Atrial Fibrillation and Risk of ST-Segment Elevation versus Non-ST Segment Elevation Myocardial...

DOI: 10.1161/CIRCULATIONAHA.114.014145

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Atrial Fibrillation and Risk of ST-Segment Elevation versus

Non-ST Segment Elevation Myocardial Infarction:

The Atherosclerosis Risk in Communities (ARIC) Study

Running title: Soliman et al.; AF and risk of MI by type

Elsayed Z. Soliman, MD, MSc, MS1,2; Faye Lopez, MS, MPH3; Wesley T. O’Neal, MD, MPH4;

Lin Y. Chen, MD5; Lindsay Bengtson, PhD3; Zhu-Ming Zhang, MD, MPH1; Laura Loehr, MD,

PhD6; Mary Cushman, MD, MSc7; Alvaro Alonso MD, PhD3

1Epidemiological Cardiology Research Center (EPICARE), Dept of Epidemiology and Prevention, Wake Forest School of Medicine, Winston Salem, NC; 2Dept of Internal Medicine,

Section on Cardiology, Wake Forest School of Medicine, Winston Salem, NC; 3Division of Epidemiology and Community Health, School of Public Health, University of Minnesota,

Minneapolis, MN; 4Dept of Internal Medicine, Wake Forest School of Medicine, Winston Salem, NC; 5Cardiovascular Division, Dept of Medicine, University of Minnesota Medical School,

Minneapolis, MN; 6Dept of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC; 7Dept of Medicine, University of Vermont,

Burlington, VT

Address for Correspondence:

Elsayed Z. Soliman MD, MSc, MS, FAHA, FACC

Epidemiological Cardiology Research Center (EPICARE)

Wake Forest School of Medicine

Medical Center Blvd

Winston Salem, NC 27157

Tel: 336-716-8632

Fax: 336-716-0834

E-mail [email protected]

Journal Subject Codes: Etiology:[8] Epidemiology, Diagnostic testing:[171] Electrocardiology

PhD6; Mary Cushman, MD, MSc7; Alvaro Alonso MD, PhD3

1Epidemiological Cardiology Research Center (EPICARE), Dept of Epidemiology and rPrevention, Wake Forest School of Medicine, Winston Salem, NC;f 2Deptpp of Internal Medicine,

SeSeSectctctiiionnn ononon Cararardddiology, Wake Forest School ooof ff MMMedicine, Winsnsston SaSaSalllem, NC; 3Division of EEEpidemioioologygygy anddd CCComomommuuunininitytyty HHHeaeaealtltl h,,, SSSchchc ool ooof Puuublblblicicic Heaeaealtltlth,h,h, UUnininivevv rsitty y y ofofof MMinnenenesososotatata,,

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Burlington, VT

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Abstract

Background—It has recently been reported that atrial fibrillation [AF] is associated with an

increased risk of myocardial infarction [MI]. However, the mechanism underlying this

association is currently unknown. Further study of the relationship of AF with type of MI [ST

elevation MI (STEMI) vs. non-ST elevation MI [NSTEMI] might shed light on the potential

mechanisms.

Methods and Results—We examined the association between AF and incident MI in 14,462

participants [mean age 54 years, 56% women, 26% African Americans] from the Atherosclerosis

Risk in Communities study who were free of coronary heart disease at baseline [1987-1989] with

follow-up through December 31, 2010. AF cases were identified from study visits

electrocardiogram and by review of hospital discharge records. Incident MI and its types were

ascertained by an independent adjudication committee. Over a median follow up of 21.6 years,

1374 MI events occurred [829 NSTEMI, 249 STEMI, 296 unclassifiable]. In a multivariable

adjusted model, AF [n=1545] as a time-varying variable was associated with a 63% increased

risk of MI [HR (95% CI):1.63(1.32-2.02)]. However, AF was associated with NSTEMI [HR

(95% CI): 1.80(1.39-2.31)] but not STEMI [HR (95% CI): 0.49(0.18-1.34)]; p-value for hazard

ratios comparison=0.004. Combining the unclassifiable MI group with either STEMI or

NSTEMI did not change this conclusion. The association between AF and MI, total and

NSTEMI, was stronger in women than in men [interaction p-value<0.01 for both].

Conclusions—AF is associated with an increased risk of incident MI, especially in women.

However, this association is limited to NSTEMI.

Key words: atrial fibrillation, electrocardiography, epidemiology, myocardial infarction

Risk in Communities study who were free of coronary heart disease at baseline [191919878787-1-1-19898989]9]9] wwwith

follow-up through December 31, 2010. AF cases were identified from study visits

elecctrtrtrocococararardididiogogo ram m m and by review of hospital disccchahaharrrge records. Incidennnttt MIMM and its types were

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1333747474 MI evvenenents ooocccc urrrerered [822929 NNNSTTTEMEMEMI,I,I, 244949 SSTEEMMMI, 292996 unununclcllaasssisififiiabaa llle]].] IInnn aaa muuultltltiivivarriaaable

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Introduction

The significance of atrial fibrillation [AF] as a major public health problem stems from its

increasing prevalence and strong association with poor outcomes. Currently, the number of

individuals with AF in the United States is estimated as 2.7 to 6.1 million, and this is expected

to double by 2050.1-3 In addition to being an established risk factor for stroke 4, 5, a recent study

showed that AF is a risk factor for myocardial infarction [MI].6 In the Reasons for Geographic

and Racial Differences in Stroke [REGARDS] study, AF was associated with a 70% increased

risk of incident MI after adjustment for several cardiovascular risk factors and potential

confounders, and the risk was significantly higher in women than in men and in blacks than in

whites.6 These results are yet to be validated in an independent cohort, and the mechanism

explaining this association is currently unknown. Further study of the relationship of AF with

type of MI [ST elevation MI (STEMI) vs. non-ST elevation MI (NSTEMI] might shed light on

the underlying mechanisms. Thus, we examined the association between AF and MI [overall and

by type] in the Atherosclerosis Risk in Communities [ARIC] Study.

Methods

Study Population

The ARIC study is a community-based population study designed to investigate the causes of

atherosclerosis and its clinical outcomes as well as variation in cardiovascular risk factors,

medical care, and disease by race and sex.7 From 1987 to 1989 [ARIC study baseline], 15,792

adults [55.2% women, 45-64 years of age] from four US communities [Washington County,

MD; suburbs of Minneapolis, MN; Jackson, MS; and Forsyth County, NC] were enrolled and

underwent a home interview and clinic visit. Additional exams were conducted in 1990–1992,

whites.6 These results are yet to be validated in an independent cohort, and the memeechchchanananisisism mm n

explaining this association is currently unknown. Further study of the relationship of AF with

ypeee ooof f f MIMIMI [[[STSS eeelelelevav tion MI (STEMI) vs. non-STSTST eeelevation MI (NSTEMEMEMI] might shed light on

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byyy typypype] in thththee AAtA hheh roooscccleroossis sss RiR sksksk in n n CCoC mmmmmmunu ittieees [A[AARRRICCC] SSStutuudyyy.




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1993–1995, 1996–1998, and 2011–2013. Participants were mostly white in the Washington

County and Minneapolis sites, exclusively African American in Jackson, and a mix of both in

Forsyth County.

For the purpose of this study, we excluded participants with missing or poor quality

baseline electrocardiograms [ECG] [n=242], missing data on baseline covariates [n=241], race

other than white or black as well as non-white in the Minneapolis and Washington County sites

[n=103], and those with prevalent coronary heart disease [history of MI, baseline ECG-evidence

of MI, or history of coronary bypass or angioplasty] [n=744]. After all exclusions, 14,462

participants remained and were included in this analysis. The ARIC study was approved by the

institutional review boards at each participating center, and written informed consent was

obtained from all participants.

Ascertainment of AF

AF cases were identified from study visit ECGs and by review of hospital discharge records.8,9

At each study exam, a standard supine 12-lead resting ECG was recorded with a MAC PC

Personal Cardiograph [Marquette Electronics, Milwaukee, Wisconsin, USA] and transmitted to

the ARIC ECG Reading Center [EPICARE Center, Wake Forest School of Medicine, Winston

Salem, NC] for automatic coding. A cardiologist visually confirmed all AF cases automatically

detected from the study ECG. Information on hospitalizations during follow-up was obtained

from annual follow-up calls and surveillance of local hospitals, with hospital discharge diagnoses

codes collected by trained abstractors. AF during follow-up was defined as International

Classification of Disease 9th revision, Clinical Modification [ICD-9-CM] 427.31 or 427.32

diagnosis codes. AF cases detected in the same hospitalization with open cardiac surgery were

not included in the AF cases. Hospital diagnosis codes for AF ascertainment have been shown to

nstitutional review boards at each participating center, and written informed consssenenent tt wawawasss

obtained from all participants.

Asceceertrtrtaiaiainmnmnmenee t ofofof AF

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have good positive predictive value reaching 98.6%.8, 10, 11

Ascertainment of MI events

MI events were identified by contacting participants annually, identifying hospitalizations during

the previous year, and by review of all discharge records from all hospitals serving the four

ARIC field centers.12 Trained ARIC staff members abstracted medical records for all

hospitalizations. Information obtained from medical records included presence of chest pain,

history of MI or other cardiovascular-related conditions, and measures of cardiac biomarkers

[total creatinine phosphokinase (CK), CK-MB, lactate dehydrogenase, and troponin]. Elevated

cardiac enzymes were considered abnormal if the values are at least twice the upper limits of

normal, while considered equivocal if they are between the upper limit of normal and twice that

limit. Copies of up to three ECGs were obtained and sent to the University of Minnesota

Electrocardiographic Reading Center [Minneapolis, MN] for classification according to the

Minnesota code.13 A standardized computerized algorithm was applied to data on chest pain,

cardiac biomarkers, and ECG evidence to determine each participant’s computer-based MI

diagnosis.14 Cases with disagreements between the computer-based diagnosis and discharge

diagnosis codes were reviewed by physicians of the ARIC Mortality and Morbidity

Classification Committee for final classification. All eligible hospitalized events were classified

as definite, probable, possible or not present. Definite or probable MI defined MI event in our

analysis. The diagnosis of definite MI was made if one or more of the following criteria were

met: 1) Evolving diagnostic ECG pattern; 2) Diagnostic ECG pattern plus abnormal enzymes; or

3) Cardiac pain and abnormal enzymes plus evolving ST-T pattern or equivocal ECG pattern.

On the other hand, the diagnosis of probable MI must meet one or more of the following criteria

in the absence of sufficient evidence for definite MI: 1) Cardiac pain and abnormal enzymes; 2)

normal, while considered equivocal if they are between the upper limit of normal l l ananand dd twtwtwiciciceee thththaaat f

imit. Copies of up to three ECGs were obtained and sent to the University of Minnesota

Eleccctrtrtrocococararardididiogoo raaaphphphic Reading Center [Minneapooolililis,s,, MN] for classificatattioioion according to the

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6

Cardiac pain and equivocal enzymes plus either evolving ST-T pattern or diagnostic ECG

pattern; or 3) Abnormal enzymes and evolving ST-T pattern. MI events were further classified as

NSTEMI or STEMI on the basis of the coded ECGs. MI events with missing or equivocal ECGs

were considered as unclassifiable. For fatal MI events, documentation of MI was based on

information obtained from the next of kin and other informants including the certifying

physician, coroner, or medical examiner, or from medical records for any eligible hospitalization

within 28 days before death. Detailed definition of on MI ascertainment in ARIC including

details on the definitions of different ECG patterns involved in the diagnosis as well as the cut-

points for cardiac enzymes could be found at the publically available manual of operation of

surveillance components procedures in ARIC.15

In this analysis, incident MI event was defined as first occurrence of a fatal or non-fatal

MI in a participant without evidence of prior MI. Follow-up time was stopped at the time of MI

occurrence. Therefore, AF events occurring after MI incidence were not included, and those MI

events were assigned to the non-AF follow-up.

Covariates

Baseline age, sex, race, education level, income and smoking status were determined by self-

report. Body mass index [BMI] at baseline was calculated as weight [in kilograms] divided by

height [in meters] squared. Blood samples were obtained after an 8-hour fasting period. Diabetes

was defined as a fasting glucose level 126 mg/dL [or non-fasting glucose 200 mg/dL], a self-

reported physician diagnosis of diabetes, or use of diabetes medications. Hypertension was

defined as systolic blood pressure 140 mmHg, diastolic blood pressure 90 mmHg, or use of

blood pressure lowering medications. Estimated glomerular filtration rate (eGFR) based on

creatinine (eGFRcreat) was calculated using the CKD Epidemiology Collaboration (CKD-EPI)

urveillance components procedures in ARIC.15

In this analysis, incident MI event was defined as first occurrence of a fatal or non-fatal

MI iinn n a a a papapartrtrticicicipaanant t t without evidence of prior MIII. . FoFoFollow-up time was stststooopped at the time of MI

oooccucucurrence. ThTherererefforrree,e AAAFFF evevevenenentststs ooocccc uuurrringg afftf er MMMI innncicicidededencncnce e wewewererere nnnooot iinclululudededed,d,d, aaandndnd ttthohohosesese MMMI

evvvenenentstt were e asaa signgngned ttto the nonnon-nn AFFF fooollooow--upupup.

