Influence of diabetes on characteristics and outcomesin patients hospitalized with heart failure:A report from the Organized Program to InitiateLifesaving Treatment in Hospitalized Patients withHeart Failure (OPTIMIZE-HF)Barry H. Greenberg, MD,a William T. Abraham, MD,b Nancy M. Albert, PhD, RN,c Karen Chiswell, MS,d

Robert Clare, MS,d Wendy Gattis Stough, PharmD,e Mihai Gheorghiade, MD,f Christopher M. O’Connor, MD,e

Jie Lena Sun, MS,d Clyde W. Yancy, MD,g James B. Young, MD,c and Gregg C. Fonarow, MDh San Diego andLos Angeles, CA; Columbus and Cleveland, OH; Durham, NC; Chicago, IL; and Dallas, TX

Background Diabetes, a common comorbidity in patients with heart failure (HF), is associated with worse long-termoutcomes in patients with HF due to systolic dysfunction. Whether diabetes mellitus (DM) influences characteristics andoutcomes in patients hospitalized with HF has not been well studied.

Methods The Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure is a patientregistry and performance-improvement program for patients hospitalized with HF that included a prespecified 10% subgroupwith 60- to 90-day follow-up data. Data were analyzed as DM compared with no DM. Pearson m2 test for categoricalvariables and t test for continuous variables were used, as was a multivariable analysis that included a stepwise Coxproportional hazard model.

Results Among 48,612 patients from 259 hospitals, 42% had DM. Heart failure patients with DM tended to be younger,with greater likelihood of ischemic etiology, and higher serum creatinine levels. Heart failure patients with DM receivedquality care measures to a similar degree, with a few modest exceptions. No differences in in-hospital mortality wereobserved, but HF patients with DM experienced modestly longer length of stay (5.9 vs 5.5 days for nondiabetic patients; P b

.0001). In the 5791 patients in the follow-up cohort, patients with DM (n = 2464) had similar postdischarge mortality butincreased all-cause rehospitalization (31.5% vs 28.2% for nondiabetic patients; P = .006). Multivariable analysis showedthat DM was not an independent predictor of in-hospital (odds ratio, 1.00; 95% confidence interval, 0.88-1.14; P = .99) orfollow-up mortality (hazard ratio, 1.08; 95% confidence interval, 0.87-1.35; P = .48).

Conclusions The Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure datareveal a high prevalence of DM in patients hospitalized with HF. Heat failure patients with DM received similar quality ofcare and experienced similar short-term mortality compared with patients without DM but had higher risk of rehospitalization.(Am Heart J 2007;154:647254.)

From the aUniversity of California-San Diego Medical Center, San Diego, CA, bOhio

State University, Columbus, OH, cCleveland Clinic Foundation, Cleveland, OH, dDuke

Clinical Research Institute, Durham, NC, eDuke University Medical Center, Durham, NC,fNorthwestern Feinberg School of Medicine, Chicago, IL, gBaylor University Medical

Center, Dallas, TX, and hUCLA Medical Center, Los Angeles, CA.

The OPTIMIZE-HF registry and this study were supported by GlaxoSmithKline,

Philadelphia, PA.

The OPTIMIZE-HF registry is registered: www.clinicaltrials.gov, study number

NCT00344513.

Submitted January 30, 2007; accepted May 1, 2007.

Reprint requests: Barry H. Greenberg, MD, University of California-San Diego Medical

Center, 200 W. Arbor Drive, #8411, San Diego, CA 92103-8411.

E-mail: bgreenberg@ucsd.edu

0002-8703/$ - see front matter

doi:10.1016/j.ahj.2007.08.002

Diabetes mellitus (DM) is a common comorbid

condition of heart failure (HF),1 and the prevalence of

HF among diabetic patients is 2 to 3 times that of age-

matched controls.2,3 Among the selected group of

patients enrolled in chronic systolic HF clinical trials,

generally 20% to 30% have DM, with a similar observed

percentage (28%) for patients with preserved systolic HF

investigated in the Candesartan in Heart Failure: Assess-

ment of Reduction in Mortality and Morbidity (CHARM)-

Preserved trial.4-9 Although these patients sometimes

have worse long-term outcomes than their nondiabetic

counterparts, analyses from several major clinical studies

American Heart Journal

October 2007648 Greenberg et al

have shown that the reduction in HF mortality and

morbidity observed in treatment with angiotensin-con-

verting enzyme inhibitors (ACEI), aldosterone antago-

nists, and h-blockers extends to diabetic

patients.4,5,7,8,10-12

Currently, little is known about the prevalence of DM

and the effect of its presence on the characteristics,

treatment, and outcomes in patients hospitalized for HF.

