging

a’ velocity permits evaluation of segmental atrial function [43].

Clinical Utility and PrognosticImplications of TDI Velocities:Systolic s’ Velocitys’ velocity has been investigated in a variety of cardiac con-

ditions, including heart failure, cardiomyopathies, valvular

as well as coronary artery disease [9,23,28,35], for both diag-

nosis as well as for long-term prognosis. It is also useful to

identify patients with cardiac dyssynchrony [7].

Wang et al. reported that s’ was lower in non-survivors at

19 month follow-up in 252 patients with cardiovascular risk

[28]. A similar increase in adverse cardiovascular events was

seen in hypertrophic cardiomyopathy patients with a low s’

velocity [23]. The prospective SPHERE (multicenter proSPec-

tive study of ecHocardiography in hypERtEnsion) study [18]

enrolled 1556 patients with LVEF � 50%; 286 (18%) had

LVDD (advanced LVDD in 128, less advanced in 158).

s’ velocity was reduced in LVDD and was an independent

predictor of advanced LVDD. Seo and colleagues evaluated

s’ velocity and its relation with dp/dt in experimental dogs

during dobutamine and esmolol infusion. s’ showed a dose-

dependent increase and decrease after dobutamine and

esmolol infusions, respectively. [46]. More recently a reduced

s’ velocity was demonstrated despite preserved LVEF, in

patients undergoing chemotherapy for breast cancer [47].

s’ velocity is useful in detecting and assessing prognosis in

CAD. Hoffmann and colleagues measured s’ from six annular

segments prior to coronary angiography [48]. Both s’ velocity

and E/e’ negatively correlated with vessels with significant

stenosis. s’ was reduced regionally and globally in patients

with three-vessel disease. In another study, 296 patients with

stable angina with normal LVEF were compared with 188

patients without significant CAD [49]; 108 had �70% stenosis

in at least one epicardial coronary artery. Average (six annular

segments) s’ remained an independent predictor of CAD

after multivariable analysis of exercise ECG and conventional

echocardiographic parameters. Tissue Doppler imaging s’ can

also diagnose early myocardial ischaemia [50]. Biering-Soren-

sen and co-workers also noted that a low s’ velocity after ST

elevation MI (STEMI) resulted in poor prognosis [51] in 391

patients treated with primary percutaneous coronary inter-

vention. Patients with low s’ at median follow up of 25 months

had >2 times risk for the composite end point of death, heart

failure, or recurrent myocardial infarction (hazard ratio, 2.60;

95% CI 1.64-4.13; P < .001).

Stress TDIStress echocardiography is an essential tool in the clinical

work-up of subjects with suspected CAD or latent ischaemia.

Wall motion scoring by visual assessment has improved

accuracy compared with stress electrocardiography, but

has high inter-observer variability [52]. Segmental TDI

velocities are reduced with ischaemia and recover with

reperfusion [53] and can differentiate transmural from non-

transmural infraction [53,54]. Yamada et al reported a smaller

increase in myocardial velocities in ischaemic segments with

dobutamine stress echocardiography (DSE); peak TDI s’

velocity of <12 cm/s had 80% accuracy for detecting ischae-

mic segments [55]. Cain et al combined TDI with wall motion

score and derived cut-off values of myocardial Doppler

velocities in 128 normal subjects [56]. s’ velocity for the septal,

anteroseptal and inferior basal segments was � 7 cm/sec and

� 5 cm/sec for the mid segments; s’ was � 6 cm/sec for basal

and � 4 cm/sec for mid segments of other walls. When

applied to 114 patients who underwent DSE and angiogra-

phy, a sensitivity of 83% and specificity of 73% was present

for detection of � 50% coronary artery stenosis, but were not

significantly different to visual assessment.

Marwick and colleagues reported prognostic value of s’

velocity; patients with a lower s’ velocity had more adverse

events (average s’ � 4.9 +/- 1.7 cm/s versus 6.4 +/- 6.5 cm/s;

p < 0.001) [35]. s’ velocity can also be used with low dose DSE

to determine viability; the percentage increase in s’ velocity

in viable segments, four weeks after revascularisation was 45

+/-10%, versus 25+/-12% in non-viable segments. [34].

Both s’ velocity [24] and isovolumic acceleration [26] reflect

regional wall motion. Isovolumic acceleration is less affected

by ventricular loading compared to myocardial velocity. In

the Myocardial Doppler in Stress Echocardiography (MYD-

ISE) study, 149 patients had DSE before coronary angiogra-

phy. Both peak s’ velocity and isovolumic acceleration, at rest

and post stress, from basal and mid segments were compared

to angiographic results. Isovolumic acceleration velocity was

a better diagnostic marker for CAD and in combination with

peak s’ had an accuracy of 85-95% to diagnose coronary

stenosis [24,26]. Hence, combining TDI with DSE, may

improve accuracy for identifying ischaemic segments, reduce

inter observer variability and determine viability.

Measurements can also be performed during exercise

echocardiography [33]. A s’ velocity of <5 cm/s at peak stress

predicted exercise induced wall motion abnormality [57]


Valvular Heart DiseaseTissue Doppler imaging has been useful in identifying sub-

clinical myocardial dysfunction in patients with valvular

heart disease. Patients with aortic stenosis have reduced

mitral annular excursion despite normal LVEF [58]. LV lon-

gitudinal shortening, age and indexed aortic valve area, were

independent predictors of symptoms in patients with aortic

stenosis [59].

A reduction in longitudinal s’ velocity has also been dem-

onstrated in asymptomatic patients with severe aortic regur-

gitation [60].

In patients with chronic mitral regurgitation, LV function

appears ‘hyperdynamic’ but there is often subclinical dys-

function with reduced s’ velocity [20]. In 169 patients who

underwent mitral valve surgery s’ was the only independent

predictor of LV reverse remodelling. Haluska et al [61] fur-

ther demonstrated that s’ velocity was lower in mitral regur-

gitation patients without contractile reserve on exercise

echocardiography.

Cardiac DyssynchronyPatients with severe systolic dysfunction have evidence of

electromechanical dyssynchrony [62], with delayed propa-

gation of electrical activity from the LV septum to the lateral

wall. Prognostic value of LV dyssynchrony, was first

reported by Bader and co-workers [63], and TDI was consid-

ered one of the most useful echocardiographic dyssynchrony

measures [7,12]. Colour tissue Doppler imaging was consid-

ered superior to pulsed TDI, as multiple segments could be

measured from the same cardiac cycle. Systolic dyssyn-

chrony is the delay in time to peak s’ velocity between the

septal and lateral walls (Fig. 2). Bax and colleagues in their

meta-analysis concluded that TDI could predict responders

to resynchronisation therapy with 87-97% sensitivity and

55-100% specificity [14]; further, a septal to lateral delay

�65 m/s, had prognostic value [7]. Systolic dyssynchrony

was further defined as the standard deviation of time to peak

s’ velocity from 12 segments; a value � 33ms, was an inde-

pendent predictor of reverse remodelling [12].