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7

equation for creatinine.16 At each study visit, medication history was obtained by self-report of

medication intake during last two weeks and by reviewing medications brought by the

participants to their visit. Each medication was coded by trained and certified interviewers with

the use of a computerized medication classification system. Prevalent stroke and peripheral

arterial disease were identified by self-reported history of a previous physician diagnosis.

Prevalent heart failure was identified by the Gothenburg criteria and/or self-reported history of

heart failure medication use in the past two weeks.17

Statistical analysis

Baseline characteristics of the analysis population were tabulated by AF status. Age-adjusted

incidence rates of MI per 1000 person-years in participants with and without AF were calculated

in the entire analysis population and in sex and race subgroups. In the AF group, person-time for

the incidence rates was calculated from AF diagnosis to occurrence of MI or censoring, while in

the non-AF group, person-time was calculated from baseline, AF occurrence, MI occurrence, or

censoring. Event-free survival probability was estimated using Kaplan Meier method and

compared using log-rank test by AF status.

Cox proportional hazards regression was used to examine the association between AF as

a time-varying variable with incident MI [overall, and by MI type] in a series of models with

incremental adjustments as follows: Model 1 adjusted for age, sex, race, field center, education,

income; Model 2 adjusted for Model 1 plus baseline BMI, smoking status, total cholesterol, HDL

cholesterol, systolic blood pressure, blood pressure lowering drugs, diabetes, eGFR, heart failure,

prevalent stroke, and prevalent peripheral arterial disease; Model 3 adjusted for Model 2

covariates plus time-varying use of statins, warfarin and aspirin ascertained at ARIC

examinations. We examined the assumption of proportional hazards by computation of

ncidence rates of MI per 1000 person-years in participants with and without AF wwwererereee cacacalclclculululatatated

n the entire analysis population and in sex and race subgroups. In the AF group, person-time for

he ininincicicidededencncnce ee ratetetesss was calculated from AF diagngngnooosiss s to occurrence of MMMI or censoring, while in

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8

Schoenfeld residuals, and inspection of log( log[survival function]) curves, and they were met.

Individuals were censored at the time of MI, death or December 31, 2010, whichever occurred

earlier. We compared the association of incident AF with STEMI and NSTEMI applying the

competing risk approach proposed by Lunn and McNeil to an augmented data set. Differences in

the association were tested including an interaction term between AF incidence and MI type in a

stratified Cox model ran in this augmented data set.18

Because of the previously reported significant interaction by sex and race,6 models with

identical incremental adjustment as those described above for the main analysis were examined

in subgroups by sex and race. Additionally, we examined interaction by age, using the median

age (>55 years) at the time of enrollment as a cut-point. Interactions were tested including

multiplicative terms in the models.

In the analysis by MI type, we excluded the unclassifiable MIs. However, to examine the

effect of the unclassifiable MIs on the association between AF and type of MI, we conducted

sensitivity analyses in which we considered the unclassifiable MIs as STEMI in one set of

analysis and as NSTEMI in another set of analysis. Also, to ensure temporality (i.e. occurrence

of MI after AF), we conducted another sensitivity analysis in which we excluded participants

with an MI event occurring within a short period (within a week) after a documented AF.

Other additional analyses included: 1) Examining the association between AF and MI

[overall and by type] using Cox proportional models adjusted for variables in model 3 plus other

possible confounders [heart rate, beta blocker use, angiotensin converting enzyme inhibitors use,

interim revascularization] all included in the models as time-varying covariates; 2) Comparing

the association between AF and MI at different times of follow up; 3) Plotting the cumulative

incidence of AF from baseline [1987-1989] to the end of follow up [2010]. The results of these

age (>55 years) at the time of enrollment as a cut-point. Interactions were tested inininclclcludududinining g g

multiplicative terms in the models.

InInIn ttthehehe anaaalylylysis by MI type, we excluded thththeee unclassifiable MIs. . HoHH wever, to examine the

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9

additional analyses are provided in the Online-Only Data Supplement.

Statistical significance for all analyses was p<0.05 (two-sided). Analyses were conducted

using SAS 9.2 [SAS Institute, Cary, NC].

Results

This analysis included 14,462 participants [mean age 54 years, 56% women, 26% African

Americans] free of coronary heart disease at the time of enrollment, of whom 1,545 had AF

either at baseline (n= 31) or during follow up (n=1514) before occurrence of an MI event.

Supplemental Figure 1 shows the cumulative incidence of AF from baseline [1987-1989] to the

end of follow up [2010], and Supplemental Table 1 shows the incidence rate of AF by 5-year

time interval since baseline.

Table 1 shows the baseline characteristics of the study population at the study baseline

[1987-1989] stratified by AF status detected at baseline and follow up through 2010. Compared

with those without AF by the end of follow up, participants with AF were more likely to be

older, white, and men with higher prevalence of diabetes, hypertension, and prior cardiovascular

disease [heart failure, stroke, peripheral arterial disease] at baseline.

Over a median follow up of 21.6 [25th and 75th percentiles = 16.9 and 22.6] years, 1374

incident MI events occurred. The mean + SD time from AF diagnosis to MI in those with AF

was 4.82+4.58 [median 3.35] years. The age adjusted incidence rate of MI was almost three-fold

higher in those with AF than those without AF [event rate (95%CI): 11.60 (10.49-12.83) vs. 3.96

(3.71-4.22) per 1000 person-years respectively; incidence rate ratio (95%CI): 2.93 (2.61-3.30)].

Figure 1 shows the event (total MI) free survival curves by AF status. In subgroup analyses by

sex and race, the highest age-adjusted MI incidence rate ratios [IRR] by AF status were observed

end of follow up [2010], and Supplemental Table 1 shows the incidence rate of AAAFFF bybyby 555-y-y-yeaeaearrr

ime interval since baseline.

TaTaTablblble ee 1 ssshohohows the baseline characteristicccsss ofoo the study populatioioionnn at the study baselinef

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in women [IRR (95%CI): 3.75 (3.14-4.47)] and blacks [IRR (95%CI): 3.26 (2.57- 4.14)], which

compare to IRR (95%CI) of 2.88 (2.52-3.30) in whites and 2.27 (1.94-2.66) in men (Figure 2).

In a socio-demographic adjusted Cox proportional hazards model, AF, compared with no AF,

was associated with a 92% increase in MI risk [p<0.001]. This association remained significant

[63% increased risk, p<0.001] after further adjustment for traditional cardiovascular risk factors

and other potential confounders (Table 2). Also, the results were similar when the variables in

model 3 plus other possible confounders/mediators were used in the models as time-varying

covariates (Supplemental Table 2)

In subgroup analysis, the association between AF and risk of MI was stronger in women

than in men [interaction p<0.001; Table 2]. Quantitatively, the risk of MI associated with AF

was stronger in blacks [multivariable HR (95%CI): 2.05 (1.32-3.18)] than in whites

[multivariable HR (95%CI): 1.52 (1.19-1.94)] but the interaction p-value did not reach statistical

significance [p=0.16] (Table 2). No significant differences in the association between AF and

MI stratified by median age [55 years] were observed in Model 3 [HR (95%CI): 1.72 (1.17-2.53)

for age <55 years and 1.59 (1.23-2.06) for age > 55years; interaction p=0.51].

Of 1374 incident MIs that occurred during follow up, 249 were STEMI and 829 were

NSTEMI. There was no significant difference in the mean time from AF to STEMI [4.29+ 4.58

(median 3.75) years] and NSTEMI [5.07+ 4.56 (median 3.59) years]; p-value=0.74.

Supplemental Figure 2 and Supplemental Figure 3 show the event free survival curves by AF

status stratified by type of MI. Table 3 shows the relative HR for MI type by AF status. As

shown, AF was associated with an increased risk of NSTEMI [multivariable HR (95%CI): 1.80

(1.39-2.31)] but not STEMI [multivariable HR (95%CI): 0.49, (0.18-1.34)]; p-value for

comparison of HRs =0.004 using the Lunn-McNeil method. Similar patterns were observed in

han in men [interaction p<0.001; Table 2]. Quantitatively, the risk of MI associatatatededed wwwititith h h AFAFAF

was stronger in blacks [multivariable HR (95%CI): 2.05 (1.32-3.18)] than in whites

mululltititivavavariririababablelel HHHRRR (95%CI): 1.52 (1.19-1.94)] bbututut ttthehh interaction p-valuuueee did not reach statistical

iiignnnificance [p===000.1666]]] ((TaTaTablblbleee 222))). NNNoo o sisisignng iffficicicannnt diifffferenenencceces ss ininin ththhe ee asasassososoccciaation n n bebebetwtwtweeeeeen n AFAFAF aaandndnd

MIMIMI ssstrtrt atified d d bybb mmmede iaaan age [[[555555 yyyeaeaearrrs]] wwew reee oobbserrveed ininin MMooodededel l 333 [H[H[HR RR (9(9(95%%%CICICI):) 1.7.7.7222 (11.1117-2.53)

fofoforrr agagageee <5<5<5555 yeeyearararsss anananddd 111.595959 (((111.232323 22-2 00.06)6)6) fffooorrr agagageee >>> 555555yeeyeararars;s;s; iiintntnterereracacactititiononon ppp 00=0 55.51]1]1].




11

subgroup analysis stratified by sex and race (Table 4). Also, the results were similar when the

variables in Model 3 plus other possible confounders/mediators were used in the models as time-

varying covariates (Supplemental Table 3)

In a sensitivity analysis in which unclassifiable MIs (n= 296) were considered as either

NSTEMI or STEMI, separately, the association between AF with NSTEMI remained statistically

significant [p<0.001], and with STEMI remained non-significant [p=0.11]. Also, the magnitude

and direction of the associations between AF with STEMI and NSTEMI in the early years of

ARIC [1987-2002] were similar to the associations observed in the later years of ARIC follow

up [2003-2010]; interaction p-value by period of follow up =0.42 for STEMI and 0.44 for

NSTEMI (Supplemental Table 4).

Excluding participants [n=72] with an MI event occurring within a week after a

documented AF did not change our conclusions and only strengthened our results [multivariable

adjusted HR (95%CI): 1.74 (1.40-2.16), p<0.001 for total MI, 1.91 (1.48-2.47), p<0.001 for

NSTEMI; and 0.51 (0.18-1.38), p=0.18 for STEMI].

Discussion

In this analysis from the ARIC study, AF was associated with a significantly increased risk of

incident MI after adjustment for cardiovascular and other risk factors. The association was

stronger in women than in men. These results accord with the recently reported findings from the

REGARDS study showing that AF is a risk factor for MI.6 More importantly, however, our

results from this analysis fill knowledge gaps and address several unanswered questions

including the effect of MI type and methods of AF ascertainment on the AF and MI association.

Our results show that the association between AF and MI is limited to NSTEMI. This

NSTEMI (Supplemental Table 4).

Excluding participants [n=72] with an MI event occurring within a week after a

docuuumemementntntededed AAAF dididid d not change our conclusions ananand dd only strengthened ououour results [multivariable

adadadjuuusted HR (9(995%5%5%CIII)):): 111.7.7.744 4 (1(1(1.4.4.40-0-0-2.2.2.161616), p<<0.00 00001 fooor toootatatalll MIMIMI, 1.11 91911 (((1.1 4448--2.4447)7)7), p<p<p<0.0.0.0000111 fofoforrr

NSNSNSTETETEMI; anannd dd 0...5111 (00.18-1.3338)8)),,, p=p=p 0.00 1888 fffor SSSTTTEMMI]]].




12

finding may shed light on the underlying mechanism by which AF is linked to MI. Although

STEMI and NSTEMI have similar long-term prognosis, their pathophysiology and treatment

differ significantly.19, 20 These different treatment strategies stem from the fact that in STEMI the

culprit artery usually is occluded completely by a thrombus, whereas in NSTEMI the culprit

artery is usually patent with a non-occlusive thrombus. With that in mind and given our finding

that AF is associated with NSTEMI and not STEMI suggests that direct coronary

thromboembolization is less likely to be the primary mechanism by which AF leads to MI. This

suggestion accords with the common belief that direct coronary thromboembolization is less

common because of the anatomical obstacles that minimize the possibility of direct coronary

embolization e.g. differences between the caliber of the aorta and the coronary arteries, location

of the coronary vessels at the root of the aorta, emergence of the coronary arteries at a right

angle, and the fact that the major part of coronary filling occurs in diastole.21

The association between AF and NSTEMI also suggests that factors that lead to partial

occlusion of the coronary arteries or increased oxygen demand are more likely to explain the

observed association between AF and MI. Hence, AF-induced increase in peripheral

prothrombotic risk through systemic platelet activation, thrombin generation, endothelial

dysfunction and inflammation 22-33 are more plausible explanations for the increased risk of MI

with AF. Episodes of poorly controlled fast AF with uncontrolled ventricular response resulting

in demand infarction, referred to as type-2 MI which typically occurs without ST elevation,

could be another mechanism.