In addition, very little is known about how well

guideline-recommended therapies are being used in

patients with HF with DM. Although h-blockers are

recommended by national guidelines for use in diabetic

patients with HF,13,14 they have been underutilized in

this population due to perceived negative metabolic

effects.15,16 Analyses of large patient databases from all

regions of the country are critical in providing insight

into whether optimal evidence-based therapies are used

in HF patients with DM.

Organized Program to Initiate Lifesaving Treatment in

Hospitalized Patients with Heart Failure (OPTIMIZE-HF) is

a registry and performance-improvement program for

patients hospitalized with HF. This analysis of the

OPTIMIZE-HF patient registry data aims to document the

prevalence of DM in patients hospitalized for HF; assess

the associations between DM and the characteristics,

quality of care, treatment, and outcomes in these patients;

and improve the understanding of the influence of DM on

treatment and outcomes in patients hospitalized for wor-

sening HF with reduced or preserved systolic function.

MethodsThe OPTIMIZE-HF was a comprehensive hospital-based

registry and process-of-case improvement program designed to

provide optimal medical care and education to patients

hospitalized for HF. The OPTIMIZE-HF program has been

described in detail elsewhere17-19 and will be briefly summa-

rized below.

OPTIMIZE-HF patient eligibilityEligible patients were hospitalized for episodes of new-

onset or worsening HF as the primary cause of admission or

had significant HF symptoms that developed during hospital-

ization where HF was the primary discharge diagnosis.17 Left

ventricular systolic dysfunction (LVSD) was defined as a

documented left ventricular ejection fraction b40% or quali-

tative assessment of moderate/severe dysfunction. Diabetes

and insulin use was assessed by past medical and medication

history as documented in the medical record.

From March 2003 to December 31, 2004, 48,612 patients

hospitalized at 259 centers in the United States were enrolled in

the OPTIMIZE-HF registry. All regions of the United States were

represented, and institutions from community hospitals to large

tertiary medical centers participated.17,18 A prespecified sub-

group of patients (10%) enrolled from 91 hospitals had 60- to 90-

day follow-up data, and this cohort was demographically similar

to patients in the overall registry.18,19 Participants were

screened for inclusion before hospital discharge or identified

from administrative databases subsequent to discharge. The

registry component captured data on important characteristics

(demographic, pathophysiologic, and clinical), treatment

patterns, and outcomes of patients hospitalized for HF using

a web-based case report form.17 Written informed consent

was obtained before enrollment from patients who partici-

pated in the follow-up data collection. The protocol was

approved by each participating center’s institutional review

board or through use of a central institutional review board.

The registry coordinating center was Outcome Sciences, Inc

(Cambridge, MA).

OPTIMIZE-HF Registry Process-of-CareImprovement Program

The OPTIMIZE-HF Process-of-Care Improvement Program

assisted hospitals in improving the quality of care in hospital-

ized patients with HF through the use of a hospital tool kit

including order sets, treatment algorithms, discharge check-

lists, and structured educational materials, as previously

described.17 Through the use of these materials and bench-

marked feedback data, OPTIMIZE-HF aimed to accelerate the

adoption of evidence-based, guideline-recommended therapies.

This analysis of the OPTIMIZE-HF registry assessed the

presence or absence of DM as documented in the medical record

in patients hospitalized for HF. The association of DM with the

characteristics, quality of care, treatment, and outcomes in these

patients was analyzed. Specific measures examined in this patient

population include the use of evidence-based medicines (ACEI

and/or angiotensin receptor blockers [ARB], aldosterone antag-

onists, aspirin, h-blockers, statins, and warfarin); Joint Commis-

sion on Accreditation of Healthcare Organizations (JCAHO) core

HF measures (complete discharge instructions, LVEF assessment,

discharge ACEI use, smoking-cessation counseling); and clinical

outcomes in-hospital (length of stay, in-hospital mortality) and at

60- to 90-day follow-up (all-cause rehospitalization, all-cause

mortality) as previously described.17-19

Statistical analysisAll statistical analyses were performed independently at the

Duke Clinical Research Institute (Durham, NC). The data are

reported as mean and standard deviation for continuous

variables or percentages of nonmissing values for categorical

variables. Data on HF medication use are reported as the

number and frequency of eligible patients, and contraindica-

tions/intolerance were assessed at discharge from the index

hospitalization and during follow-up. Patient characteristics

and evidence-based treatments at hospital discharge were

compared using Pearson m2 test for categorical variables and

t test for continuous variables. Multivariable models of in-

hospital death, length of hospital stay, postdischarge mortality,

and postdischarge death or rehospitalization were developed to

be used for consistent covariate adjustment across all studies.