While dyssynchrony determined by TDI showed great

promise early on, more recent trials demonstrated that QRS

duration >150m/sec with a left bundle branch block pattern is

the best determinant of responders to resynchronisation ther-

apy [64]. However, the prevalence of systolic dyssynchrony is

more marked in patients with a wide QRS (51% in the narrow

QRS group versus 73% in the wide QRS group)[13].

In summary, systolic myocardial velocity (s’/Sa/Sm) mea-

sured at the mitral annulus or basal myocardial segment

correlates with LVEF and dP/dt. s’ detects subclinical myo-

cardial dysfunction in various cardiac disorders including

CAD, CHF, hypertension, diabetes and primary cardiomy-

opathies. The s’ velocity can be used in stress echocardiog-

raphy [35] for improved identification of ischaemia and

viability and also has prognostic value.

Early Diastolic (e’) VelocityAlthough s’ velocity is a good predictor of long term cardio-

vascular outcome, e’ appears superior [21]. Reduction in e’

velocity had prognostic significance in 518 subjects, who

were followed for two years. Reduction in e’ velocity and

increased left atrial dimensions were the strongest predictors

for cardiac mortality [65]. In 182 patients with LV systolic

impairment, e’ <3 cm/s emerged as the best prognostic

marker for cardiac mortality at long term follow-up [10].

Comparable results were reported in hypertensive patients

with LV hypertrophy [28]. e’ velocity was also reduced in

patients with hypertrophic cardiomyopathy who had pul-

monary oedema versus stable patients [27]. Hence e’ velocity

is a sensitive marker of LV DD and a prognostic predictor of

cardiovascular outcomes.

E/ e’ RatioMitral inflow E velocity increases with higher LV filling

pressure (LVFP) with a corresponding reduction in e’ veloc-

ity [66]. The ratio of E/e’ correlates well with LV end diastolic

pressure or pulmonary capillary wedge pressure [66]. An E/

e’ > 15 using septal e’ or E/e’ >12 using lateral e’ velocity, is a

surrogate marker of elevated LVFP. In a cohort with dilated

cardiomyopathy with similar systolic function, patients with

an elevated E/e’ were more symptomatic [21]. Additionally,

the independent predictive value of E/e’> 15 for cardiac

mortality and heart failure has been documented [16] and

subsequently confirmed by Dokainish and co-workers [67].

Hillis and colleagues examined E/e’ ratio as a prognostic

indicator after myocardial infarction in 250 unselected

patients followed for a median of 13 months. Seventy-three

patients (29%) with an E/e’ >15, had an associated increased

mortality (log-rank statistic 21.3, p < 0.0001); moreover E/e’

was the most powerful independent predictor of survival

(risk ratio 4.8, 95% CI 2.1 - 10.8, p = 0.0002) [68]. The same

group also reported that E/e’ ratio >15 was a useful predictor

of LV dilation after infarction [69].

In another study, 417 patients admitted with heart failure

were followed for a median of 306 days [70]; an increase in E/

e’ was linearly associated with increased all-cause mortality.

E/e’ ratio is also useful in detecting early LV DD in patients

with untreated early onset hypertension and hyperinsulinae-

mia [71].

Diastolic Stress TestingIn heart failure with preserved ejection fraction (HFpEF), it is

diastolic dysfunction that precipitates symptoms; HFpEF is

the cause for � 50% of all heart failure cases [72]. Symptoms

of diastolic dysfunction are often exertional, due to elevated

LVFP during exercise [73]. As discussed earlier, E/e’ ratio is a

surrogate for LVFP. E/e’ was evaluated during exercise in 45

patients presenting with exertional dyspnoea with normal


LVEF by Ha and colleagues, with supine bicycle exercise;

patients with normal resting E/e’, that increased with exer-

cise, had significantly shorter exercise duration [74]. In a

recent study of 522 patients referred for stress echocardiog-

raphy [75], the relative contributions of exercise E/e’ and

ischaemia to cardiovascular outcomes was assessed. E/e’

was obtained at rest and after exercise. Patients with a normal

exercise E/e’ and those without exercise induced ischaemia,

had better prognosis than those with ischaemia (with or

without raised exercise E/e’). Importantly cardiovascular

outcomes were similar in patients with increased exercise

E/e’ without ischaemia, to those who developed exercise

induced ischaemia. Additionally, patients with normal rest-

ing E/e’ but elevated exercise E/e’ had worse outcomes than

those with normal exercise E/e’. Thus exercise induced

elevations in E/e’ was associated with increased cardiovas-

cular hospitalisation, independent of inducible ischaemia

[75]. E/e’ correlates with exercise LVFP [76], and latent

diastolic dysfunction can be unmasked with exercise

E/e’ ratio.

e’ Velocity and CADReduction of TDI e’ occurs early in myocardial ischaemia

[50]. As mentioned earlier, Hoffmann and colleagues studied

E/e’ along with s’ in patients with CAD [48]. Similar to s’

velocity, E/e’ negatively correlated with the number of ves-

sels with significant stenosis. e’ velocity was reduced in the

segments supplied by a stenotic artery. Average e’ velocity

remained an independent predictor of CAD, after adjustment

for baseline exercise ECG and conventional echocardio-

graphic parameters [49].

Biering-Sorensen and co-workers also noted a low e’ veloc-

ity after STEMI resulted in greater risk for the composite of

death, heart failure, or a new myocardial infarction (hazard

ratio, 2.26; 95% CI 1.44-3.55; P < .001) [51].

e’ Velocity in Cardiomyopathyand Constrictive PericarditisDiastolic TDI velocities are reduced in inherited cardiomy-

opathies and could be used to detect the condition at a

preclinical stage. Reduced e’ velocity has been demonstrated

in genotype positive patients with hypertrophic cardiomy-

opathy prior to the development of LV hypertrophy [22].

Similarly, e’ velocities were reduced in Fabry patients before

they developed LVH [19], and stratified patients based on

severity in primary AL amyloidosis [77].