AF is an elusive rhythm that is hard to ascertain completely, especially in large

population-based studies. Moreover, different methods of AF ascertainment can lead to different

prevalence estimates.34 Despite differences in the methods of AF ascertainment, the results in our

embolization e.g. differences between the caliber of the aorta and the corof nary artrtrterererieieies,s,s, lllocococatatatioioion

of the coronary vessels at the root of the aorta, emergence of the coronary arteries at a right

anglgle,e,e, aaandndnd ttthehehe facacact t t that the major part of coronarrry y y fififilling occurs in diastototolell .21

The assosooccciaatioioion nn bebebetwtwtweeeeeennn AFAFAF andnnd NNNSTSTS EEEMII aaalsooo sususuggggggeeeststs tthahahattt fafafactcc oors thththatatat llleaeaead dd tototo pararartititialalal

occcclclcluusu ion offf tttheh cooro onnnarrry arrttteriririese ooor rr innncrrreaseseseddd oxygygygennn dddememmananand d d aaaree e momm rrre likkeeely y y to eeexpxpxplaiin the

obobobseseservrrvededed aaassssssococociaiaiatititiononon bbbetetetweeweenenen AAAFFF anananddd MIMIMI. HeHeHencncnceee, AAAFFF-ininindudducececeddd ininincrcrcreaeaeasesese iiinnn pepeperiririphphpherereralalal




13

ARIC analysis and REGARDS6 reached similar conclusions; AF is associated with increased

risk of MI with potential sex and race differences in the magnitude of association. This

consistency in results across studies provides assurance that the association between AF and MI

is not dependent on the method of AF ascertainment. Notably, the hazard ratios for MI

associated with AF were similar in both ARIC and REGARDS.

Our observation that AF is associated with increased risk of MI in women more than men

and possibly in blacks more than whites adds to the accumulating evidence of the sex and racial

differences in CVD outcomes and the potential differences in the impact of risk factors among

sexes and races. Since we adjusted for several potential confounders, it is less likely that our

observed sex and racial differences were confounded by differences in AF associated

morbidities. Future investigation should assess whether genetic background, emerging risk

factors, access to healthcare, awareness and adherence to medications contribute to sex and racial

differences. In the REGARDS study, we have previously shown that blacks and women are less

likely to be aware of having AF or to be treated with warfarin.35 The excess risk of MI coupled

with the tendency to under treat AF may magnify the risk of poor outcomes in these two groups.

Clinical and public health implications

The prevalence of AF doubles with each additional decade of life,36 and so we should expect the

prevalence of AF-associated morbidity/mortality including MI also to grow according to our

results. In an increasingly older population, such as the United States population, this may incur

a substantial burden on the healthcare system. Efforts to increase awareness and detection of AF,

especially in blacks and women, and the development of risk stratification tools to identify AF

patients who are high risk for developing MI are needed.

From the prevention perspective, our results raise the question of whether anticoagulants

observed sex and racial differences were confounded by differences in AF associiatatatededed ff

morbidities. Future investigation should assess whether genetic background, emerging risk

factorors,s, aaccccesess too hhealthcare, awareness and adheererennce to medications cconntribute to sex and racia

didiffferences. In ththe REREGAGARDRDS S ststududy,y wewwe hhhavavvee e preeviiioususslylyly sshohohownwn thhh tatat bbblllaccks anananddd wowowomememen nn ararareee lelel ssss

ikkekelylyly to be aaawwwarrer of hhhavviv ngg AAAF FF orrr tttooo bbbe treaaateeed wwitthhh wawawarrfararrinnn.rrr 35 Thehehe exxxceess ririiskss off f MMMI ccooupledeed

wiiwiththth ttthehehe tttenenendededencncncy tototo undndndererer tttrerereatatat AAAFFF mamamay mamamagngngnififify thththeee riririsksksk ooofff popopoororor ooouttutcococomememesss ininin ttthehehesesese tttwoowo gggrororouppupsss. ttt




14

could be effective in prevention of MI as they are for stroke. Results from different meta-

analyses among patients who had coronary artery disease suggest a potential reduction of MI risk

in individuals receiving warfarin.37-41 In our study, however, the risk of MI was only attenuated

by 3% after adjustment for warfarin, aspirin and statin use [i.e. HR reduced from 1.66 in model 3

to 1.63 in model 4; Table 2]. Nevertheless, the relation between these medications and outcomes

in our study should be interpreted with caution not only because they were self-reported which is

subject to recall bias but also because they were only ascertained during study visits, introducing

the potential for nonrandom misclassification. Also, whether the new generation of oral

anticoagulants could have a role or will perform better than warfarin in prevention of MI in the

setting of AF needs to be determined. The notion that AF potentiates thrombogenic risk through

endothelial dysfunction and inflammation may highlight the potential importance of other

therapeutic modalities that improve endothelial function and blunt the inflammatory response.

Strengths and limitations

Our results should be read in the context of certain limitations. Although we used two methods

for AF ascertainment, study scheduled ECG and hospital discharge ICD codes, it remains

possible that some paroxysmal/intermittent AF cases were not detected. However, this

misclassification would likely attenuate the association between AF and MI and subsequently

our results should be considered as conservative. Also, most of AF cases in our study were

detected through hospital discharge ICD codes. Thus, individuals with asymptomatic AF or those

managed in an outpatient setting were more likely to remain unidentified. Nonetheless, the

validity of hospital discharge codes for identifying incident AF in epidemiologic studies has

previously been demonstrated.8, 10, 11

The number of blacks in the ARIC study may not be sufficient to examine black/white

etting of AF needs to be determined. The notion that AF potentiates thrombogenininic c c riririsksksk ttthrhrhrououougghg

endothelial dysfunction and inflammation may highlight the potential importance of other

herrapapapeueueutititiccc momm daaalililities that improve endothelial fufufuncncnction and blunt the iiinfnfnflammatory response.

SSStreeengths and lililimmitatatatttionononsss

OuOuOur rerr sults shshshouuldldld be rereread innn ththhee cooontnn eeextt t off cececertr ainn lllimmmittatatioonons.s. AAAlttthohoouguggh weee uuusess d twtwtwo memeethoddds

fofoforrr AFAFAF aaascscscererertatatainininmemementntnt, stststuddudy scscschehehedudduleleleddd ECECECGGG anananddd hohohospspspitititalalal dddisisischchchararargegege IIICDCDCD cccodododeseses, ititit rrremememaiaiainsnsns




15

differences in the association between AF and MI. Hence, the non-significant interaction by race

may be due to lack of statistical power.

Release of cardiac enzymes could be the result of non-ischemic causes (e.g. heart

failure, myocarditis, etc.) or even non-cardiac causes (e.g. muscle trauma, rhabdomyolysis, etc.).

Also, data on the timing of revascularization or thrombolysis during hospitalization for MI were

not available to us which could have provided further insights into the unclassified MI cases.

This could lead to misclassification of some cases of STEMI and non-STEMI. Nevertheless, as

part of the standard procedures of MI ascertainment in ARIC,15 information on non-ischemic or

non-cardiac causes for elevated cardiac enzymes during hospital admission for an MI is routinely

abstracted from the discharge summary on the ARIC participants. This information is considered

in the interpretation of the cardiac enzymes as part of the MI diagnosis. Therefore, it is unlikely

that non-cardiac causes of elevated cardiac enzymes have resulted in significant misclassification

of MI.

On a related note, the growing use of highly sensitive troponin in recent years has led

to an increase in the rates of detection of MI compared to before. This raises the possibility of

differences in the association between AF with MI in the early years compared to the later years

of ARIC follow up. However, changes in the ability to diagnose MI over time would be more

relevant for the study of trends, which requires assessment of absolute incidence rates of MI over

time. In our case, this is less important unless we think that the changes in sensitivity to identify

MI are going to be different in those with vs those without AF, which is unlikely, as supported

by our results of the association between AF and MI at different periods of follow up

(Supplemental Table 4)

Finally, similar to other studies, residual confounding and misclassification of the

abstracted from the discharge summary on the ARIC participants. This informationonon iiisss cococonsnsnsidididererered

n the interpretation of the cardiac enzymes as part of the MI diagnosis. Therefore, it is unlikely

hatt nnnononon-c-c-cararardidd ac caaauses of elevated cardiac enzyyymememess s have resulted in sigigigninn ficant misclassification

oofof MMMI.

On n n aaa reeelaaated nooote, thtthe ee grgg owowowinnng usu e e e off higgghhhly seeensiititivvve ee trtrropopoponono innn iin rrereccecent yyyeeaears haaas ledeed

ooo aaannn ininincrcrcreaeaeasesese iiinnn thththeee rararatetetesss ofofof dddetetetececectititiononon ooofff MIMIMI cccomomompapaparerereddd tototo bbbefefeforororeee. TTThihihisss rararaisisiseseses ttthehehe pppososossisisibibibilililitytty ooofff




16

outcome always remain a possibility. For example, we could not adjust for left ventricular

ejection fraction or valvular heart disease, which could confound our results. Nevertheless, we

adjusted for heart failure, minimizing the concern of confounding by left ventricular function.

Also events triggering AF or the follow-up of AF patients may further confound or increase the

suspicion for MI diagnosis, which could also lead to an association of AF with MI.

Despite these limitations, our study, with its robust methodology, provides further

evidence for a link between AF and MI and highlights the role of MI type in this association.

Key strengths of our study include a large community-based cohort, long-term follow up,

substantial number of MI events identified by rigorous physician adjudication, and the ability to

use AF as time-updated variable.

Conclusions

AF was associated with an increased risk of incident MI in the ARIC study. This association

differed by MI type; AF was associated with an increased risk of NSTEMI but not STEMI. Sex

differences in the association between AF and MI were also observed, with a stronger risk of MI

associated with AF in women compared to men. While it is currently unknown whether AF

prevention or use of anticoagulants will reduce MI risk, our findings extend AF complications

beyond stroke and total mortality to include MI.

Acknowledgments: The authors thank the staff and participants of the ARIC study for their

important contributions.

Funding Sources: The Atherosclerosis Risk in Communities Study is carried out as a

collaborative study supported by National Heart, Lung, and Blood Institute (NHLBI) contracts

(HHSN268201100005C, HHSN268201100006C, HHSN268201100007C,

use AF as time-updated variable.

Concncnclululusisisionononsss

AAAF was associaaatetetedd wiwiwiththth aaannn ininincrcrcreaeaasesesed d d riririskk of f f innncideennnt MMMI I I iinin thehh AAARIRIRICCC stststuddy. TTThihihis s asasassoss ciciciatattioioionnn

diiifffff ererered by y MIMM typypype; AAAFFF wass s asasassos ciciciataa ededd wwwitthhh aaan inncrreaaaseeed rrriiiskkk ofoff NNNSTSTS EMEEMI bububut tt not t STSTSTEMMMI. Sexx

dididifffffferererenenencececesss ininin ttthehehe aaassssssococociaiaiatititiononon bbbetetetweeweenenen AAAFFF anananddd MIMIMI weewererere aaalslslsooo obobobseseservrrvededed, wiiwiththth aaa stststrororongngngererer rrrisisiskkk ofofof MMMIII I




17

HHSN268201100008C, HHSN268201100009C, HHSN268201100010C,

HHSN268201100011C, and HHSN268201100012C). This study was additionally funded by

grant 09SDG2280087 from the American Heart Association.

Conflict of Interest Disclosures: None

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23. Lim HS, Willoughby SR, Schultz C, Gan C, Alasady M, Lau DH, Leong DP, Brooks AG, Young GD, Kistler PM, Kalman JM, Worthley MI, Sanders P. Effect of atrial fibrillation on atrial thrombogenesis in humans: Impact of rate and rhythm. J Am Coll Cardiol. 2013;61:852-860. 24. Mondillo S, Sabatini L, Agricola E, Ammaturo T, Guerrini F, Barbati R, Pastore M, Fineschi D, Nami R. Correlation between left atrial size, prothrombotic state and markers of endothelial dysfunction in patients with lone chronic nonrheumatic atrial fibrillation. Int J Cardiol. 2000;75:227-232. 25. Lip GY, Lowe GD, Rumley A, Dunn FG. Increased markers of thrombogenesis in chronic atrial fibrillation: effects of warfarin treatment. Br Heart J. 1995;73:527-533. 26. Willoughby SR, Roberts-Thomson RL, Lim HS, Lim HS, Schultz C, Prabhu A, De Sciscio P, Wong CX, Worthley MI, Sanders P. Atrial platelet reactivity in patients with atrial fibrillation. Heart Rhythm. 2010;7:1178-1183. 27. Watson T, Shantsila E, Lip GYH. Mechanisms of thrombogenesis in atrial fibrillation: Virchow’s triad revisited. Lancet. 2009;373:155-166. 28. Frustaci A, Chimenti C, Bellocci F, Morgante E, Russo MA, Maseri A. Histological substrate of atrial biopsies in patients with lone atrial fibrillation. Circulation. 1997;96:1180–1184. 29. Fukuchi M, Watanabe J, Kumagai K, Morgante E, Russo MA, Maseri A. Increased von Willebrand factor in the endocardium as a local predisposing factor for thrombogenesis in overloaded human atrial appendage. J Am Coll Cardiol. 2001;37:1436-1442. 30. Matsue Y, Suzuki M, Abe M, Katori Y, Baba S, Fukuda K, Yagi T, Iguchi A, Yokoyama H, Miura M, Kagaya Y, Sato S, Tabayashi K, Shirato K. Endothelial dysfunction in paroxysmal atrial fibrillation as a prothrombotic state: comparison with permanent/persistent atrial fibrillation. J Atheroscler Thromb. 2010;18:298-304.

atrial thrombogenesis in humans: Impact of rate and rhythm. J Am Coll Cardiol. 20133;61:852860.