The types of models were logistic for in-hospital mortality,

general linear modeling for length of stay, Cox proportional

hazards for postdischarge mortality, and logistic for postdi-

scharge mortality and rehospitalization (date of rehospitaliza-

tion was not available for survival modeling). The model-

development process was similar for all 4 outcomes and used

stepwise and backward variable selection methods. The

linearity assumption for continuous measures was evaluated

Table I. Patient characteristics at hospital admission and discharge

Variable Diabetes (n = 20,162) No diabetes (n = 28,450) P4

Mean age (SD), y 71.5 (12.2) 74.4 (15.0) b.0001Women, % 51.6 51.6 .9992White, % 71.3 76.2 b.0001African American, % 19.2 16.6LVSD, % 47 50 b.0001Mean LVEF (SD), % 39.7 (17.2) 38.5 (18.0) b.0001Ischemic etiology, % 51.8 41.4 b.0001Atrial arrhythmia, % 26.2 34.0 b.0001Hyperlipidemia, % 39.8 26.7 b.0001Hypertension, % 77.0 66.6 b.0001Peripheral vascular disease, % 18.0 10.6 b.0001CVA/TIA, % 17.1 14.4 b.0001COPD 27.7 27.4 .5047CABG or PCI 33.9 24.2 b.0001Cigarette smoker within the past year, % 14.2 18.2 b.0001Mean serum creatinine (SD), mg/dL 1.93 (1.61) 1.65 (1.50) b.0001Chronic renal insufficiency (serum creatinine N2 mg/dL), % 25.5 15.4 b.0001Mean admission serum sodium (SD), mmol/L 137.69 (4.60) 137.83 (4.84) .0020Mean admission hemoglobin (SD), g/dL 11.83 (2.00) 12.34 (2.04) b.0001Mean admission B-type natriuretic peptide (SD), pg/mL 1212.1 (1275.9) 1324.0 (1364.8) b.0001Mean admission troponin I (SD), ng/mL 0.51 (1.54) 0.47 (1.36) .0188Edema at admission, % 70.4 60.6 b.0001Edema at discharge, % 31.7 23.5 b.0001Mean admission weight (SD), kg 89.8 (26.7) 77.4 (24.7) b.0001Mean weight change from admission (SD), kg –2.69 (5.12) –2.43 (4.5) b.0001Mean admission SBP (SD), mm Hg 145.2 (32.8) 140.9 (32.9) b.0001Mean discharge SBP (SD), mm Hg 127.9 (22.8) 122.6 (22.0) b.0001Mean admission heart rate (SD), beats/min 85.0 (20.4) 87.7 (22.1) b.0001Mean discharge heart rate (SD), beats/min 75.3 (13.7) 76.5 (14.5) b.0001ACEI before admission, % 43.0 37.3 b.0001ARB before admission, % 14.0 10.2 b.0001Aldosterone antagonist before admission, % 7.7 6.6 b.0001h-Blocker before admission, % 57.8 49.8 b.0001Digoxin before admission, % 23.5 23.3 .7008Diuretic before admission, % 71.1 61.8 b.0001

CVA/TIA, Cerebrovascular accident/transient ischemic attack; COPD, chronic obstructive pulmonary disease; CABG, coronary artery bypass graft; PCI, percutaneous coronaryintervention; SBP, systolic blood pressure.4Due to the large number of patients in the registry, some small differences that may be of little clinical relevance have P values indicating a high degree of statistical significance.

American Heart Journal

Volume 154, Number 4Greenberg et al 649

using restricted cubic spline transformations. When needed,

appropriate transformations such as piecewise linear splines

were applied. A P value of .05 was used for both entry and

remaining in the model. The potential covariates were prese-

lected with 45 for in-hospital mortality, 39 for length of stay, 19

for postdischarge mortality, and 70 for postdischarge mortality

or rehospitalization (Supplemental appendix). To test the

relative effect of diabetes in the final adjusted model, an

indicator for the presence or absence of diabetes was

added to the model. The relative effect of insulin-treated

diabetes versus non–insulin-treated diabetes in the final

model was investigated in a similar manner. SAS version

8.2 (SAS Institute, Cary, NC) was used for all statistical

analyses.