It is often difficult, both clinically and using traditional

echocardiography, to differentiate pericardial constriction

from restrictive cardiomyopathy; TDI is useful in differenti-

ating these two conditions. Septal e’ velocity is reduced in

restrictive cardiomyopathy whereas it was normal or ‘supra

normal’ in constrictive pericarditis (septal vs lateral e’: 12.3 vs

5.1 cm/s, p < 0.001). A septal e’ � 8 cm/s resulted in 95%

sensitivity and 96% specificity for the diagnosis of constric-

tive pericarditis [78]. Further, because of pericardial adhesion

to the lateral LV wall in constriction, the LV and RV lateral e’

velocities are not significantly different, and often reduced

when compared to septal e’ [79]. The reduction in lateral e’

velocity is termed ‘annulus reversus’ [80]. By combining

ventricular septal shift with a septal e’ �9 cm/s, 87% sensi-

tivity and 91% specificity for detection of constriction was

demonstrated [81].

a’ Velocity in Clinical PracticeThe a’ velocity represents atrial contractile function, and is

useful in evaluating atrial dysfunction. Wang and co-work-

ers, using tertiles of a’ velocity (<4, 4 to 7, and>7 cm/s)

observed that a’ <4 cm/s and a’ � 4 but <7 cm/s, had an

increased hazard ratio for cardiac death compared with a’ >

7 cm/s (HR: 11.53, 95% CI: 4.1- 32.39 and HR: 4.28, 95% CI:

1.54 - 11.9 respectively) [65]. a’ velocity was also found to be

reduced in ventricular [82] and atrial dysfunction [83].

The duration from onset of the P-wave on electrocardiogram

to peak TDI a’-velocity of the lateral left atrial wall (PA-TDI

duration) has been proposed as an independent predictor of

AF recurrence post cardioversion [84], and can also predict

maintenance of sinus rhythm. Reports on the utility of a’

velocity are limited and require validation in larger groups.

Right Ventricular FunctionEchocardiographic quantification of right ventricular (RV)

function is under-reported due to the difficulty in accurate

evaluation given its retrosternal position, making imaging

more challenging. Similar to the LV, pulsed TDI velocities of

the right ventricle demonstrate a base to apex gradient [85]

with lateral RV s’ being greater than the LV lateral s’ velocity.

Colour tissue Doppler imaging is also useful in assessing

segmental RV velocities offline [86]. In normal individuals,

RV s’ velocity is 14 � 2 cm/s [87]. Meluzin and co-workers,

reported good correlation between RV s’ velocity and RV

ejection fraction (r = 0.648, P < 0.001); RV s’ velocity <

11.5 cm/s predicted RV dysfunction (EF < 45%) with a sen-

sitivity of 90% and specificity of 85% [15]. Reduced s’ is seen

in posterior myocardial infarction, chronic pulmonary

hypertension [15] and chronic airway limitation [88]. More

recently, RV dysfunction has been reported in elite athletes

[89], while Bos and co-workers, reported a reduced RV s’

velocity in asymptomatic patients with congenitally cor-

rected transposition of the great arteries [90] and in tetralogy

of Fallot [91]. Hence TDI is a useful tool to assess early RV

dysfunction.

LimitationsAlthough TDI measurements are relatively robust, there is a

learning curve for acquisition and analysis of TDI data.


Commercially available machines may use varying algo-

rithms that may provide different TDI velocities [92]. It is

also not clear where in the spectral trace of the pulsed Dopp-

ler envelope to measure tissue velocity; a recent study rec-

ommends measurement at the mid portion of the spectral

trace [93] (Fig. 1A). Tissue Doppler imaging is angle depen-

dent and if the angle of interrogation exceeds 20 degrees, then

the velocity may be underestimated. Even though TDI sig-

nals are robust, it is not unusual to have some variation in

signal amplitude and timing by minimal alterations in posi-

tion of the sample volume. This is particularly important in

dyssynchrony studies as cursor position may alter timing.

Sometimes interpretation of pulsed TDI traces may be chal-

lenging, as there are multiple peaks.

ConclusionTissue Doppler imaging is a robust echocardiographic

technique for quantification of global and regional myocar-

dial contractile function as well as left ventricular relaxa-

tion and E/e’ is a surrogate for LVFP. Tissue Doppler

imaging measurements are powerful prognostic markers

in a variety of cardiovascular conditions. As it is relatively

easy to obtain and is reproducible, its incorporation in

routine clinical echocardiographic evaluation should be

considered.

Conflict of interestThere are no conflicts of interest.

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Chapter 7: Biomarkers of chronic kidney disease: the value of left atrial metrics

Publication 5

Krishna K. Kadappu,, Lawrence Cai, David Thomas, Wei Xuan, John K. French, Liza Thomas At press

Declaration

I certify that this publication wa~ a direct result of my research towards this PhD and that reproduction in this thesis doesn't breach copyright regulations


100

Cardiac biomarkers in Chronic Kidney Disease Biomarkers of chronic kidney disease: the value of left atrial metrics

100

Biomarkers of chronic kidney disease: the value of left atrial metrics

Krishna K. Kadappu, MD 1,2,3,4;Lawrence Cai 1,2;David Thomas, MSc 5; Wei Xuan,

MAppStat,PhD1,6; John K. French, PhD 1,2 ; Liza Thomas, PhD 1,2,7 1 South Western Sydney Clinical School, University of New South Wales, NSW, Australia 2 Cardiology Department, Liverpool Hospital, NSW, Australia. 3 Cardiology Department, Campbelltown Hospital, NSW, Australia. 4 University of Western Sydney 5Department of Biochemistry, Liverpool Hospital, NSW, Australia. 6 Ingham Institute of Applied Medical Research, NSW, Australia. 7 Westmead Hospital, University of Sydney

Institution of work: Liverpool Hospital, Liverpool, Australia

Corresponding Author: Prof. Liza Thomas, PhD Cardiology Department, Liverpool Hospital, Elizabeth Street, Liverpool, NSW 2170, Australia [email protected] Phone: + 61 2 87383797 Fax: +61 2 87383341 Conflict of interest: There are no conflicts of interest



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Abstract

Aim: We sought to identify an easily available non-invasive, biomarker to detect

cardiovascular involvement in early chronic kidney disease (CKD).

Methods: Sixty nine stage 3 CKD patients (eGFR of 30-59 ml/min/1.73m2) were

compared with 31 risk factor matched controls with normal renal function. A

comprehensive echocardiogram was performed in all participants and

echocardiographic parameters including indexed left atrial (LA) volume and LA 2-

dimensional strain analysis were performed in all participants. N terminal pro- brain

natriuretic peptide (NT-pro BNP) levels were also measured in all study participants.