24. Mondillo S, Sabatini L, Agricola E, Ammaturo T, Guerrini F, Barbati R, Pastore M, FineschiD, Nami R. Correlation between left atrial size, prothrombotic state and markers of endothelial dysfffunununctctctioioionnn inini patatatieii nts with lone chronic nonrheeeumumumatic atrial fibrillationonon. Int J Cardiol.2000000000;75:2227-7-7-232.

2522 . Lip GY, Lowewe GDDD, Rummmleeey A, Duuunnn FGGG. Incrreaased d d mamamarkkkerss oof thromoomboooggeenesiiiss s iinin cchrrronic fatttririr alalal fibrillatatatioii n:n eeeffeccctsss of wwwarararfaf riiin nn trrreaeaeatmeeenttt. Brrr HHHeaaartrtrt J. 199999955;77373:5:552777--53333.

262626. WiWiWillllllouooughghghbybby SSSRRR, RRRobobobererertststs TT-Thohohomsmsmsononon RLRLRL, LiLiLimmm HSHSHS, LiLiLimmm HSHSHS, ScScSchuhhultltltz CCC, PPPrararabhbhbhu AAA, DDDeee ScScScisisisciciciooo PPPP




20

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32. Minamino T, Kitakaze M, Sato H, Asanuma H, Funaya H, Koretsune Y, Hori M. Plasma levels of nitrite/nitrate and platelet cGMP levels are decreased in patients with atrial fibrillation. Arterioscler Thromb Vasc Biol. 1997;17:3191-3195. 33. Skalidis EI, Zacharis EA, Tsetis DK, Pagonidis K, Chlouverakis G, Yarmenitis S, Hamilos M, Manios EG, Vardas PE. Endothelial cell function during atrial fibrillation and after restoration of sinus rhythm. Am J Cardiol. 2007;99:1258-1262. 34. Prineas RJ, Soliman EZ, Howard G, Howard VJ, Cushman M, Zhang ZM, Moy CS. The sensitivity of the method used to detect atrial fibrillation in population studies affects group-specific prevalence estimates: ethnic and regional distribution of atrial fibrillation in the REGARDS study. J Epidemiol. 2009;19:177-181. 35. Meschia JF, Merrill P, Soliman EZ, Howard VJ, Barrett KM, Zakai NA, Kleindorfer D, Safford M, Howard G.. Racial disparities in awareness and treatment of atrial fibrillation: the REasons for Geographic and Racial Differences in Stroke (REGARDS) study. Stroke. 2010;41:581-587. 36. Kannel WB, Benjamin EJ. Status of the epidemiology of atrial fibrillation. Med Clin North Am. 2008;92:17-40. 37. Rothberg MB, Celestin C, Fiore LD, Lawler E, Cook JR. Warfarin plus aspirin after myocardial infarction or the acute coronary syndrome: meta-analysis with estimates of risk and benefit. Ann Intern Med. 2005;143:241-250. 38. Dukes JW, Marcus GM. Atrial fibrillation begets myocardial infarction. JAMA Intern Med. 2014;74:5-7. 39. Anand SS, Yusuf S. Oral anticoagulant therapy in patients with coronary artery disease: ameta-analysis. JAMA. 1999;282:2058-2067. 40. HurlenM, Abdelnoor M, Smith P, Erikssen J, Arnesen H. Warfarin, aspirin, or both after myocardial infarction. N Engl J Med. 2002;347:969-974. 41. Carrero JJ, Evans M, Szummer K, Spaak J, Lindhagen L, Edfors R, Stenvinkel P, Jacobson SH, Jernberg T. Warfarin, kidney dysfunction, and outcomes following acute myocardial infarction in patients with atrial fibrillation. JAMA. 2014;311:919-928.

35. Meschia JF, Merrill P, Soliman EZ, Howard VJ, Barrett KM, Zakai NA, Kleindooorfr er D, dSafford M, Howard G.. Racial disparities in awareness and treatment of atrial fibrrrililillalalatititiononon::: thththeeeREasons for Geographic and Racial Differences in Stroke (REGARDS) study. Sttrororokekeke. 2010;41:581-587.

36. KaKaKannnnnnelelel WWWB, BBBene jamin EJ. Status of the epidddemememioi logy of atrial fibriiillllllataa ion. Med Clin North Ammm. 222008;92922:::17-40.

3733 . Rothberg MBBB, Celllesstin C,C,C, Fiore LD,DD, Lawwwlller EE, Cookokok JJJRRR. Waaarfffarin pllus assspirinnn afffterr rmymymyocococardial iiinfnn arrrctttion orrr the aacucucute cccoooronononara y y y sysyyndrrommeme:: mmmetataa-aaananan lylylysis s s s wwwithh eestss imimimateseses of rrisssk andnnd benefififittt. AnAnAnn n Inteteternrn MMM deded. 222005;5;5;141414333:241-1 252525000.




21

Table 1. Baseline (1987-1989) characteristics by atrial fibrillation status occurring through 2010.

Characteristic* No Atrial Fibrillation (N=12,917) Atrial Fibrillation (N= 1545) Age, years, mean, (SD) 53.7 (5.7) 56.6 (5.5) Men, % 42.7 50.1 African American, % 26.6 18.7 Education > high school, (%) 77.8 72.5 Annual income < $16,000, (%) 20.5 23.6 Body mass index, kg/m2 mean,(SD) 27.5 (5.2) 28.9 (6.0) Current smoking, % 25.8 28.0 Diabetes, % 10.6 14.3 Hypertension, % 32.1 44.2 Antihypertensive medication use, % 26.9 40.1 Systolic blood pressure, mmHg mean, (SD) 121 (19) 125 (19) Diastolic blood pressure, mmHg mean, (SD) 74 (11) 73.7 (11) Total cholesterol mg/dL mean,(SD) 215 (42) 213 (41) HDL- cholesterol mg/dl mean,(SD) 52 (17) 49 (16) Peripheral arterial disease, % 3.3 4.3 Heart failure, % 3.5 7.7 Stroke, % 1.7 1.9 Estimated glomerular filtration rate ml/min/1.73 m2 103 (16) 99 (16) Statin use, % 0.4 0.9 Warfarin use, % 0.3 1.3 Aspirin use,% 44.9 48.4 * Characteristics are measured at baseline (1987-1989) while the number of atrial fibrillation cases are from baseline and follow up (until 2010).

mass index, kg/m mean,(SD) 27.5 (5.2) 28288.9 (6.0)ent smoking, % 25.8 282828.0.0.0 etes, % 10.6 141414.3.3.3 rtension, % 32.1 44.2

hypertensive medication use, % 26.9 40.1 lic blood pressure, mmHg mean, (SD) 121 (19) 125 (19)olicc blblblooooooddd prprpresesessususure, mmmmmmHg mean, (SD) 74 (11) 73.7 (11)chchcholololesterol ggmg/d/d/dL mean,(SD) 215 (42) 213 (41)

--- chohoh lesterol mg//dlll mmm aean,(S(S(SD)D)D) 525252 (((171717) )) 4999 ((( 6616) ) ) hhheralaa arterial diseas ,ee %% 3.33 333 .4..3 faff lliluruu e, % 3.3.3 5 .7..7

e, %%% 111.777 .1.1.9 mated glomerular filtration rate ml/min/1.737 m2 103 (16) 99 (16) n use, % 0.4 0.9




22

Table 2. Association between atrial fibrillation and incident myocardial infarction [ARIC, 1987-2010].

Participants without AF Participants with AF Model 1† Model 2* Model 3 ‡Participants

(n) Events

(n) Participants

(n) Events

(n) HR

(95% CI) HR

(95% CI) HR

(95% CI)

Interaction p-value#

All population 12,917 1267 1545 107 1.92 (1.56-2.35)

1.66 (1.35-2.04)

1.63 (1.32-2.02)

N/A

Women 7399 541 771 64 3.10 (2.37-4.06)

2.54 (1.94-3.32)

2.47 (1.87-3.25)

Men 5518 726 774 43 1.21 (0.88-1.65)

1.09 (0.80-1.50)

1.08 (0.78-1.50)

<0.0001

White 9480 927 1256 84 1.76 (1.40-2.21)

1.56 (1.24-1.97)

1.52 (1.19-1.94)

Black 3437 340 289 23 2.59 (1.68-4.00)

2.02 (1.31-3.14)

2.05 (1.32-3.18)

0.16

*Model 1, adjusted for age, sex, race, study field center, education level and income † Model 2, Model 1 covariates plus, total cholesterol, HDL cholesterol, smoking status, systolic blood pressure, body mass index, diabetes, blood pressure lowering drugs, estimated glomerular filtration rate, heart failure, stroke, peripheral arterial disease. ‡Model 3, Model 2 plus time-varying use of statins, warfarin and aspirin ascertained at ARIC examinations # Interaction tested in Model 3

(2.37 4.06) (1.94 3.32) (1.8777 3.25) 5518 726 774 43 1.21

(0.88-1.65) 1.09

(0.80-1.50) 11.1.080808

(0(0(0.7778---111.505050)))e 9480 927 1256 84 1.76

(1.40-2.21) 1.56

(1.24-1.97) 1.52

(1.19-1.94) k 3437 340 289 23 2.59

(1.68-4.00) ))2.02

(11.3.. 1-11 3.14) 2.05

(1.32-3.18)

0.1

el 111, adadadjuj sted for aaagegeg , sex, race, study field center, education level and incomemm tteeel 2,,, MModel 1 cov rariai teteesss plplplusu , totototatatalll chchchololol sesesteroool,l,l, HHHDLDLDL ccchohoolelele tststeree ol, smsmsmokokoking ttstatusuu , syyystststolololicicic bbblololood ppprereressururure,e,e, bbododody yy mamm ss indndndeeex,x,x, dddiaiaiabebb tes,s,, bbblololoododod ppprer sssssuruu e ngn dddrur gs, estimated glol memm rur lar fffil rtrratata oioionn n aaratetete, , he rart t t faailii ure,ee strtt oke, perirr pherala aaarteriaiai l didd seasaa e. elee 3, MoM del 2 plus time-vavv yrying usuu e ofo sta iitins, ,, warfarin a ddnd aspss irin aaa ccscertainede at ARRICICC eeexaxaxa iiminati noo s aaactcc ooion nn tested in Mooodedd l 3




23

Table 3. Association between AF and incident STEMI and NSTEMI [ARIC, 1987-2010].

STEMI (n=249) NSTEMI (n=829) Hazard ratio (95% CI) p-value Hazard ratio (95% CI) p-value

p-value for hazard ratios comparison

Model 1* 0.49 (0.18-1.33) 0.16 2.21 (1.74-2.82) <0.0001 0.005 Model 2† 0.44 (0.16-1.20) 0.11 1.85 (1.47-2.36) <0.0001 0.004 Model 3‡ 0.49 (0.18-1.34) 0.17 1.80 (1.39-2.31) <0.0001 0.004

AF= atrial fibrillation; MI=myocardial infarction; STEMI= ST elevation MI; NSTEMI= non-ST elevation MI *Model 1, adjusted for age, sex, race, study field center, education level and income † Model 2, Model 1 covariates plus, total cholesterol, HDL cholesterol, smoking status, systolic blood pressure, body mass index, diabetes, blood pressure lowering drugs, estimated glomerular filtration rate, heart failure, stroke, peripheral arterial disease. ‡Model 3, Model 2 plus time-varying use of statins, warfarin and aspirin ascertained at ARIC examinations.

1, adjusted for age, sex, race, study field center, education level and income tl 2, Model 1 covariates plus, total cholesterol, HDL cholesterol, smoking status, systolic blood pressure, body mass index, dddiaiaiabebebetetetes,s, bbblololoododod ppprerereessss ureestimated glomerular filtration rate, heart failure, stroke, peripheral arterial disease. 3, Model 2 plus time-varying use of statins, warfarin and aspirin ascertained at ARIC examinations.




24

Table 4. Association between AF and incident STEMI and NSTEMI, stratified by race and sex [ARIC, 1987-2010].

Women (n=8170) Men (n=6292) OutcomeEvents (n) HR (95%CI)* p-value Events (n) HR (95%CI)* p-value

Interaction p-value

STEMI 90 0.29 (0.04-2.13) 0.22 159 0.53 (0.17-1.69) 0.28 0.86 NSTEMI 392 2.72 (1.98-3.74) <0.0001 437 1.21 (0.82-1.78) 0.34 0.0002

White (n=10736) Black (n=3777) OutcomeEvents (n) HR (95%CI)* p-value Events (n) HR (95%CI)* p-value

Interaction p-value

STEMI 178 0.38 (0.12-1.20) 0.10 72 0.72 (0.10-5.30) 0.74 0.68 NSTEMI 584 1.67 (1.26-2.22) 0.0004 245 2.40 (1.49-3.88) 0.0003 0.13 AF= atrial fibrillation; MI=myocardial infarction; STEMI= ST elevation MI; NSTEMI= none ST elevation MI *Adjusted for age, sex, race, study field center, education level and income total cholesterol, HDL cholesterol, smoking status, systolic blood pressure, body mass index, diabetes, blood pressure lowering drugs, estimated glomerular filtration rate, heart failure, stroke, peripheral arterial disease and time-varying use of statins, warfarin and aspirin ascertained at ARIC examinations.