ResultsPatient comparison

This analysis included 48,612 patients at 259 hospitals,

with follow-up data from 5791 patients. Among patients

hospitalized for HF, 42% had diabetes (n = 20,162). Of

these patients with DM, 40% were treated with insulin

(n = 8058). The overall registry population was elderly,

with a mean age of 73.2 years, and patients with DM

were slightly younger than their nondiabetic counter-

parts (71.5 F 12.2 vs 74.4 F 15.0 years; P b .0001).

Diabetic patients were more likely to have an ischemic

etiology, hyperlipidemia, and a hypertension history

than the nondiabetic cohort. In addition, these diabetic

patients were less likely to be white, have atrial

arrhythmia, or be cigarette smokers. They were also

more likely to have edema on admission and discharge,

to weigh more on admission and discharge, and to have

higher systolic blood pressure on admission and dis-

charge. Patients with DM were more likely to have a

history of renal insufficiency, and admission serum

creatinine was significantly higher than in patients

without DM (1.93 vs 1.65 mg/dL; P b .0001). Further-

more, this cohort demonstrated lower B-type natriuretic

Figure 1

Percent of patients receiving HF measures at hospital discharge bydiabetes status.

Figure 2

Eligible patients receiving other medications at hospital dischargeby diabetes status. *ACEI/ARB use in patients with LVSD, excludingpatients with contraindications. yh-Blocker use in patients withLVSD, excluding patients with contraindications. zStatin use inpatients with medical history of coronary artery disease, cerebro-vascular accident/transient ischemic attack, diabetes, hyperlipid-emia, or peripheral vascular disease. §Aldosterone antagonist usein patients with LVSD. ||Warfarin use in patients with chronic orparoxysmal atrial fibrillation.

American Heart Journal

October 2007650 Greenberg et al

peptide levels compared with patients without DM.

Table I summarizes the patient characteristics at admis-

sion and discharge in patients with and without DM.

Quality of careQuality of care for patients with HF within the

OPTIMIZE-HF program was assessed using performance

measures from JCAHO as well as additional quality

measures, including discharge use of h-blockers, ACEI/

ARB, and warfarin for patients with atrial fibrillation, as

previously described.17-19 Analysis of performance on

specific JCAHO quality measures within this registry

demonstrated that patients with DM were less likely to

receive ACEI in the absence of contraindications and

intolerance (72.9% vs 76.8%; P b .0001). LVEF assessment

was also slightly less in diabetic patients (85.9% vs 87.0%;

P = .0013). Diabetic patients participating in OPTIMIZE-

HF were just as likely as nondiabetic patients to receive

smoking-cessation counseling and complete discharge

instructions (Figure 1). Additional OPTIMIZE-HF quality

measures showed that eligible patients with DM were

slightly less likely to be treated at discharge with ACEI/

ARB (81.0% vs 83.6%; P b .0001), slightly more likely to be

treated with h-blockers (83.9% vs 82.6%; P = .0246), and

just as likely to be treated with warfarin and aldosterone

antagonists (Figure 2). The use of statins was significantly

greater in diabetics than in nondiabetics (41.3% vs 36.7%;

P b .0001), a finding that may be related to the higher

likelihood of ischemic disease in these enrolled diabetic

patients. Further analysis of patients based on insulin

treatment showed no significant differences between

insulin-treated and non–insulin-treated patients

except that insulin-treated patients were slightly less

likely to have left ventricle function assessment (84.5% vs

86.8%; P b .0001).

Analysis regarding guideline-recommended medication

use in the 60- to 90-day cohort was performed on the

diabetic and nondiabetic subgroups within the registry.

Patients with DM and LVSD were more likely to be

receiving ACEI therapy (52% of diabetics with LVSD vs

42.9% of nondiabetics with LVSD; P b .0001), with a

similar result observed with ARB therapy (13.6% of

diabetics with LVSD vs 10.3% of nondiabetics with LVSD;

P = .009) when reevaluated at 60- to 90-day follow-up.