Results: LA systolic strain (21.2±6.3 vs 26.9±8.9%; p = 0.002) and systolic, early and

late diastolic strain rate were significantly lower in the CKD group compared to the risk

factor matched group. However, traditional echocardiographic parameters including left

ventricular (LV) ejection fraction and indexed LV mass were similar between CKD

patients and controls, although E/e’ was significantly higher in the CKD group (12±4.8

vs 9.6±3.4; P=0.007). LA volume indexed to body surface area (LAVI) was

significantly larger in the CKD group compared to risk factor matched group (32.7 ± 8.6

vs 26.6 ± 11.7 ml/m2; p = 0.01). Though NT-pro BNP levels were relatively higher in

the CKD group (20.8±24 vs 5.9±6.2pg/ml (p=0.001)), levels were within the upper

reference limit (<100pg/ml).

Conclusion: LAVI and LA strain parameters, are sensitive biomarkers of early

cardiovascular involvement in stage 3 CKD patients that are easily available. Our

preliminary analysis demonstrated that LA parameters are more sensitive than NT-pro

BNP to detect myocardial involvement in CKD. Longitudinal studies in a larger cohort

of patients are needed to evaluate their prognostic utility.

Key words: LA strain, LA volume, NT-pro BNP, Chronic Kidney Disease


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Introduction

Patients with chronic kidney disease (CKD) are frequently asymptomatic and CKD is

often detected by the presence of proteinuria, haematuria, or reduced GFR1.

Furthermore, the prevalence of CKD is increasing in the general population due to

increased risk factors like obesity, diabetes and hypertension2. As the prevalence of

CKD increases, the risk of associated cardiovascular disease (CVD) also increases;

traditional predictive instruments like the Framingham risk score, while useful, under

estimates CVD risk in CKD patients3. Due to the large number of CKD patients in the

general population, a simple non-invasive biomarker to identify cardiovascular

involvement in CKD patients would be attractive. Identification of patients at higher

risk could prompt interventions that reduce future adverse cardiovascular events.

A number of studies have reported the utility of brain natriuretic peptide (BNP) / N

terminal pro BNP (NT-pro BNP) as a cardiovascular prognostic marker in CKD4-6. An

echocardiographic examination is routinely performed in almost all CKD patients to

assess left ventricular and valvular function as standard practice in most institutions.

Both left atrial (LA) volume7 and LA strain have been shown to be predictors of

cardiovascular mortality in end-stage renal disease8. Our group has previously

demonstrated that LA function evaluated by 2D strain analysis is reduced even in early

CKD9, as well as in diabetes 10, which often results in CKD. In view of these previous

observations, we sought to determine whether NT-pro BNP levels or evaluation of

echocardiographic LA metrics (LA volume indexed to body surface area - LAVI and

LA strain) would be the more sensitive biomarker that would identify cardiovascular

involvment in early CKD patients.


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Material and methods

Stage 3 CKD patients (with eGFR of 30-59 ml/min/1.73m2 by modified diet in renal

disease formula), without any previous cardiac illness were screened from the renal

outpatient clinic at Liverpool Hospital, Sydney, Australia. These CKD patients were

compared to subjects with similar cardiac risk factors but who had normal renal

function, admitted for evaluation of chest pain. These control subjects had no dynamic

ECG changes with below the upper reference limit of high sensitivity troponin

measurements. All patients and controls had stress echocardiogram to rule out

myocardial ischemia. Any patients with a previous history of heart failure or atrial

arrhythmia, and those with greater than mild valvular disease or significant mitral

annular calcification were excluded from this study.

This study was approved by Human Research and Ethics Committee South Western

Area Health Service (HREC/09/LPOOL/53). All participants provided written informed

consent.

Echocardiography

A comprehensive transthoracic echocardiogram was performed with subjects in the left

lateral decubitus position using a Vivid 9 (GE Healthcare) system. M mode, 2

dimensional, colour, pulsed and continuous wave Doppler and tissue Doppler imaging

were obtained according to standard practice11. An average of 3 cardiac cycles with

zoomed LA images were obtained from the apical 4 and 2 chamber views at high frame

rate (>70 fps) and was stored digitally.

Traditional measurements

Left ventricular (LV) ejection fraction (EF) was calculated using Simpson’s biplane


104

method. LV mass was calculated as per American society of echocardiographic (ASE)

criteria and indexed to BSA (LV mass index -LVMI)12. Pulsed Doppler transmitral flow

was obtained with the sample volume placed at the mitral leaflet tips in the apical 4-

chamber view. Peak E and A velocity and the E-wave deceleration time (DT) were

measured and E/A ratio were calculated13. Tissue Doppler velocities were measured

with the sample volume placed at the septal and lateral mitral annulus14. Patients were

classified into different diastolic grades as per standard criteria15. Apical 4- and 2-

chamber zoomed LA images were used to measure maximum LA volume using

Simpson’s biplane method at end-systole. LA volume was indexed to BSA. An average

of 3 measurements was used for all parameters.

2D speckle tracking LA/ LV Strain Imaging

2D LA strain analysis was performed using customized computer software (EchoPAC,

Vingmed, General Electric, Horten, Norway) from LA zoomed views from apical 4 and

2 chamber images obtained at high frame rates. The endocardial border was manually

traced in end-systole and the software automatically traces the myocardium. The width

of the region of interest (ROI) was manually adjusted by decreasing the ROI (as the

atrium is thin walled) to ensure proper tracking of the myocardial wall. Peak systolic

strain (fig.7.1); systolic (SRs), early diastolic (SRe) and late diastolic (SRa) atrial strain

rates were measured as described earlier16. Similarly LV strain and strain rate were also

measured by using the same software from zoomed LV images obtained at a high frame

rate.


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Figure7. 1. Left atrial 2D global strain

NT-pro BNP assay

Blood sample were collected from all subjects using a wide bore cannula from the anti-

cubital vein. These samples were centrifuged and the serum was stored at -800C for

batch analysis. NT-pro BNP immunoassay (Roche Mannheim, Germany) was

performed by using standard diagnostic techniques17. This NT-pro BNP assay has been

utilised to diagnose LV systolic and diastolic dysfunction18, 19. A cut off value of

>100pg/ml, for the particular kit used indicates cardiac involvement with left ventricular

dysfunction (both systolic and diastolic)20.