MI 178 0.38 (0.12 1.20) 0.10 72 0.72 (0.10 5.30) 0.74 0.68 EMI 584 1.67 (1.26-2.22) 0.0004 245 2.40 (1.49-3.88) 0.000000030303 0000.13 trial fibrillation; MI=myocardial infarction; STEMI= ST elevation MI; NSTEMI= none ST elevation MI sted for age, sex, race, study field center, education level and income tott tal cholesterol, HDL cholesterol, smoking status, ysystststolo ic bbblllo dodd re, body mass index, diabetes, blood pressure lowering drugs, estimated glomerular filtration rate, heart failure, strokerr , peripheral arterial e and time-varying use of statins, warfarin and aspirin ascertained at ARIC examinations.




25

Figure Legends:

Figure 1. Unadjusted Kaplan Meier myocardial infarction free survival curves by atrial

fibrillation status. *Time to event in the AF group is the time from detection of AF not the cohort

inception.

Figure 2. Sex and race stratified age-adjusted incidence rates and incidence rate ratios of MI by

AF status. MI= Myocardial infarction, AF= Atrial fibrillation. *Age-adjusted incidence rate ratio

and incidence rates were based on the average age of the cohort (54 years). †Time to event in the

AF group is the time from detection of AF not the cohort inception. AF group is the time from detection of AF not the cohort inception.



Figure 1 by guest on May 17, 2016http://circ.ahajournals.org/Downloaded from


Figure 2 by guest on May 17, 2016http://circ.ahajournals.org/Downloaded from


Zhang, Laura Loehr, Mary Cushman and Alvaro AlonsoElsayed Z. Soliman, Faye Lopez, Wesley T. O'Neal, Lin Y. Chen, Lindsay Bengtson, Zhu-Ming

Myocardial Infarction: The Atherosclerosis Risk in Communities (ARIC) StudyAtrial Fibrillation and Risk of ST-Segment Elevation versus Non-ST Segment Elevation

Print ISSN: 0009-7322. Online ISSN: 1524-4539 Copyright © 2015 American Heart Association, Inc. All rights reserved.

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Supplemental Material

Atrial Fibrillation and Risk of ST-Segment Elevation versus Non-ST Segment

Elevation Myocardial Infarction: The Atherosclerosis Risk in Communities

(ARIC) Study

Supplemental Table 1 Incidence rate of atrial fibrillation by 5-year time intervals [ARIC, 1987-2010]

Time since baseline (years)

0-<5 5-<10 10-<15 15+

Atrial fibrillation * 172 283 364 726

Participants† 14,462 13,622 12,857 11,847

Incidence rate (95% CI)

per 1000 person-years

2.46 (2.10-2.85) 4.38 (3.88-4.92) 6.27 (5.65-6.95) 10.31 (9.57-11.09)

* Number of atrial fibrillation cases occurring during the time period.

† Number of individuals alive and free of AF and MI at the beginning of the time period

Supplemental Table 2 Association between AF and incident MI [ARIC, 1987-2010]

Model A* Model B †

HR (95% CI) HR (95% CI)

All population 1.63 (1.32-2.02) 1.60 (1.30-1.97)

Women 2.47 (1.87-3.25) 2.36 (1.79-3.11)

Men 1.08 (0.78-1.50) 1.08 (0.78-1.48)

White 1.52 (1.19-1.94) 1.48 (1.17-1.88)

Black 2.05 (1.32-3.18) 1.99 (1.29-3.09)

AF= atrial fibrillation; MI=myocardial infarction

* Model A: Similar to model 3 of Table 2 which is adjusted for age, sex, race, study field center, education level and income,

plus, total cholesterol, HDL cholesterol, smoking status, systolic blood pressure, body mass index, diabetes, blood pressure

lowering drugs, estimated glomerular filtration rate, heart failure, stroke, peripheral arterial disease, plus time-varying use of

statins, warfarin and aspirin

†Model B: Adjusted for baseline age, race, sex, study field center, education and income, plus time-varying total cholesterol,

HDL cholesterol, smoking status, systolic blood pressure, body mass index, diabetes, blood pressure lowering drugs, estimated

glomerular filtration rate, heart failure, stroke, peripheral arterial disease, heart rate, interim revascularization (cardiac

procedures) and use of statins, warfarin aspirin, beta-blockers and angiotensin converting enzyme inhibitors ascertained at ARIC

examinations .

Supplemental Table 3 Association between AF and incident STEMI and NSTEMI [ARIC, 1987-2010]

STEMI(n=249) NSTEMI(n=829)

HR (95% CI) HR (95% CI)

Model A* 0.49 (0.18-1.34) 1.80 (1.39-2.31)

Model B† 0.42 (0.16-1.16) 1.74 (1.36-2.23)

AF= atrial fibrillation; MI=myocardial infarction; STEMI= ST elevation MI; NSTEMI= non-ST elevation MI

* Model A: Similar to model 3 of Table 2 which is adjusted for age, sex, race, study field center, education level and income,

plus, total cholesterol, HDL cholesterol, smoking status, systolic blood pressure, body mass index, diabetes, blood pressure

lowering drugs, estimated glomerular filtration rate, heart failure, stroke, peripheral arterial disease, plus time-varying use of

statins, warfarin and aspirin

†Model B: Adjusted for baseline age, race, sex, study field center, education and income, plus time-varying total cholesterol,

HDL cholesterol, smoking status, systolic blood pressure, body mass index, diabetes, blood pressure lowering drugs, estimated

glomerular filtration rate, heart failure, stroke, peripheral arterial disease, heart rate, interim revascularization (cardiac

procedures) and use of statins, warfarin aspirin, beta-blockers and angiotensin converting enzyme inhibitors ascertained at ARIC

examinations .

Supplemental Table 4 AF and risk of STEMI and NSTEMI during 1987-2002 vs. 2003-2010

Study Period

STEMI

(n=249)

Interaction

p-value

NSTEMI

(n=829)

Interaction

p-value

HR (95% CI)*

HR (95% CI)*

1987-2002 0.36 (0.09-1.47) 0.42 1.55 (1.03-2.34) 0.44

2003-2010 0.82(0.19-3.51) 1.92 (1.35-2.72)

AF= atrial fibrillation; MI=myocardial infarction; STEMI= ST elevation MI; NSTEMI= non-ST elevation MI

*Adjusted for age, sex, race, study field center, education level and income, plus, total cholesterol, HDL cholesterol, smoking

status, systolic blood pressure, body mass index, diabetes, blood pressure lowering drugs, estimated glomerular filtration rate,

heart failure, stroke, peripheral arterial disease, plus time-varying use of statins, warfarin and aspirin ascertained at ARIC

examinations

Supplemental Figure 1 Cumulative incidence of atrial fibrillation [ARIC, 1987-2010]

Supplemental Figure 2 Unadjusted Kaplan Meier NSTEMI free survival curves by AF status [ARIC, 1987-2010]*

Number at risk:

14,462 13,487 12,222 10,775 9,181

* Time to event in the AF group is the time from detection of AF not the cohort inception

AF= atrial fibrillation; NSTEMI= non-ST elevation myocardial infarction

0.25

0.50

0.75

1.00

Survival Probabilities

0 5 10 15 20 Time (years)

No atrial fibrillation

Atrial fibrillation

Supplemental Figure 3 Unadjusted Kaplan Meier STEMI free survival curves by AF status [ARIC, 1987-2010]*

Number at risk:

14,462 13,487 12,222 10,775 9,181

* Time to event in the AF group is the time from detection of AF not the cohort inception

AF= atrial fibrillation; STEMI= ST elevation myocardial infarction

0.90

0.95

1.00

Survival Probabilities

0 5 10 15 20 Time (years)

No atrial fibrillation

Atrial fibrillation

10 Circulation Septiembre 2015

Fibrilación auricular y riesgo de infarto de miocardio con elevación del segmento ST y sin elevación del segmento ST

El Estudio del Riesgo de Aterosclerosis en Comunidades (ARIC)

Elsayed Z. Soliman, MD, MSc, MS; Faye Lopez, MS, MPH; Wesley T. O’Neal, MD, MPH;Lin Y. Chen, MD; Lindsay Bengtson, PhD; Zhu-Ming Zhang, MD, MPH;

Laura Loehr, MD, PhD; Mary Cushman, MD, MSc; Alvaro Alonso, MD, PhD

Antecedentes—Se ha informado recientemente que la fibrilación auricular (FA) está asociada con un aumento del riesgo de infarto de miocardio (IM). Sin embargo, actualmente no se conoce el mecanismo subyacente de esta asociación. Un estudio más profundo de la relación de la FA con el tipo de IM (IM con elevación del segmento ST [STEMI, ST-segment─elevation myocardial infarction] versus IM sin elevación del segmento ST [NSTEMI, non─ST-segment─elevation myocardial in-farction]) pondría de relieve los mecanismos potenciales.

Métodos y Resultados—Examinamos la asociación entre FA e IM incidental en 14 462 participantes (edad promedio: 54 años; 56% mujeres; 26% raza negra) del estudio de Riesgo de Aterosclerosis en Comunidades [Atherosclerosis Risk in Communities (ARIC)] que estaban libres de cardiopatías coronarias a nivel basal (1987–1989) con seguimiento hasta el 31 de diciembre de 2010. Los casos de FA fueron identificados de ECG de visitas durante el estudio y mediante revisión de los registros de altas hospitalarias. Los IM incidentales y sus tipos fueron determinados por un comité de adjudicación in-dependiente. Luego de un seguimiento promedio de 21.6 años, hubo 1374 eventos de IM (829 NSTEMI, 249 STEMI, 296 IM no clasificables). En un modelo ajustado por multivariables, la FA (n = 1545) como una variable de variación temporal se asoció con un aumento del riesgo del 63% de IM (índice de riesgo: 1,63; intervalo de confianza de 95%: 1,32–2,02). Sin embargo, la FA se asoció con NSTEMI (hazard ratio: 1,80; intervalo de confianza de 95%: 1,39–2,31), pero no STEMI (hazard ratio: 0,49; intervalo de confianza de 95%: 0,18–1,34; P para comparación del hazard ratio= 0,004). Al combinar el grupo de IM no clasificable ya sea con STEMI o NSTEMI no cambió esta conclusión. La asociación entre FA e IM, total y NSTEMI, fue más fuerte en mujeres que en hombres (P para interacción < 0,01 para ambos).

Conclusiones—La FA está asociada con un aumento de riesgo de IM incidental, especialmente en mujeres. Sin embargo, esta aso-ciación está limitada a NSTEMI. (Circulation. 2015;131:1843-1850. DOI: 10.1161/CIRCULATIONAHA.114.014145.)

Palabras clave: fibrilación auricular ◼ electrocardiografía ◼ epidemiología ◼ infarto de miocardio

Recibido el 5 de noviembre de 2014; aceptado el 19 de marzo de 2015.De Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention (E.Z.S., Z.-M.Z.), Department of Internal Medicine,

Section on Cardiology (E.Z.S.), and Department of Internal Medicine (W.T.O.), Wake Forest School of Medicine, Winston Salem, NC; Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (F.L., L.B., A.A.); Cardiovascular Division, Department of Medicine, University of Minnesota Medical School, Minneapolis (L.Y.C.); Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill (L.L.); y Department of Medicine, University of Vermont, Burlington (M.C.).

El suplemento de datos de este artículo, disponible solamente online, puede consultarse en http://circ.ahajournals.org/lookup/suppl/doi:10.1161/CIRCULATIONAHA.114.014145/-/DC1.

Remitir la correspondencia a Elsayed Z. Soliman MD, MSc, MS, FAHA, FACC, Epidemiological Cardiology Research Center (EPICARE), Wake Forest School of Medicine, Medical Center Blvd, Winston Salem, NC 27157. Correo electrónico [email protected]

© 2015 American Heart Association, Inc.Circulation está disponible en http://circ.ahajournals.org

10DOI: 10.1161/CIRCULATIONAHA.114.014145

Véase la Perspectiva Clínica en la página 18

Epidemiología y prevención

La importancia de la fibrilación auricular (FA) como un significativo problema de salud pública deriva de su

creciente prevalencia y fuerte asociación con malos resulta-dos. Actualmente, la cantidad de individuos con FA en los Estados Unidos se estima en ≈2,7 a 6,1 millones, y se espera que esta cifra se duplique hacia 2050.1-3 Además de ser un factor de riesgo establecido para accidente cerebrovascular,4,5 un estudio reciente demostró que la FA es un factor de ries-go para infarto de miocardio (IM).6 En el estudio Razones para Diferencias Geográficas y Raciales en Accidente Cerebrovascular (REGARDS, Reasons for Geographic and

Racial Differences in Stroke), la FA se asoció con un aumento de riesgo del 70% de IM incidental luego de ajustar para va-rios factores de riesgo cardiovascular y factores de confusión potenciales, y el riesgo fue significativamente superior en mujeres comparadas con hombres y en raza negra comparada con raza blanca.6 Estos resultados aún deben ser validados en una cohorte independiente, y actualmente no se conoce el mecanismo que explica esta asociación. Un estudio más pro-fundo de la relación de la FA con el tipo de IM (IM con ele-

Soliman y cols FA y riesgo de IM por tipo 11

vación del segmento ST [STEMI, ST-segment─elevation MI] versus IM sin elevación del segmento ST [NSTEMI, non- ST-segment─elevation MI]) pondría de relieve los mecanismos subyacentes. Por lo tanto, examinamos la asociación entre FA e IM (en general y por tipo) en el estudio de Riesgo de Aterosclerosis en Comunidades (ARIC, Atherosclerosis Risk in Communities).