Overall, the rate of ACEI/ARB therapy was significantly

higher in diabetic patients with LVSD (63.9% of diabetics

vs 52.9% of nondiabetics; P b .0001). In addition, during

the 60- to 90-day reevaluation, h-blocker use in patients

with DM and LVSD was higher than in nondiabetic

patients (63.5% of diabetics vs 51.9% of nondiabetics;

P b .0001). Interestingly, use of carvedilol, a third-

generation h-adrenergic antagonist, was higher in dia-

betic patients with LVSD than in nondiabetic patients

with LVSD (30.9% vs 23.9%, respectively; P b .0001).

Clinical outcomesIn-hospital mortality was similar for diabetic and

nondiabetic patients with HF (3.6% vs 3.9%; P = .08)

(Table II). Patients with DM did experience a modestly

increased length of stay (5.9 vs 5.5 days; P b .0001). In

Table II. In-hospital and 60- to 90-day follow-up outcomes by diabetes and left ventricular function

Diabetes(n = 20,162)

No diabetes(n = 28,450)

P value forinteraction

P valuewithin group

Mean length of stay (SD), dTotal cohort 5.87 (5.69) 5.46 (5.34) .2602 b.0001LVSD 6.22 (6.20) 5.73 (5.83) b.0001No LVSD 5.91 (5.40) 5.55 (5.05) b.0001

In-hospital mortality, n (%)Total cohort 724/20,162 (3.6) 1110/28,450 (3.9) .2976 .0765LVSD 312/8010 (3.9) 470/12,108 (3.9) .9616No LVSD 244/9039 (2.7) 365/12,110 (3.0) .1761

60- to 90-d rehospitalization, n (%)Total cohort 777/2464 (31.5) 938/3327 (28.2) .0378 .0059LVSD 378/1123 (33.7) 435/1597 (27.2) .0003No LVSD 310/1042 (29.8) 390/1355 (28.8) .6049

60- to 90-d mortality, n (%)Total cohort 194/2396 (8.1) 287/3210 (8.9) .0021 .2643LVSD 103/1092 (9.4) 118/1545 (7.6) .1019No LVSD 63/1018 (6.2) 120/1304 (9.2) .0079

60- to 90-d mortality and/or rehospitalization, n (%)Total cohort 900/2398 (37.5) 1133/3212 (35.3) .0012 .0819LVSD 440/1093 (40.3) 512/1545 (33.1) .0002No LVSD 349/1018 (34.3) 472/1306 (36.1) .3526

American Heart Journal

Volume 154, Number 4Greenberg et al 651

addition, among the follow-up cohort, HF patients with

DM had a higher incidence of rehospitalization com-

pared with HF patients without DM (31.5% compared to

28.2%; P = .006).

On multivariable analysis, diabetes status was not an

independent predictor of in-hospital or postdischarge

mortality (in-hospital mortality: odds ratio [OR], 1.00;

95% confidence interval [CI], 0.88-1.14; P = .99;

postdischarge mortality: hazard ratio, 1.08; 95% CI, 0.87-

1.35; P = .48). In addition, diabetes was not an

independent predictor of 60- to 90-day mortality and/or

rehospitalization (OR, 1.06; 95% CI, 0.92-1.22; P = .43).

An additional multivariable analysis demonstrated that

insulin-treated diabetes status was not an independent

predictor of in-hospital or postdischarge mortality (in-

hospital mortality: OR, 1.11; 95% CI, 0.92-1.34; P = .29;

postdischarge mortality: hazard ratio, 1.24; 95% CI, 0.89-

1.73; P = .21) or 60- to 90-day mortality and/or

rehospitalization (OR, 1.15; 95% CI, 0.94-1.42; P = .17).

The patient population in the OPTIMIZE-HF registry

was also stratified based on the presence or absence of

LVSD (Table II). For patients with LVSD, those with DM

had increased incidence of rehospitalization (33.7% vs

27.2%; P = .0003) compared to nondiabetic patients

with LVSD. For patients with LVSD, the presence of

diabetes was associated with an increased risk for 60- to

90-day mortality and/or rehospitalization (OR, 1.33; 95%

CI, 1.12-1.59; P = .001).

In those patients without LVSD, DM was not related to

in-hospital mortality or follow-up rehospitalization

(Table II). Diabetes was associated with a lower

likelihood of follow-up mortality (6.2% vs 9.2%; P = .008)

in patients with preserved systolic function (Table II). In

contrast to what was observed for patients with LVSD, in

patients with preserved systolic function, DM was not

associated with an increased risk for 60- to 90-day

mortality and/or rehospitalization (OR, 0.98; 95% CI,

0.81-1.19; P = .87). The association of the use of ACEI/

ARB and h-blocker in eligible patients with and without

diabetes with 60- to 90-day death and death/rehospital-

ization was similar to the findings for the overall cohort

(Supplemental appendix).