Statistical analysis

All continuous variables are expressed as mean ± SD, while categorical variables are


106

expressed as a percentage. An independent samples t-test analysis was performed to

evaluate differences between the CKD group and controls. NT- pro BNP was log

transformed as it is not uniformly distributed. Pearson correlation was used to assess the

correlation between variables. Significant univariate predictors for the effect of group

(i.e. presence of CKD) were entered into a logistic regression model to determine

independent predictors for CKD as well as for NT-pro BNP. Logistic regression model

was also used to select the most sensitive bio-marker to detect cardiovascular

involvement in early CKD. All statistical analysis was performed by using Statistical

Package for Social Sciences for Windows, version 22 (SPSS, Chicago, Illinois) and

SAS 9.2 (Cary, North Carolina, USA). Inter and intra observer variability was assessed

by intraclass correlation coefficient using Statistical Package for Social Sciences for

Windows, version 22 (SPSS, Chicago, Illinois).

Results

Baseline characteristics are presented in Table7.1. Seventy one CKD patients were

screened; 2 were excluded from the study as the stress echocardiogram was positive for

exercise induced ischemia. Thus a total of sixty nine CKD patients were compared to

31 controls in the final analysis. Majority of CKD patients had renal impairment due to

diabetes (n=30) and or hypertensive nephropathy (n=29). The remainder were drug-

related, due to renal calculi, chronic inflammatory nephropathy, glomerulonephropathy,

chronic granulomatous nephropathy (n=2 for each) and due to hepatitis and polycystic

kidney disease (n=1). The CKD patients were older and their mean age was 63.9 years

where as mean age was 50.6 years in the control group (p<0.001). Both patient groups

had similar body surface area (Table7.1). A total of 68 patients (55 in CKD and 13 in

controls) had hypertension and forty (34 in CKD and 6 in control) had diabetes. Though


107

NT-pro BNP levels were in the normal range, CKD patients had higher NT-pro BNP

compared to the control group (Table7.1).

Traditional echocardiographic parameters

Left ventricular ejection fraction was comparable in the two groups. LV mass indexed

to body surface area was also similar between groups. CKD patients had a higher E/e’

ratio than that observed in controls (p=0.007) (Table7.1). Two CKD patients had normal

diastolic function, 27 impaired relaxation and 40 pseudo normal filling whereas 10

patients in control had normal diastolic function, 4 impaired relaxation 17 pseudo

normal ( p=0.046).

Table7. 1. Clinical and traditional echocardiographic characteristics of the study population

Parameters CKD(69) Control(31) p-value

Age, years (SD) 63.8 (10) 50.7 (10) 0.001†

Body surface area, m2 (SD) 1.92(0.24) 1.9(0.24) 0.34

NT-pro BNP(pg/ml) 20.8(24) 5.9(6.2) 0.001†

LVEF (%) (SD) 67(6.5) 66(6.9) 0.88

LVMI gm/ m2 (SD) 90.6(28.5) 84.1(25.5) 0.25

LAVI ml/ m2 (SD) 32.7(8.6) 26.6(11.7) 0.01†

E/e’ (SD)

12(4.8) 9.6(3.4) 0.007†

HT

55 (75%) 13 (42%) 0.001†

DM

34(47%) 6 (20%) 0.01†

†p<0.05 compared to control. LAVI= maximum left atrial volume indexed to BSA, LVEF= left ventricular ejection fraction, LVMI= left ventricular mass indexed to BSA, HT= hypertension, DM= diabetes mellitus

Left atrial and ventricular strain parameters

LAVI was significantly larger in the CKD group; the mean LAVI of the CKD group


108

was in the ‘mild LA enlargement’ range as per the ASE guidelines, while the mean

values of the control group was within the normal range for LAVI. LA systolic strain,

SRs (reservoir function), SRe (LA conduit function) and SRa (contractile function)

were all reduced in the CKD group (Table7.2). LV global strain was reduced in both

groups, but not statistically difference between the groups (Table7.2). When we applied

the current accepted normal values of LAVI (<34 ml/m2)21 and LA strain (>32%)22, 30

(43.5%) patients in the CKD group had LAVI greater than 34 ml/m2 whereas 67 (97%)

patients had LA global strain < 32%.

Table7. 2. Left atrial and ventricular strain parameters

Strain parameter CKD(69) Control(31) p value

LA GS (%) 21.2±6.3 26.9±8.9 <0.002†

LA SRs (s-1) 1.2±0.3 1.4±0.4 <0.001†

LA SRe (s-1) 1±0.3 1.4±0.4 <0.0001†

LA Sra (s-1) 1.6±0.4 2.1±0.6 <0.001†

LV strain (%) 15.5 ±3.8 16.8±3.7 0.11

†p<0.05 compared to control LA GS= left atrial strain, LA SRa= Left atrial late diastolic strain rate, LA SRe = Left atrial early diastolic strain rate, LASrs= left atrial systolic strain rate, LV strain= left ventricular systolic strain.

Correlation between NT-pro BNP and LAVI

NT-pro BNP levels correlated with LAVI, and correlated inversely with LA strain and

eGFR. The correlation of NT-pro BNP with LV strain and LAEF were weaker

compared to LA volume and LA strain (Table7.3).


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Logistic regression analysis

Logistic regression analysis was performed to determine independent predictors of NT-

pro BNP. Presence of CKD, LAVI, LVMI, E/e’ ratio, LA and LV strain and age were

used as covariates in the model. The independent predictors of NT-pro BNP were

presence of CKD, LAVI, E/e’ ratio and LA global strain (Table7. 4). Logistic regression

analyses was additionally performed to determine independent predictors for the

presence of CKD; significant univariate predictors included LAVI, diastolic grade,

LVMI, E/e', LA strain, LV strain and NT-pro BNP as covariates (Table7. 5). LA strain

and NT-pro BNP were the only 2 independent predictors for the presences of CKD.

Furthermore, logistic regression model showed that LA global strain was the more

powerful parameter to determine the presence of CKD.

Table7. 3. Pearson correlation of parameters to NT-pro BNP( log transformed)

Correlation (r) p-value eGFR -0.44 <0.0001 LVMI 0.07 0.48 LA strain -0.26 0.009 LAVI 0.47 <0.0001 E/e’ 0.15 0.14 LV strain -0.16 0.09 LAEF -0.18 0.07 LVEF -0.068 0.47 LAVI= maximum left atrial volume indexed to BSA, LAEF= left atrial ejection fraction LVEF= left ventricular

ejection fraction, LVMI= left ventricular mass indexed to BSA


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Table7. 5. Independent Predictors for CKD group

CKD group

predictor Beta p-value

LAVI -.004 .976

Diastolic Grade -.122 .227

LVMI .037 .721

E/e' -.125 .229

LA strain .261 .029†

LV strain -.221 .826

NT-pro BNP -.257 .016†

†p<0.05 compared to control LAVI=left atrial volume indexed to BSA, LVMI=left ventricular mass indexed to BSA

Table7. 4. Independent Predictors of NT-pro BNP (log transformed)