MétodosPoblación del estudioEl estudio ARIC es un estudio de poblaciones basado en las comuni-dades diseñado para investigar las causas de aterosclerosis y sus resul-tados clínicos, y asimismo la variación en factores de riesgo cardio-vascular, atención médica, y enfermedad por raza y sexo.7 Desde 1987 a 1989 (etapa basal del estudio ARIC), 15 792 adultos (55,2% muje-res; edad: 45–64 años) de 4 comunidades de los EE.UU. (Condado de Washington, Maryland; suburbios de Minneapolis, MN, y Jackson, MS; y Condado de Forsyth, Carolina del Norte) fueron inscriptos y sometidos a una entrevista en el hogar y visita clínica. Las evaluacio-nes adicionales se condujeron en 1990 a 1992, 1993 a 1995, 1996 a 1998 y 2011 a 2013. Los participantes eran en su mayoría blancos en el condado de Washington y sitios de Minneapolis, exclusivamente negros en Jackson y una mezcla de ambos en el condado de Forsyth.

A los propósitos de este estudio, excluimos participantes que no contaban con ECG basales o con ECG basales de baja calidad (n = 242), sin datos sobre las covariables basales (n = 241), de razas dife-rentes a blanca o negra y que no eran de raza blanca en los sitios de Minneapolis y el Condado de Washington (n = 103), y con cardio-patía coronaria prevalente (antecedentes de IM, evidencia en ECG basal de IM, o antecedentes de bypass coronario o angioplastia; n = 744). Luego de todas las exclusiones, quedaron 14 462 participantes y fueron incluidos en este análisis. El estudio ARIC fue aprobado por los comités de revisión institucionales de cada centro participante, y todos los participantes dieron su consentimiento por escrito.

Determinación de FALos casos de FA fueron identificados de los ECG de las visitas del estudio y mediante la revisión de los registros de altas hospitalarias.8,9 En cada examinación del estudio, se registraba un ECG en reposo de 12 derivaciones estándar en posición supina con un Cardiógrafo MAC PC Personal (Marquette Electronics, Milwaukee, WI) y se transmitía al Centro de Lecturas de ECG del ARIC (Epidemiological Cardiology Research Center, Wake Forest School of Medicine, Winston Salem, NC) para la codificación automática. Un cardiólogo confirmaba vi-sualmente todos los casos de FA automáticamente detectados de los ECG del estudio. La información sobre las hospitalizaciones durante el seguimiento fue obtenida de visitas anuales de seguimiento y su-pervisión de los hospitales locales, con códigos de diagnóstico de alta del hospital recopilados por personal capacitado. La FA durante el seguimiento fue definida como código diagnóstico de la Clasificación Internacional de la Enfermedad, 9ª Revisión, Modificación Clínica nº 427,31 o 427,32. Los casos de FA detectados en la misma hospitaliza-ción con cirugía cardíaca abierta no fueron incluidos en los casos de FA. Los códigos diagnósticos hospitalarios para determinación de FA han demostrado tener un buen valor predictivo positivo alcanzando el 98,6%.8,10,11

Determinación de eventos de IMLos eventos de IM fueron identificados contactando a los partici-pantes anualmente, identificando las hospitalizaciones durante el año previo y revisando todos los registros de altas de todos los hospitales

que respondían a los 4 centros de campos del ARIC.12 Los miembros capacitados del personal de ARIC resumieron los registros médicos de todas las hospitalizaciones. La información obtenida de los re-gistros médicos incluía presencia de dolor torácico, antecedentes de IM u otras afecciones cardiovasculares, y medidas de biomarcadores cardíacos (creatininfosfoquinasa total, creatininfosfoquinasa-MB, lactato deshidrogenasa y troponina). Las enzimas cardíacas elevadas eran consideradas anormales si los valores eran por lo menos el do-ble de los límites superiores de lo normal y consideradas equívocas si se encontraban entre el límite superior de lo normal y el doble de ese límite. Se obtuvieron copias de alrededor de 3 ECG y fueron enviadas al Centro de Lectura Electrocardiográfica de Minnesota (Minneapolis, MN) para clasificación de acuerdo con el código de Minnesota.13 Se aplicó un algoritmo computarizado estandarizado a los datos sobre el dolor torácico, biomarcadores cardíacos y eviden-cia de ECG para determinar el diagnóstico computarizado de IM de cada participante.14 Los casos con desacuerdos entre el diagnóstico computarizado y los códigos diagnósticos de altas fueron revisados por médicos del Comité de Clasificación de Morbimortalidad del ARIC para su clasificación final. Todos los eventos de hospitaliza-ción elegibles fueron clasificados como definitivos, probables, posi-bles o no presentes. El IM definitivo o probable definió los eventos de IM en nuestro análisis. El diagnóstico de IM definitivo se hacía si se cumplían ≥ 1 de los siguientes criterios: patrón de ECG diagnós-tico evolutivo, patrón de ECG diagnóstico más enzimas anormales, o dolor cardíaco y enzimas anormales más patrón de ST-T evolutivo o patrón de ECG equívoco. Por otro lado, el diagnóstico de IM pro-bable debe cumplir con ≥ 1 de los siguientes criterios en ausencia de evidencia suficiente para IM definitivo: dolor cardíaco y enzimas anormales, dolor cardíaco y enzimas equívocas más patrón de ST-T evolutivo o patrón de ECG diagnóstico, o enzimas anormales y pa-trón de ST-T evolutivo. Los eventos de IM fueron posteriormente clasificados como NSTEMI o STEMI según los ECG codificados. Los eventos de IM sin ECG o con ECG equívocos eran considerados no clasificables. Para eventos de IM fatales, la documentación de IM se basaba en la información obtenida de familiares y otros informan-tes, incluyendo el médico certificante, forense o examinador médico, o de registros médicos para cualquier hospitalización elegible dentro de los 28 días antes del fallecimiento. La definición detallada de la determinación de IM en ARIC, incluyendo detalles sobre las defini-ciones de diferentes patrones de ECG incluidos en el diagnóstico y los puntos de corte para enzimas cardíacas, pueden encontrarse en el manual públicamente disponible de operación de procedimientos de componentes de supervisión en ARIC.15

En este análisis, un evento de IM incidental era definido como la primera presentación de un IM fatal o no fatal en un participante sin evidencia de IM previo. El tiempo de seguimiento se interrumpía en el momento en que se presentaba el IM. Por lo tanto, los eventos de FA que se presentaban luego de la incidencia de IM no eran incluidos, y aquellos eventos de IM eran asignados al seguimiento de no FA.

CovariablesLa edad basal, sexo, raza, nivel educativo, ingresos y estado de taba-quismo eran determinados por los autoinformes. El índice de masa corporal basal se calculaba como peso en kilogramos dividido por la altura en metros al cuadrado. Las muestras de sangre se obtuvieron luego de un período de ayuno de 8 horas. Se definió diabetes melli-tus como un nivel de glucosa en ayunas de ≥ 126 mg/dL (o glucosa sin ayuno ≥ 200 mg/dL), un diagnóstico autoinformado del médi-co de diabetes mellitus o el uso de medicamentos para la diabetes. Hipertensión se definió como presión arterial sistólica ≥ 140 mm Hg, presión arterial diastólica ≥ 90 mm Hg o el uso de medicamentos para disminuir la presión arterial. El índice de filtración glomerular esti-


mado basado en creatinina se calculó con la ecuación para creatinina de la Colaboración de Epidemiología de Enfermedad Renal Crónica (Chronic Kidney Disease Epidemiology Collaboration).16 En cada visita del estudio, se obtenían los antecedentes de los medicamen-tos mediante el autoinforme de la ingesta de medicamentos duran-te las últimas 2 semanas y revisando los medicamentos traídos por los participantes a sus visitas. Cada medicamento era codificado por entrevistadores capacitados y matriculados con el uso de un sistema computarizado de clasificación de medicamentos. El accidente cere-brovascular y enfermedad arterial periférica prevalentes eran identifi-cados por antecedentes autoinformados de un diagnóstico previo del médico. La insuficiencia cardíaca prevalente era identificada según los criterios de Gothenburg o antecedentes autoinformados del uso de medicamentos para insuficiencia cardíaca en las últimas 2 semanas.17

Análisis estadísticoLas características basales de la población del análisis fueron tabula-das por estado de FA. Los índices de incidencia de IM ajustados por edad cada 1000 personas/años en participantes con y sin FA fueron calculados en toda la población del análisis y en subgrupos de sexos y razas. En el grupo de FA, la relación persona/tiempo para los índices de incidencia fue calculada desde el diagnóstico de FA hasta la pre-sentación del IM o censos; en el grupo no FA, la relación personas/tiempo fue calculada desde el nivel basal, presentación de FA, presen-tación de IM o censos. La probabilidad de sobrevida libre de eventos fue estimada con el método de Kaplan-Meier y comparada mediante el uso de pruebas del rango logarítmico por estado de FA.

Se usó la regresión de riesgos proporcionales de Cox para exa-minar la asociación entre FA como una variable de tiempo e IM in-cidental (general y por tipo de IM) en una serie de modelos con los siguientes ajustes incrementales: modelo 1: ajustado por edad, sexo, raza, centro de campo, educación e ingresos; modelo 2: ajustado para modelo 1 más índice de masa corporal basal, estado de tabaquismo, colesterol total, colesterol de lipoproteínas de alta densidad, presión arterial sistólica, fármacos para reducir la presión arterial, diabetes mellitus, índice de filtración glomerular estimado, insuficiencia car-díaca, accidente cerebrovascular prevalente y enfermedad arterial periférica prevalente; y modelo 3: ajustado para las covariables del modelo 2 más uso variable en tiempo de estatinas, warfarina y as-pirina determinado en las evaluaciones del ARIC. Examinamos la suposición de riesgos proporcionales mediante la computación de residuos de Schoenfeld e inspección de curvas log (−log[función de sobrevida]) y pudieron verificarse. Los individuos fueron censados al momento del IM o fallecimiento o el 31 de diciembre de 2010, lo que primero ocurriera. Comparamos la asociación de FA incidental con STEMI y NSTEMI aplicando el enfoque de riesgo competente propuesto por Lunn y McNeil18 en un grupo de datos aumentado. Las diferencias en la asociación fueron testeadas, incluyendo un término de interacción entre incidencia de FA y tipo de IM, en un modelo de Cox estratificado aplicado en este grupo de datos aumentado.

Debido a la significativa interacción previamente informada por sexo y raza,6 los modelos con ajuste incremental idénticos a aquellos descriptos anteriormente para el principal análisis fueron examinados en subgrupos por sexo y raza. Además, examinamos la interacción por edad con edad promedio (≥ 55 años) al momento de la inscripción usada como punto de corte. Se analizaron las interacciones, incluyen-do términos multiplicativos en los modelos.

En el análisis por tipo de IM, excluimos los IM no clasificables. Sin embargo, para analizar el efecto de los IM no clasificables sobre la asociación entre FA y tipo de IM, realizamos análisis de sensibilidad en los cuales consideramos los IM no clasificables como STEMI en un grupo de análisis y NSTEMI en otro grupo de análisis. Además, para garantizar temporalidad (es decir, la presentación de IM luego de

FA), realizamos otro análisis de sensibilidad en el cual excluimos par-ticipantes con un evento de IM que se presentara dentro de un corto período (una semana) después de una FA documentada.

Otros análisis adicionales incluyeron la evaluación de la asociación entre FA e IM (general y por tipo) con el uso de modelos proporcio-nales de Cox ajustados por variables en modelo 3 más otros posibles factores de confusión (frecuencia cardíaca, uso de β-bloqueantes, uso de inhibidores de la enzima convertidora de angiotensina, revascula-rización intermedia) todos incluidos en los modelos como covariables de variación temporal; la comparación de la asociación entre FA e IM en diferentes etapas del seguimiento; y graficando la incidencia acu-mulada de FA desde el nivel basal (1987–1989) hasta la finalización del seguimiento (2010). Los resultados de estos análisis adicionales se proporcionan en el Suplemento de Datos únicamente online.

El valor estadístico para todos los análisis fue P < 0,05 (bilateral). Los análisis se realizaron con SAS 9.2 (SAS Institute, Cary, NC).