DiscussionThis analysis from OPTIMIZE-HF demonstrates that a

very high prevalence of DM exists among hospitalized

patients with HF, with 42% of those enrolled having DM

documented. A prevalence similar to that of the current

study has also been observed in the Acute Decompen-

sated Heart Failure National Registry, which showed that

44% of hospitalized patients with HF have DM.20 In the

Enhanced Feedback for Effective Cardiac Treatment

study of 4031 community-based patients presenting

with new onset HF at multiple hospitals in Ontario,

Canada, from 1997 to 2001, the prevalence of diabetes

was 34%.21 Interestingly, clinical trials investigating the

use of HF therapies have generally enrolled populations

with a substantially lower prevalence of DM.4-9

One possible explanation for the underrepresentation

of the diabetic cohort in clinical trials is a common

presumption that patients with DM are not treated in

the same manner as their nondiabetic counterparts due

to potential problems associated with tolerance and

adherence to medication strategies, particularly

American Heart Journal

October 2007652 Greenberg et al

h-blockade. Results from OPTIMIZE-HF demonstrate

that this assumption may not be founded. Participation

in the OPTIMIZE-HF performance-improvement pro-

gram was associated with remarkably high rates of

h-blocker treatment at hospital discharge among eligi-

ble HF patients with and without DM. This is a

significant finding, considering conflicting views on

h-blocker use being contraindicated in diabetic patients

with HF due to the possible worsening of glycemic and

metabolic parameters.15,16 In fact, as noted earlier, the

actual percentage of HF patients with DM using

h-blocker therapy at the 60- to 90-day follow-up period

was higher than that among HF patients without DM.

In addition, patients with DM were more likely to be

retained on ACEI/ARB at the 60- to 90-day follow-up

compared with HF patients without DM. These results

describing the use of evidence-based medication use

shed new light on managing medication strategies in

HF patients with DM, and, based on them, one may

argue that HF patients with DM need not be excluded

and that aggressive evidence-based therapies are war-

ranted in both diabetic and nondiabetic cohorts of

patients with HF.

The presence of DM in patients with HF has been

shown in previous studies to be associated with an

increased risk for poor outcomes.21-26 An analysis

from the Studies of Left Ventricular Dysfunction trials

and registry program demonstrated that the presence

of DM in patients with HF resulted in an increased

risk for mortality.23 However, this increased mortality

risk with DM was confined to patients with coronary

artery disease, with no increase in mortality risk in

patients with nonischemic HF.26 The Beta-Blocker

Evaluation of Survival Trial reported a DM prevalence

of 36% among patients with HF enrolled, and on

multivariable analysis showed that DM was indepen-

dently associated with a 22% increased risk of all-

cause mortality ( P = .007).25 Interestingly, this

increased risk was also found to be confined to

those patients with an ischemic cardiomyopathy

etiology of HF. Results from the Danish Investiga-

tions of Arrhythmia and Mortality on Dofetilide study

demonstrated an independent risk for mortality

associated with DM in patients hospitalized with

HF.26 The increased risk of diabetes was similar in

those patients with depressed and normal left

ventricular systolic function.24 Recently, an analysis

from the CHARM program showed that the predicted

risk for mortality associated with DM in this 2-year

study was found to be 2 times greater for patients

treated with insulin and 58% greater for non–insulin-

treated patients compared to those HF patients

without DM.22

In contrast, the present analysis of short-term clinical

outcomes in the OPTIMIZE-HF registry demonstrates

that in-hospital and 60- to 90-day follow-up mortality

rates were similar in patients with DM and those

without, despite the increased frequency of baseline

characteristics associated with increased mortality risk.

Surprisingly, among HF patients without LVSD, those

with DM actually had significantly lower all-cause

postdischarge mortality than patients without DM (6.2%

vs 9.2%; P = .008). The outcome data within OPTIMIZE-

HF could have been influenced by the high use of

evidence-based therapies among patients with DM in

this study. Use of these proven treatments may have

minimized the outcomes differences between the dia-

betic and nondiabetic patients enrolled, although

patients with DM and HF were shown to experience a

longer length of hospital stay and higher rehospitaliza-

tion rates compared with HF patients without DM.