NT-pro BNP Predictor Beta

p-value

Group -0.26 0.004† LVMI -0.15 0.09 LA strain -0.19 0.017† LAVI 0.28 0.004† E/e’ 0.18 0.037† LV strain -0.11 0.27 Age 0.15 0.17 †p<0.05 compared to control

LAVI=left atrial volume indexed to BSA, LVMI=left ventricular mass indexed to BSA


111

Inter and intra observer variability

LA strain and strain rate were analysed by 2 different individuals and by the same

individual on a different day, to evaluate inter and intra observer variability. Inter and

intra observer variability was evaluated by estimating intraclass correlation coefficients

(ICC); ICC for LA strain were 0.97(0.92-0.99) and 0.98 (0.95-0.99) respectively. Inter

and intra observer ICC for LA SRs was 0.95 (0.88-0.98) and 0.98 (0.96-0.99), LASRe

0.96 (0.90-0.98) and 0.99 (0.98-0.99) and LASRa 0.97 (0.91-0.99) and 0.99 (0.97-0.99)

respectively.

Discussion

Several patients with CKD present with associated CVD, and have adverse

cardiovascular events; in fact, CKD patients often die from cardiovascular disease rather

than progress to ESRD23 . It is therefore important to find an early marker of

cardiovascular involvement in CKD patients. Such a parameter should be non-invasive

and easily obtainable. Both LA strain as well as BNP have demonstrated alterations

especially in conditions with cardiovascular involvement including myocardial

infarction24, 25 and cardiac failure26. In this study, we evaluated NT-pro BNP levels, LA

volume and function by 2D strain and diastolic dysfunction to determine which of these

parameters would be more sensitive to detect myocardial involvement in stage 3 CKD

patients. Moreover, almost all CKD patients would undergo a transthoracic

echocardiogram as part of their clinical evaluation. We selected only stage 3 CKD

patients as there is a paucity of reports in this particular subgroup, although they

demonstrate a significant increase in adverse CV events27. In our earlier studies we have

reported altered LA function assessed by 2D strain in stage 3 CKD patients9, thereby


112

indicating alterations in LA function metrics even in early CKD. As our present report

is based on a cross sectional study, we are unable to comment on its specific prognostic

value in CKD patients; however, the prognostic value of LA strain has been

demonstrated in other high risk patient groups28, 29.

LAVI has been independently associated with increased cardiovascular risk and CVD

burden30 and is a powerful predictor of medium-term outcome in patients with

suspected heart failure31. LA enlargement is also a predictor of increased cardiovascular

morbidity and mortality in end stage kidney disease32. Combining LA volume with

measures of LA function has been shown to be a more powerful predictor of adverse

events33. 2D LA strain is a new and sensitive method for evaluating global and phasic

LA function34. There are reports demonstrating prognostic utility of LA strain in atrial

fibrillation and cardiomyopathy35, 36. Our group has previously reported that LA strain

was reduced, even though LAVI was similar between the CKD and non CKD controls

with hypertension. We postulated that this could be due to excessive activation of renin-

angiotensin-aldosterone (RAAS) system in CKD. Activation of RAAS can lead to

myocardial fibrosis which in turn alters myocardial deformation properties, with

preferential involvement of the LA over the LV given its relatively thin walls. RAAS

blockade using ACE inhibitor therapy in patients with hypertension has resulted in the

normalisation of LA strain and strain rate37, 38, and would therefore support this

hypothesis.

It has previously been shown that plasma naturetic peptide levels is an independent

predictor of CKD progression39. Even though BNP is excreted by the kidney, BNP

levels that are within the upper reference limit, are seen in most stage 3 CKD patients,

despite having a decreased eGFR40. Hence, altered cardiac function is the more likely

cause for elevated BNP levels in patients with CKD41. rather than as a consequence of


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altered renal function. NT-pro BNP has also demonstrated prognostic utility for adverse

cardiovascular events in patients with advanced renal failure5, 42. Bruch and colleagues

showed that CKD patients with NT-pro BNP >1400pg/ml had poor cardiovascular

outcome. Pfister and colleagues reported that NT-pro BNP was a sensitive marker for

detection of systolic and diastolic heart failure20. However, there is no accepted standard

cut off value for NT-pro BNP or BNP, as indicators of early myocardial involvement in

CKD that could potentiate their use as biomarkers for adverse cardiovascular events.

We found that although NT-pro BNP levels were higher in the CKD group, the absolute

value was within the reference range (<100pg/ml) in all CKD patients. The presence of

CKD was however an independent predictor of NT-pro BNP level on logistic regression

analysis, indicating a relationship between elevation of this peptide and the presence of

CKD. Left atrial parameters (LAVI, LA strain) and diastolic dysfunction were also

independent predictors of NT-pro BNP. Diastolic dysfunction consequent to CKD

would lead to LA enlargement and dysfunction43, and this may in turn increase NT-pro

BNP levels in CKD patients. However, as the NT-pro BNP levels were within the

‘normal’ range, its value as a marker of cardiac involvement in stage 3 CKD patients is

limited.

Echocardiograms are routinely performed in stage 3 CKD patients as part of their

routine clinical evaluation and management. As such, this group of patients often

require serial transthoracic echocardiograms. Interestingly, we found that there was no

significant difference between traditional echocardiographic parameters like LVEF or

LVMI between CKD patients and the control group (with normal renal function); hence

these parameters are unlikely to detect early cardiac involvement in CKD patients with

no previous history of CVD. However, more patients with CKD had abnormal diastolic

function by traditional grading using mitral inflow velocity. While this could be


114

attributed in part to the older age in the CKD patients, in the logistic regression model

diastolic grading was not a predictor of CKD. CKD patients also had a higher E/e’ ratio

indicating elevated LV filling pressure, consequent to diastolic dysfunction. Even

though, E/e’ ratio has been demonstrated to be superior to other echocardiographic

indices for the assessment of diastolic dysfunction as well as LV filling pressure14 , we

observed that the mean E/e’ of 12 was in the ‘grey zone’ ( ie between 8-15) and was not

different to the control group. Hence the use of E/e’ cannot be specifically used to

determine cardiovascular involvement in CKD and may be attributable to associated

risk factors including hypertension and diabetes. LV systolic strain was lower than

reference value in both groups; however, there was no statistically significant difference

between the groups. This may be due to the relatively increased myocardial mass in the

LV compared to the LA, making it a less sensitive marker in early CKD. LA volume

and LA strain parameters including global systolic strain, SRs, SRe and SRa were

abnormal in CKD group compared to control group. As mentioned earlier, we have

demonstrated that LA strain is reduced early, and in this study we demonstrated that this

reduction occurs even prior to any elevation of a cardiac biomarker like NT-pro BNP in

Stage 3 CKD patients, thereby indicating that LA strain parameters are probably more

sensitive and better suited to detect cardiac involvement in this subset of patients.