ResultadosEste análisis incluyó 14 462 participantes (edad promedio: 54 años; 56% mujeres; 26% raza negra) libres de cardiopatía co-ronaria al momento de la inscripción, de los cuales 1545 pre-sentaron FA a nivel basal (n = 31) o durante el seguimiento (n = 1514) antes de la presentación de un evento de IM. La Figura I en el Suplemento de Datos online únicamente muestra la in-cidencia acumulada de FA desde el nivel basal (1987–1989) hasta la finalización del seguimiento (2010), y la Tabla I en el Suplemento de Datos online únicamente muestra el índice de incidencia de FA en un intervalo de 5 años desde el nivel basal.

La Tabla 1 muestra las características basales de la pobla-ción del estudio en el nivel basal del estudio (1987–1989) estratificadas por estado de FA detectado a nivel basal y se-guimiento durante 2010. Comparados con aquellos sin FA ha-cia la finalización del seguimiento, los participantes con FA tenían mayor probabilidad de ser mayores, blancos, y de sexo masculino con una mayor prevalencia de diabetes mellitus, hi-pertensión y enfermedad cardiovascular previa (insuficiencia cardíaca, accidente cerebrovascular, enfermedad arterial peri-férica) a nivel basal.

En un seguimiento promedio de 21.6 años (percentiles 25º y 75º, 16.9 y 22.6 años), se presentaron 1374 eventos de IM incidental. El tiempo promedio ±DE desde el diagnóstico de FA a IM en aquellos con FA fue 4.82 ± 4.58 años (promedio: 3.35 años). El índice de incidencia ajustado por edad de IM fue casi 3 veces superior en aquellos con FA que en aquellos sin FA (índice de eventos: 11,60 [intervalo de confianza de 95% (IC), 10,49–12,83] versus 3,96 [IC 95%, 3,71–4,22] cada 1000 personas/años respectivamente; proporción del índice de inci-dencia [IRR], 2,93 [IC 95%, 2,61–3,30]). La Figura 1 muestra las curvas de sobrevida libres de eventos (IM totales) por es-tado de FA. En análisis de subgrupos por sexo y raza, las IRR más altas de IM ajustadas por edad por estado de FA fueron observadas en mujeres (IRR: 3,75; IC 95%, 3,14–4,47) y de raza negra (IRR: 3,26; IC 95%, 2,57–4,14), que se comparan con una IRR de 2,88 (IC 95%, 2,52–3,30) en raza blanca y 2,27 (IC 95%, 1,94–2,66) en hombres (Figura 2).

En un modelo de riesgos proporcionales de Cox ajustado sociodemográficamente, FA comparada con no FA se asoció con un aumento en el riesgo de IM del 92% (P < 0,001). Esta


asociación se mantuvo significativa (63% de aumento de ries-go; P < 0,001) luego de un posterior ajuste para factores de riesgo cardiovasculares tradicionales y otros factores de con-fusión potenciales (Tabla 2). Los resultados fueron similares cuando las variables en modelo 3 más otros posibles factores de confusión/mediadores se usaron en los modelos como co-variables de variación temporal (Tabla II del Suplemento de Datos online únicamente).

En análisis de subgrupos, la asociación entre FA y riesgo de IM fue más fuerte en mujeres que en hombres (interacción P < 0,001; Tabla 2). Cuantitativamente, el riesgo de IM asociado con FA fue mayor en raza negra (hazard ratio multivariable [HR] 2,05; IC 95%, 1,32–3,18) que en blancos (HR multiva-riable 1,52; IC 95%, 1,19–1,94), pero el valor P de interacción no alcanzó importancia estadística (P = 0,16; Tabla 2). No se observaron diferencias significativas en la asociación entre FA e IM estratificados por edad promedio (55 años) en modelo 3 (HR 1,72 [IC 95% 1,17–2,53] para edad < 55 años y 1,59 [IC 95% 1,23–2,06] para edad > 55 años; P de interacción = 0,51).

De 1374 IM incidentales que se presentaron durante el seguimiento, 249 fueron STEMI y 829 fueron NSTEMI. No hubo diferencia significativa en el tiempo promedio desde FA a STEMI (4.29 ± 4.58 años; mediana: 3.75 años) y NSTEMI (5.07 ± 4.56 años; mediana: 3.59 años; P = 0,74). Las Figuras II y III del Suplemento de Datos online únicamente mues-tran las curvas de sobrevida libre de eventos por estado de FA estratificado por tipo de IM. La Tabla 3 muestra el HR relativo para tipo de IM por estado de FA. Como se muestra, la FA se asoció con un aumento del riesgo de NSTEMI (HR multivariable 1,80; IC 95% 1,39–2,31), pero no STEMI (HR multivariable 0,49; IC 95%, 0,18–1,34; P para comparación de HR = 0,004 con el método de Lunn-McNeil). Se observa-ron patrones similares en análisis de subgrupos estratificados por sexo y raza (Tabla 4). Los resultados fueron similares cuando las variables en modelo 3 más otros posibles factores de confusión/mediadores se usaron en los modelos como co-variables de variación temporal (Tabla III del Suplemento de Datos online únicamente).

En un análisis de sensibilidad donde los IM no clasificables (n = 296) eran considerados tanto NSTEMI como STEMI in-dependientemente, la asociación entre FA y NSTEMI se man-tuvo estadísticamente significativa (P < 0,001) y entre FA y STEMI se mantuvo no significativa (P = 0,11). Además, la magnitud y dirección de las asociaciones entre FA y STEMI y NSTEMI en los primeros años del ARIC (1987–2002) fueron similares a las observadas en los años posteriores del segui-miento del ARIC (2003–2010; P de interacción por período de seguimiento = 0,42 para STEMI y 0,44 para NSTEMI; Tabla IV del Suplemento de Datos online únicamente).

Tabla 1. Características basales (1987-1989) por estado de FA has-ta 2010

Característica* No FA(n = 12 917)

FA(n = 1545)

Edad, promedio (DE), años 53.7 (5.7) 56.6 (5.5)

Hombres, % 42,7 50,1

Raza negra, % 26,6 18,7

Educación superior a secundario, % 77,8 72,5

Ingresos anuales < $16 000, % 20,5 23,6

Índice de masa corporal, promedio (DE), kg/m2 27,5 (5,2) 28,9 (6,0)

Fumador habitual, % 25,8 28,0

Diabetes mellitus, % 10,6 14,3

Hipertensión, % 32,1 44,2

Uso de medicamentos antihipertensivos, % 26,9 40,1

Presión arterial sistólica, promedio (DE), mm Hg 121 (19) 125 (19)

Presión arterial diastólica, promedio (DE), mm Hg 74 (11) 73,7 (11)

Colesterol total, promedio (DE), mg/dL 215 (42) 213 (41)

Colesterol HDL, promedio (DE), mg/dL 52 (17) 49 (16)

Enfermedad arterial periférica, % 3,3 4,3

Insuficiencia cardíaca, % 3,5 7,7

Accidente cerebrovascular, % 1,7 1,9

Índice estimado de filtración glomerular, mL∙min−1∙1,73 m−2

103 (16) 99 (16)

Uso de estatinas, % 0,4 0,9

Uso de warfarina, % 0,3 1,3

Uso de aspirina, % 44,9 48,4

FA indica fibrilación auricular y HDL: lipoproteína de alta densidad.*Las características se miden a nivel basal (1987–1989), mien-

tras que la cantidad de casos de FA son del nivel basal y el segui-miento (hasta 2010).

Figura 1. Curvas no ajustadas de sobrevida libres de infarto de miocardio de Kaplan-Meier por estado de fibrilación auricular (FA). *El tiempo hasta el evento en el grupo FA es el tiempo desde la detección de FA, no el inicio de la cohorte.


La exclusión de participantes (n = 72) con la presentación de un evento de IM dentro de una semana posterior a una FA documentada no cambió nuestras conclusiones y sólo reforzó nuestros resultados (HR ajustado por multivariables 1,74; IC 95%, 1,40–2,16; P < 0,001 para IM total; HR ajustado por mul-tivariables 1,91; IC 95% 1,48–2,47; P < 0,001 para NSTEMI y HR ajustado por multivariables 0,51; IC 95% 0,18–1,38; P = 0,18 para STEMI).

Discusión En este análisis del estudio ARIC, la FA se asoció con un au-mento significativo del riesgo de IM incidental luego de ajus-tar por factor cardiovascular y otros factores de riesgo. La aso-ciación fue más fuerte en mujeres que en hombres. Estos resul-tados coinciden con los hallazgos recientemente informados del estudio REGARDS que muestra que la FA es un factor de riesgo para IM.6 Sin embargo, y más importante aún, nuestros resultados en este análisis cubren vacíos en el conocimiento y abordan varias preguntas no respondidas, incluso el efecto del tipo de IM y métodos de determinación de FA sobre la asocia-ción entre FA e IM.

Nuestros resultados muestran que la asociación entre FA e IM está limitada a NSTEMI. Este hallazgo pondría de relieve el mecanismo subyacente mediante el cual la FA está ligada al IM. Aunque STEMI y NSTEMI tienen pronósticos similares a largo plazo, sus fisiopatologías y tratamientos difieren sig-nificativamente.19,20 Estas diferentes estrategias de tratamiento derivan del hecho de que en STEMI la arteria en cuestión está generalmente ocluida completamente por un trombo, mientras que en NSTEMI la arteria en cuestión generalmente se evi-dencia con un trombo no oclusivo. Considerando lo expuesto, nuestro hallazgo con respecto a que la FA está asociada con NSTEMI y no STEMI sugiere que es menos probable que la tromboembolización coronaria directa sea el mecanismo prin-cipal mediante el cual la FA deriva en IM. Esta sugerencia coincide con la creencia común acerca de que la tromboem-bolización coronaria directa es menos común debido a los obstáculos anatómicos que minimizan la posibilidad de em-bolización coronaria directa, por ejemplo, diferencias entre el calibre de la aorta y las arterias coronarias, ubicación de las

venas coronarias en la raíz aórtica, emergencia de las arterias coronarias en un ángulo recto, y el hecho de que la mayor parte del llenado coronario tiene lugar en diástole.21

La asociación entre FA y NSTEMI también sugiere que es más probable que los factores que derivan en oclusión parcial de las arterias coronarias o aumento en la demanda de oxígeno expliquen la asociación observada entre FA e IM. Por lo tanto, el aumento inducido por FA en riesgo protrombótico periféri-co a través de la activación plaquetaria sistémica, generación de trombina, disfunción endotelial e inflamación22-23 es una explicación más viable para el aumento de riesgo de IM con FA. Los episodios de FA rápida mal controlados con respuesta ventricular no controlada que resultan en infartos por deman-da, denominados IM tipo 2, que generalmente se presentan sin elevación del ST, podría ser otro mecanismo.

La FA es un ritmo inaprensible que es difícil de determinar completamente, especialmente en estudios amplios basados en la población. Además, los diferentes métodos de determi-nación de FA pueden dar lugar a diferentes estimaciones de prevalencias.34 Más allá de las diferencias en los métodos de la determinación de FA, los resultados en nuestro análisis de ARIC y REGARDS6 llegaron a conclusiones similares: la FA está asociada con un aumento del riesgo de IM con diferencias de sexo y raza potenciales en la magnitud de la asociación. Esta consistencia en los resultados de los estudios reasegura que la asociación entre FA e IM no depende del método de determinación de FA. Cabe destacar que los HR para IM aso-ciado con FA fueron similares en ARIC y en REGARDS.

Nuestra observación con respecto a que la FA está asocia-da con un aumento de riesgo de IM en mujeres más que en hombres y posiblemente en raza negra más que en raza blanca se suma a la evidencia acumulada de diferencias de sexo y raciales en los resultados de la enfermedad cardiovascular y las diferencias potenciales en el impacto de factores de riesgo por sexos y razas. Debido a que ajustamos para varios facto-res de confusión potenciales, es menos probable que nuestras diferencias de sexo y raciales observadas se confundieran con diferencias en morbilidades asociadas con FA. Las futuras investigaciones deberán evaluar si los antecedentes genéti-cos, factores de riesgo emergentes, acceso a atención sanita-

Figura 2. Índices de incidencia ajustados por edad estratificados por sexo y raza y cocientes de índice de incidencia de infarto de miocardio por estado de fibrilación auricular (FA). *El cociente del índice de incidencia ajustado por edad y los índices de incidencia se basaron en la edad promedio de la cohorte (54 años). †El tiempo hasta el evento en el grupo de FA es el tiempo desde la detección de FA, no el inicio de la cohorte.


ria, conciencia y adherencia a los medicamentos contribuyen con las diferencias de sexo y raciales. En REGARDS, hemos demostrado previamente que las personas de raza negra y las mujeres presentan menos probabilidades de ser conscientes de tener FA o de ser tratadas con warfarina.35 El exceso de riesgo de IM, junto con la tendencia a no tratar la FA, magnificaría el riesgo de malos resultados en estos dos grupos.