Alternatively, in the first 60- to 90-day follow-up period,

DM may have little adverse effect on mortality, but with

longer term follow-up, an adverse effect on prognosis

becomes evident. Results of previous studies demon-

strating an increased risk for mortality were derived

from patients over longer periods of time.22-26 In the

Enhanced Feedback for Effective Cardiac Treatment

study, diabetes was a univariate predictor of a 25% lower

30-day and a 19% lower 1-year post hospital discharge

mortality; on multivariate analysis, diabetes was not

independently predictive of either higher or lower

mortality risk.21

There are a number of important limitations to this

analysis. All clinically relevant medical histories,

including diabetes status, were obtained as docu-

mented in the medical record. There may have been

patients with DM who had not yet been diagnosed at

study entry, which would further increase the already

high proportion of patients with HF and DM.

Information regarding the degree of glycemic control,

duration of diabetes, and diabetes medications other

than insulin was not captured. Medication use in

OPTIMIZE-HF is as documented in the medical

record, and it is therefore possible that actual

adherence rates may have been lower than reported.

In addition, contraindications and intolerance were as

documented in the medical record, and a proportion

of patients reported to be eligible but not treated

may have had contraindications that went undocu-

mented. The OPTIMIZE-HF was not designed as a

prospective randomized trial, and unmeasured con-

founders may have influenced clinical outcomes.

These findings may not apply to hospitals that differ

in patient characteristics or care patterns from

OPTIMIZE-HF hospitals. Given the overall large num-

ber of patients observed, some differences, although

statistically significant, may not be clinically relevant.

Follow-up data were obtained in a subset of patients

and were limited to 60 to 90 days. Despite these

limitations, this analysis provides new insights into

the characteristics, treatments, and outcomes from a

American Heart Journal

Volume 154, Number 4Greenberg et al 653

large representative data set of patients hospitalized

with HF, including patients with preserved systolic

function and multiple comorbidities.

ConclusionThis report from the OPTIMIZE-HF registry revealed

a high prevalence of DM (42%) among patients

hospitalized with HF. In addition, this registry dem-

onstrated that HF patients with DM differed from

those without DM in a number of important charac-

teristics, including younger age, greater ischemic

etiology, and increased renal dysfunction. Treatment

and clinical outcomes in HF patients with DM were

relatively similar to those without DM. Importantly,

the presence of DM was not associated with increased

mortality, either during hospitalization or during the

60 to 90 days of postdischarge follow-up. These

results provide additional support for the use of

aggressive evidence-based therapies in HF patients

with DM, and they challenge traditional lines of

thought on the difficulties in treating this at-risk

patient population.

Appendix A. Supplementary dataSupplementary data associated with this article can be found,

in the online version, at doi:10.1016/j.ahj.2007.08.002.

References1. Kannel WB, D’Agostino RB, Silbershatz H, et al. Profile for

estimating risk of heart failure. Arch Intern Med 1999;159:1197 -204.

2. Nichols GA, Hillier TA, Erbey JR, et al. Congestive heart failure intype 2 diabetes: prevalence, incidence, and risk factors. DiabetesCare 2001;24:1614 -9.

3. Kannel WB, Hjortland M, Castelli WP. Role of diabetes incongestive heart failure: the Framingham study. Am J Cardiol1974;34:29 -34.

4. MERIT-HF Investigators. Effect of metoprolol CR/XL inchronic heart failure: Metoprolol CR/XL Randomised InterventionTrial in Congestive Heart Failure (MERIT-HF). Lancet 1999;353:2001 -7.

5. Poole-Wilson PA, Swedberg K, Cleland JG, et al. Comparisonof carvedilol and metoprolol on clinical outcomes in patientswith chronic heart failure in the Carvedilol or MetoprololEuropean Trial (COMET): randomised controlled trial. Lancet2003;362:7 -13.

6. CONSENSUS Trial Study Group. Effects of enalapril on mortality insevere congestive heart failure. Results of the Cooperative NorthScandinavian Enalapril Survival Study (CONSENSUS). N Engl JMed 1987;316:1429-35.

7. Cohn JN, Tognoni G. A randomized trial of the angiotensin-receptor blocker valsartan in chronic heart failure. N Engl J Med2001;345:1667-75.

8. Pitt B, Poole-Wilson PA, Segal R, et al. Effect of losartan comparedwith captopril on mortality in patients with symptomatic heart failure:randomised trial—the Losartan Heart Failure Survival Study ELITE II.Lancet 2000;355:1582 -7.