Moreover 97% of CKD patients had a reduced LA strain while only 45% had an

enlarged LAVI, using standard reference ranges.

Limitations

In this relatively small “proof of concept” study, we compared stage 3 CKD patients

with risk factor matched control patients with normal renal function, on average 13

years younger. As both levels of cardiac protein biomarkers and echocardiographic


115

parameters changes with age, whether age was an unappreciated confounding factor

cannot be specifically be excluded in this study because of the small numbers. This was

a cross sectional study and therefore the impact of these parameters on future adverse

outcomes is not available. However, follow up of these patients is presently underway.

Conclusion

Echocardiographic evaluation of left atrial volume and strain parameters are sensitive

measures that are relatively easy to obtain, and have the potential to be used as

indicators to detect early myocardial involvement in stage 3 CKD patients. Our

analysis demonstrated that LA function parameters using 2D strian are more sensitive

than NT-pro BNP levels in detecting myocardial involvement in CKD. However,

longitudinal studies in a larger cohort of patients are needed to assess their prognostic

implications.

Acknowledgement:

Krishna K. Kadappu received National Health and Medical Research Council

(NHMRC) scholarship to conduct this research.

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function. Echocardiography. 2014;31:956-64.

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17.Yeo KT, Dumont KE, Brough T. Elecsys NT-ProBNP and BNP assays: are there

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Chapter 8: Discussion and concluding remarks


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The “cardio-renal syndrome” is a well described condition in medical literature1. CKD

and heart disease have a close relationship. Traditional risk factors like hypertension

and diabetes, leads to endothelial dysfunction and accelerated atherosclerosis causing

progression of CKD. This results in anaemia, uraemia, volume overload, chronic

inflammation, oxidative stress and nuero-humeral changes which in turn results in

cardiac remodelling, left ventricular hypertrophy, increased ischaemic risk, coronary

and valvular calcification, pump failure and lethal arrhythmias2. Despite CKD being an

independent risk factor for cardiovascular disease, most of the landmark trials excluded

this high risk group from their study population. Importantly, routinely used clinical

cardiovascular risk calculators, such as the Framingham predictive instrument, under

estimate future adverse cardiac events in stage 3 CKD (eGFR 30-59 ml/min/1.73m2)

patients3. For these reasons, there is a need to develop novel non-invasive cardiac bio

markers, over and above clinical risk factors, to estimate individual patient risk to

predict future adverse cardiac events in CKD patients.

8 Cardiac biomarkers in CKD

As mentioned earlier, volume overload along with other co morbidities like

hypertension and diabetes in CKD will result in myocardial hypertrophy and diastolic

dysfunction4. Long standing diastolic dysfunction results in LA enlargement as well as

LA dysfunction. It has also been demonstrated that hypertension, diabetes and CKD all

cause RAAS activation, that in turn causes myocardial fibrosis and cardiac

dysfunction5. This will also result in altered myocardial deformation with consequent

impairment in left atrial and ventricular strain and strain rate6. Atrial and ventricular

involvement also results in elevation in cardiac neuropeptides like naturetic peptide7.


124

LA and LV function were assessed by traditional as well as newer echocardiographic

technique like strain and strain rate; strain analysis has been shown in numerous

conditions to be more accurate than LV ejection fraction ( needs a few refs) Strain and

strain rate enables the evaluation of myocardial deformation throughout the cardiac

cycle, providing a sensitive and accurate assessment of global ventricular and global

and phasic atrial function8, 9. Strain and strain rate can be derived from tissue Doppler

imaging or 2D speckle tracking8.

Cardiac dysfunction has also been evaluated by the measurement of BNP/ NT-pro BNP.

Both of these bio markers have been shown to be elevated in ESRF with poor

prognostic outcome10, 11. However, again there is paucity in literature regarding their

role in early CKD.

There are numerous studies regarding various cardiac biomarkers to assess cardiac

involvement in end stage renal failure (ESRF) and their prognostic utilities12-18. It is

well established that patients with left ventricular hypertrophy, which is common in

ESRF, have poor cardiac outcome4. ESRF patients also have reduced left ventricular

strain, diastolic dysfunction, increased left atrial volume and elevated cardiac troponin

and NT-pro BNP all indicating long term adverse cardiac outcome14, 15, 17, 18. However

there are limited data regarding left atrial volume and function in early CKD. While

alterations in several echocardiographic parameters have been previously demonstrated,

the most sensitive tool among them, to identify cardiac involvement from CKD

independently, especially with coexistent hypertension and diabetes, has not been

determined.

We hypothesised that being a thin walled and low pressure chamber, left atrial metrics

should be altered early in CKD which could be used as an early marker of cardiac


125

involvement in CKD. This in turn helps the clinician to identify the high risk patient

who needs aggressive medical management, to prevent future adverse cardiac events.

To prove our hypothesis, we evaluated traditional echocardiographic parameters

including diastolic dysfunction and LA volume and newer indices like LV and LA

strain parameters as well as NT-pro BNP as a biochemical marker, to assess the

sensitivity of these various parameters to diagnose cardiovascular involvement in early

CKD. Initially we examined these parameters in subjects with risk factors like diabetes

and hyper tension without CKD and compared them with CKD patients with similar

risk factors (ie diabetes and hypertension), which can themselves also cause diastolic

dysfunction with consequent changes in LA and LV metrics.

8. 1 Diastolic dysfunction

We found that more than 75% of a diabetic population studied had diastolic

dysfunction. This was irrespective of their age. The majority of them had grade 2 or

greater diastolic dysfunction. In contrast, only 11% of similar age and sex matched

subjects without diabetes had diastolic dysfunction. It was also noted that traditional

diastolic parameters like E/A ratio, e’ and E/e’ are statistically different in patients with

hypertension. The majority of CKD patients who had hypertension or diabetes also had

diastolic dysfunction. Most of them had grade 2 or greater diastolic dysfunction. We

however did not observe any significant difference in the number of patients with

diastolic dysfunction in diabetics as well as hypertensive patients with normal or

abnormal renal function. Hence assessing diastolic dysfunction by traditional

echocardiographic parameters could not differentiate cardiac involvement from diabetes

or hypertension alone from that associated with CKD.