Implicancias en la salud pública y clínicaLa prevalencia de FA se duplica con cada década adicional de vida,36 por lo tanto, de acuerdo con nuestros resultados, deberíamos esperar la prevalencia de morbimortalidad aso-ciada con FA, incluso IM, también en aumento. En una pobla-ción cada vez mayor, como la población de los EE.UU., esto implicaría una carga importante en el sistema de salud. Se necesitan iniciativas para aumentar la toma de consciencia y detección de FA, especialmente en raza negra y mujeres, y el

desarrollo de herramientas para estratificación de riesgos para identificar pacientes con FA que se encuentran en alto riesgo de desarrollar IM.

Desde el punto de vista de la prevención, nuestros resulta-dos generan la pregunta con respecto a si los anticoagulantes podrían ser efectivos en la prevención de IM de la misma ma-nera en que lo son para accidente cerebrovascular. Los resul-tados de diferentes meta-análisis en pacientes que tuvieron en-fermedad arterial coronaria sugieren una reducción potencial del riesgo de IM en individuos que reciben warfarina.37–41 En nuestro estudio, sin embargo, el riesgo de IM fue atenuado en solamente 3% luego de ajustar por uso de warfarina, aspirina y estatinas (es decir, el HR se redujo de 1,66 en el modelo 3 a 1,63 en el modelo 4; Tabla 2). No obstante, la relación entre estos medicamentos y resultados en nuestro estudio debe in-terpretarse con precaución no solamente porque fueron autoin-formados y, por lo tanto, sujetos a distorsiones de la memoria sino también porque fueron solamente determinados durante las visitas del estudio, introduciendo el potencial para clasifi-cación errónea no aleatoria. Además, es necesario determinar si la nueva generación de anticoagulantes orales podría tener una función o si serán mejores que la warfarina en la preven-ción del IM en el marco de la FA. El concepto acerca de que la FA potencia el riesgo trombogénico a través de la disfunción endotelial e inflamación destaca la importancia potencial de otras modalidades terapéuticas que mejoran la función endote-lial y debilitan la respuesta inflamatoria.

Fortalezas y limitacionesNuestros resultados deben leerse en el contexto de ciertas li-mitaciones. Si bien usamos 2 métodos para la determinación de FA, ECG programados del estudio y códigos de alta hos-pitalaria de la International Classification of Diseases, aún es posible que algunos casos de FA paroxísticos/intermitentes no se hayan detectado. Sin embargo, esta clasificación erró-nea probablemente atenuaría la asociación entre FA e IM; en consecuencia, nuestros resultados deberían considerarse como moderados. Además, la mayoría de los casos de FA en nuestro estudio fueron detectados a través de los códigos de alta hos-pitalaria de la International Classification of Diseases. Por lo

Tabla 2. Asociación entre FA e IM incidental (ARIC, 1987–2010)

Participantes sin FA Participantes con FA Modelo 1* Modelo 2† Modelo 3‡Valores P de Interacción §Participantes, n Eventos, n Participantes, n Eventos, n HR (IC 95%) HR (IC 95%) HR (IC 95%)

Toda la población 12 917 1267 1545 107 1,92 (1,56–2,35) 1,66 (1,35–2,04) 1,63 (1,32–2,02) N/A

Mujeres 7399 541 771 64 3,10 (2,37–4,06) 2,54 (1,94–3,32) 2,47 (1,87–3,25) < 0,0001

Hombres 5518 726 774 43 1,21 (0,88–1,65) 1,09 (0,80–1,50) 1,08 (0,78–1,50)

Raza blanca 9480 927 1256 84 1,76 (1,40–2,21) 1,56 (1,24–1,97) 1,52 (1,19–1,94) 0,16

Raza negra 3437 340 289 23 2,59 (1,68–4,00) 2,02 (1,31–3,14) 2,05 (1,32–3,18)

ARIC indica Riesgo de Aterosclerosis en Comunidades; FA: fibrilación auricular; HR: hazard ratio; IC: intervalo de confianza e IM: infarto de miocardio.*Modelo 1: ajustado por edad, sexo, raza, centro de campo de estudio, nivel educativo e ingresos.†Modelo 2: covariables del modelo 1 más colesterol total, colesterol de lipoproteínas de alta densidad, estado de tabaquismo, presión arterial sistólica, índice de masa

corporal, diabetes mellitus, fármacos reductores de presión arterial, índice estimado de filtración glomerular, insuficiencia cardíaca, ACV y enfermedad arterial periférica.‡Modelo 3: modelo 2 más uso de variación temporal de estatinas, warfarina y aspirina determinado en las evaluaciones de ARIC.§Interacción evaluada en modelo 3.

Tabla 3. Asociación entre FA y STEMI y NSTEMI incidental (ARIC, 1987–2010)

STEMI (n = 249) NSTEMI (n = 829) Valor P para Comparación

de HRHR (IC 95%) Valor P HR (IC 95%) Valor P

Modelo 1* 0,49(0,18–1,33)

0,16 2,21(1,74–2,82)

< 0,0001 0,005

Modelo 2† 0,44(0,16–1,20)

0,11 1,85(1,47–2,36)

< 0,0001 0,004

Modelo 3‡ 0,49(0,18–1,34)

0,17 1,80(1,39–2,31)

< 0,0001 0,004

ARIC indica Riesgo de Aterosclerosis en Comunidades; FA: fibrilación auricu-lar; HR: hazard ratio; IC: intervalo de confianza; IM: infarto de miocardio; NSTEMI: infarto de miocardio sin elevación del segmento ST y STEMI: infarto de miocardio con elevación del segmento ST.

*Modelo 1: ajustado por edad, sexo, raza, centro de campo de estudio, nivel educativo e ingresos.

†Modelo 2: covariables del modelo 1 más colesterol total, colesterol de li-poproteínas de alta densidad, estado de tabaquismo, presión arterial sistólica, índice de masa corporal, diabetes mellitus, fármacos reductores de presión arterial, índice estimado de filtración glomerular, insuficiencia cardíaca, ACV y enfermedad arterial periférica.

‡Modelo 3: modelo 2 más uso de variación temporal de estatinas, warfarina y aspirina determinado en las evaluaciones de ARIC.


Tabla 4. Asociación entre FA y STEMI y NSTEMI incidental estratificados por raza y sexo (ARIC, 1987–2010)

Mujeres(n = 8170)

Hombres (n = 6292)

Resultado Eventos, n HR (IC 95%)* Valor P Eventos, n HR (IC 95%)* Valor P Valor P

STEMI 90 0,29 (0,04–2,13) 0,22 159 0,53 (0,17–1,69) 0,28 0,86

NSTEMI 392 2,72 (1,98–3,74) < 0,0001 437 1,21 (0,82–1,78) 0,34 0,0002

Raza blanca (n = 10 736) Raza negra (n = 3777)

STEMI 178 0,38 (0,12–1,20) 0,10 72 0,72 (0,10–5,30) 0,74 0,68

NSTEMI 584 1,67 (1,26–2,22) 0,0004 245 2,40 (1,49–3,88) 0,0003 0,13

ARIC indica Riesgo de Aterosclerosis en Comunidades; FA: fibrilación auricular; HR: hazard ratio; IC: intervalo de confianza; IM: infarto de miocardio; NSTEMI: infarto de miocardio sin elevación del segmento ST y STEMI: infarto de miocardio con elevación del segmento ST.

*Ajustado por edad, sexo, raza, centro de campo de estudio, nivel educativo e ingresos, colesterol total, colesterol HDL, estado de tabaquismo, presión arterial sistólica, índice de masa corporal, diabetes mellitus, fármacos reductores de presión arterial, índice estimado de filtración glomerular, insuficiencia cardíaca, ACV y enfermedad arterial periférica y uso de variación temporal de estatinas, warfarina y aspirina determinado en las evaluaciones de ARIC.

tanto, era más probable que los individuos con FA asintomá-tica o aquellos tratados en forma ambulatoria se mantuvieran sin ser identificados. No obstante, previamente se ha demos-trado la validez de los códigos de alta hospitalaria para identi-ficar FA incidental en estudios epidemiológicos.8,10,11

La cantidad de personas de raza negra en el estudio ARIC no sería suficiente para analizar las diferencias entre raza ne-gra y blanca en la asociación entre FA e IM. Por lo tanto, la interacción no significativa por raza es atribuible a la falta de poder estadístico.

La liberación de enzimas cardíacas podría ser el resultado de causas no isquémicas (por ej., insuficiencia cardíaca, mio-carditis) o aun causas no cardíacas (por ej., trauma muscular, rabdomiólisis). Además, no pudimos contar con la disponibili-dad de los datos sobre el tiempo de revascularización o trom-bólisis durante la hospitalización para IM, lo que podría haber proporcionado una mejor comprensión de los casos de IM no clasificados. Esto podría derivar en la clasificación errónea de algunos casos de STEMI y NSTEMI. Sin embargo, como par-te de los procedimientos estándar de la determinación de IM en ARIC,15 la información sobre causas no isquémicas o no cardíacas para enzimas cardíacas elevadas durante la admisión en el hospital para IM generalmente se toma del resumen de altas de los participantes de ARIC. Esta información es consi-derada en la interpretación de las enzimas cardíacas como par-te del diagnóstico de IM. En consecuencia, es improbable que las causas no cardíacas de enzimas cardíacas elevadas hayan resultado en clasificación errónea significativa de IM.

En una nota relacionada, el uso creciente de troponina alta-mente sensible en los recientes años ha dado lugar a un aumen-to en los índices de detección de IM. Esto genera la posibilidad de diferencias en la asociación entre FA con IM en los prime-ros años comparado con los años posteriores del seguimien-to de ARIC. Sin embargo, los cambios en la capacidad para diagnosticar IM con el tiempo serían más relevantes para el estudio de tendencias, lo que requiere evaluación de índices de incidencia absoluta de IM con el tiempo. En nuestro caso, esto es menos importante a menos que pensemos que los cam-bios en sensibilidad para identificar IM van a ser diferentes en

aquellos con FA comparados con aquellos sin FA, lo que es improbable, según lo respaldan nuestros resultados de la aso-ciación entre FA e IM en diferentes períodos de seguimiento (Tabla IV del Suplemento de Datos online únicamente).

Por último, al igual que otros estudios, los factores de confusión residuales y la clasificación errónea del resultado siempre siguen siendo posibilidades. Por ejemplo, no pudimos ajustar por fracción de eyección ventricular izquierda o en-fermedad de las válvulas cardíacas, lo que podría confundir nuestros resultados. No obstante, ajustamos por insuficiencia cardíaca, minimizando el problema de confundir por función ventricular izquierda. Además, los eventos desencadenantes de FA o el seguimiento de pacientes con FA podrían confundir aún más o aumentar la sospecha de IM, lo que también podría dar lugar a una asociación de FA con IM.

Más allá de estas limitaciones, nuestro estudio, con su sóli-da metodología, proporciona evidencia para una relación entre FA e IM, y destaca la función del tipo de IM en esta asocia-ción. Las fortalezas principales de nuestro estudio incluyen una amplia cohorte basada en la comunidad, seguimiento a largo plazo, una importante cantidad de eventos de IM identificados mediante rigurosa adjudicación de los médicos, y la propiedad de usar FA como una variable actualizada con el tiempo.

ConclusionesLa FA se asoció con un aumento del riesgo de IM incidental en el estudio ARIC. Esta asociación difirió por tipo de IM: la FA estuvo asociada con un aumento del riesgo de NSTEMI, pero no STEMI. También se observaron diferencias de sexo en la asociación entre FA e IM, con un mayor riesgo de IM aso-ciado con FA en mujeres comparadas con hombres. Aunque actualmente no se sabe si la prevención de la FA o el uso de anticoagulantes reducirán el riesgo de IM, nuestros hallazgos extienden las complicaciones de la FA más allá del accidente cerebrovascular y mortalidad total para incluir el IM.

Reconocimientos Agradecemos al personal y participantes del estudio ARIC por sus importantes contribuciones.


Fuentes de financiación El Estudio ARIC se lleva a cabo como un estudio colaborativo financia-do por los contratos del National Heart, Lung, and Blood Institute HHS-N268201100005C, HSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HSN268201100010C, HHSN268201100011C y HHSN268201100012C. El presente estu-dio fue además financiado por la subvención 09SDG2280087 de la American Heart Association.

DeclaracionesNinguna.

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PERSPECTIVA CLÍNICARecientemente se ha informado que la fibrilación auricular (FA) está asociada con un aumento del riesgo de infarto de miocardio (IM). Sin embargo, actualmente no se conoce el mecanismo subyacente de esta asociación. Un estudio más profundo de la relación de la FA con el tipo de IM (IM con elevación del segmento ST [STEMI] versus IM sin elevación del segmento ST [NSTEMI]) pondría de relieve los mecanismos potenciales. En este análisis del estudio de Riesgo de Aterosclerosis en Comunidades (ARIC), demostramos que la FA está asociada con un aumento de riesgo de IM inciden-tal, confirmando informes recientes. Sin embargo, la asociación entre FA e IM estuvo limitada a IM sin elevación del segmento ST; esto sugiere que los factores que generan la oclusión parcial de las arterias coronarias o aumento de de-manda de oxígeno, pero no oclusión coronaria total por medio de tromboembolismo directo, tienen más probabilidades de explicar la asociación observada entre FA e IM.

Atrial Fibrillation and Risk of ST-Segment Elevation versus Non-ST Segment Elevation Myocardial...

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