9. Yusuf S, Pfeffer MA, Swedberg K, et al. Effects of candesartan inpatients with chronic heart failure and preserved left-ventricularejection fraction: the CHARM-Preserved Trial. Lancet2003;362:777 -81.

10. Yusuf S, Sleight P, Pogue J, et al. Effects of an angiotensin-converting–enzyme inhibitor, ramipril, on cardiovascular events inhigh-risk patients. The Heart Outcomes Prevention Evaluation StudyInvestigators. N Engl J Med 2000;342:145 -53.

11. Shekelle PG, Rich MW, Morton SC, et al. Efficacy of angiotensin-converting enzyme inhibitors and beta-blockers in the managementof left ventricular systolic dysfunction according to race, gender, anddiabetic status. A meta-analysis of major clinical trials. J Am CollCardiol 2003;41:1529 -38.

12. Deedwania PC, Giles TD, Klibaner M, et al. Efficacy, safety andtolerability of metoprolol CR/XL in patients with diabetes andchronic heart failure: experiences from MERIT-HF. Am Heart J2005;149:159 -67.

13. Hunt SA, Abraham WT, Chin MH, et al. ACC/AHA 2005guideline update for the diagnosis and management of chronicheart failure in the adult: a report of the American College ofCardiology/American Heart Association Task Force on PracticeGuidelines American College of Cardiology Website. Available at:http://www.acc.org/qualityandscience/clinical/guidelines/failure/update/index.pdf, 2005.

14. Adams KF, Lindenfeld J, Arnold JMO, et al. HFSA 2006comprehensive heart failure practice guideline. J Card Fail2006;12:e1- e122.

15. Giugliano D, Acampora R, Marfella R, et al. Metabolic andcardiovascular effects of carvedilol and atenolol in non–insulin-dependent diabetes mellitus and hypertension: a randomized,controlled trial. Ann Intern Med 1997;126:955 -9.

16. Jacob S, Rett K, Wicklmayr M, et al. Differential effect ofchronic treatment with two beta-blocking agents on insulinsensitivity: the carvedilol-metoprolol study. J Hypertens1996;14:489 -94.

17. Fonarow GC, Abraham WT, Albert NM, et al. Organized Programto Initiate Lifesaving Treatment in Hospitalized Patients with HeartFailure (OPTIMIZE-HF): rationale and design. Am Heart J2004;148:43 -51.

18. Gheorghiade M, Abraham WT, Albert NM, et al. Systolic bloodpressure at admission, clinical characteristics, and outcomes in patientshospitalized with acute heart failure. JAMA 2006;296:2217-26.

19. Fonarow GC, Abraham WT, Albert NM, et al. Association betweenperformance measures and clinical outcomes for patients hospital-ized with heart failure. JAMA 2007;297:61 -70.

20. Adams KF, Fonarow GC, Emerman CL, et al. Characteristicsand outcomes of patients hospitalized for heart failure in theUnited States: rationale, design, and preliminary observationsfrom the first 100,000 cases in the Acute Decompensated HeartFailure National Registry (ADHERE). Am Heart J2005;149:209 -16.

21. Lee DS, Austin PC, Rouleau JL, et al. Predicting mortality amongpatients hospitalized for heart failure: derivation and validation of aclinical model. JAMA 2003;290:2581-7.

22. Pocock SJ, Wang D, Pfeffer MA, et al. Predictors of mortality andmorbidity in patients with chronic heart failure. Eur Heart J2006;27:65 -75.

23. Shindler DM, Kostis JB, Yusuf S, et al. Diabetes mellitus, a predictorof morbidity and mortality in the Studies of Left VentricularDysfunction (SOLVD) trials and registry. Am J Cardiol1996;77:1017 -20.

American Heart Journal

October 2007654 Greenberg et al

24. Gustafsson I, Brendorp B, Seibaek M, et al. Influence of diabetesand diabetes-gender interaction on the risk of death in patientshospitalized with congestive heart failure. J Am Coll Cardiol2004;43:771 -7.

25. Domanski M, Krause-Steinrauf H, Deedwania P, et al. Theeffect of diabetes on outcomes of patients with advanced

heart failure in the BEST trial. J Am Coll Cardiol2003;42:914 -22.

26. Dries DL, Sweitzer NK, Drazner MH, et al. Prognostic impact ofdiabetes mellitus in patients with heart failure according to theetiology of left ventricular systolic dysfunction. J Am Coll Cardiol2001;38:421 -8.