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8.2 LV strain

LV strain has been used in a variety of conditions to demonstrate subclinical myocardial

dysfunction, when traditional parameters like LV ejection fraction were normal. Left

ventricular strain was significantly reduced in patients with diabetes and hypertension

with normal renal function. When CKD was additionally present, a further reduction of

ventricular strain was observed, but was not statistically different between the groups.

Hence by using ventricular strain, we can diagnose abnormal myocardial deformation,

without the ability to differentiate between CKD, diabetes and hypertension groups.

8.3 Left atrial volume

LA volume is increasingly used as a biomarker of adverse future cardiovascular events.

It has been shown that LA volume indexed to body surface area (LAVI) is increased in

hypertension, diabetes as well as CKD. Additionally, LA volume is a marker of severity

and chronicity of LV diastolic dysfunction.

Interestingly, we observed in our diabetes patients, even those patients classified as

having normal diastolic function had LA enlargement. Further, no significant difference

was observed in LA volumes across the 3 grades of diastolic function. This suggests

that altered LV diastolic function only contributes in part to observed LA changes in

diabetic patients. Thus, it is likely that other factors, contributing to an atrial myopathy

associated with diabetes, may be a likely contributor to LA enlargement. Even though

diabetes independently causes LA enlargement, when associated with CKD, a

differential increase in LA volume was observed compared with the diabetic patients

with normal renal function. Hence LAVI is a useful echocardiographic parameter to

detect specific cardiac involvement in CKD, with the ability to discriminate between

different patient groups.


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Left atrial enlargement is seen in hypertension, with a significantly increased LAVI

compared to age and sex matched healthy adults. We however failed to demonstrate a

significant difference between LAVI in patients with hypertension with normal renal

function and hypertensive patients with CKD.

8.4 LA function by strain analysis

Evaluation of global and phasic LA function using strain and strain rate parameters is

feasible and these parameters have been established as a sensitive measure to assess LA

function. In a variety of clinical conditions, significant reduction in LA function was

evident before significant LA enlargement had occurred, suggesting that LA functional

changes may precede changes in LA volume.

We demonstrated the feasibility of assessing LA global and phasic function by using

strain and strain rate in diabetic patients. Along with LA enlargement, we noted that

there was a reduction in LA function with a decrease in LA global strain and strain rate.

We also noted that hypertension per se causes altered LA function. LA dysfunction was

demonstrated by altered LA strain although strain rate parameters were not significantly

altered.

Importantly, we demonstrated that LA global strain was reduced in patients with

hypertension and diabetes with CKD. This reduction was statistically significant

compared with age, sex and risk factor matched controls with normal renal function.

This indicates that LA strain is the sensitive marker to assess the cardiac involvement in

early CKD compared to other echocardiographic parameters.


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8.5 NT-pro BNP

It has been shown that plasma naturetic peptide levels are a strong and independent

predictor of CKD progression. Altered cardiac function is the likely explanation for

elevated BNP levels in CKD patients. However, in our study, most stage 3 CKD

patients had normal NT-pro BNP levels despite having a decreased eGFR. Even though

the presence of CKD was an independent predictor of NT-pro BNP level, we found that

the absolute value was within the reference range (<100pg/ml) in all CKD patients.

Hence, using current normal values, NT-pro BNP as a marker of cardiac involvement in

stage 3 CKD patients is limited.

8.6 A ‘sensitive’ biomarker to detect cardiac involvement in CKD

From the studies performed, we found that most CKD patients have diastolic

dysfunction, which is also commonly seen in other co-morbid conditions including

hypertension and diabetes. Even though evaluation of diastolic function is a good

diagnostic tool to assess cardiac involvement, its usefulness in differentiate cardiac

involvement in the various conditions is limited. We also showed that NT-pro BNP had

some utility in indicating cardiac involvement in CKD patients; however, as its value

was within the normal reference range, it has limited utility in detecting cardiac

involvement in early CKD.

However, we demonstrated that both LA volume and LA strain parameters are

abnormal in early CKD and that CKD had an independent ‘additive’ effect on LA

metrics even in the presence of hypertension and diabetes. We also showed that LA

volume and LA strain has incremental value in diagnosing cardiac involvement in CKD,

even in the presence of other risk factors. Thus, our research showed that LA metrics

were the most sensitive ‘biomarker’ in demonstrating myocardial involvement in early


129

CKD.

In CKD patients, altered LA compliance with a reduction in reservoir function was

present, as observed by reduced systolic strain rate. Altered LV relaxation with a

consequent reduction in the LA conduit function is likely responsible for the reduced

early diastolic strain rate. Atrial contractile function also was decreased in the CKD

group. Despite similar LAVI in the hypertension and CKD groups, a differential

reduction in LA strain measurements was observed in the CKD group. Thus, LA

functional changes may precede overt LA enlargement, in disease states like CKD.

Based on previous work in animal models19, we postulated that perhaps atrial fibrosis

consequent to RAAS activation in the CKD resulted in the reduction in LA function

over that observed as a consequence of co existent diastolic dysfunction.

8.7 Future direction

LA size and function are very sensitive to alterations in LV function, and are

reproducible echocardiographic parameters. Thus LA metrics may be used to assess

cardiovascular pathology and are increasingly used by clinicians in the follow up of

patients. However, we did not performed longitudinal studies to evaluate alterations in

LA metrics and to determine its value as a prognostic marker as part of this doctoral

thesis. Future studies should be performed investigating the prognostic value of

alterations in LA metrics on cardiovascular outcome in CKD patients. It is likely that

patients who demonstrate an increase in LA volume or reduction in LA strain would be

more likely to have adverse events. It would be important to determine the magnitude of

change that would likely result in adverse events.

Even though we haven’t performed a specific treatment intervention in the CKD patient

group with altered strain, there are few studies that have previously examined the effect


130

of treatment. One such example is by using alteration in LA strain rate in hypertensive

patients following intervention with anti-hypertensive medications. It was noted ACE

inhibitors ‘reverse’ or improve LA strain rate to normal values by 6 weeks20. Our

hypothesis is that activation of RAAS may contribute significantly, causing the

reduction in strain and strain rate in CKD. Future studies with RAAS inhibitor therapy

in CKD patients with abnormal LA strain, should be performed to evaluate if LA

metrics can be improved with such therapeutic intervention. These studies may

additionally help to guide the clinician to facilitate a more detailed understanding of the

pathophysiology of cardiac involvement in CKD.

Increasing technological advances have produced numerous newer techniques for

assessing myocardial function. The current techniques we used to perform strain

analysis are mainly designed to assess the left ventricle. Hence future development of

strain analysis specifically designed to evaluate the left atrium needs to be developed

and validated.

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Cardiac biomarkers in Chronic Kidney Disease - UNSWorks

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