Abstract
Atrial fibrillation (AF) frequently coexists in the setting of myocardial infarction (MI), being associated with increased mortality. Nonetheless, temporal trends in the occurrence of AF complicating MI and in the prognosis of these patients are not well described. We examined temporal trends in prevalence of AF in the setting of MI and the effect of AF on prognosis in the community. We studied a population-based sample of 20,049 validated first incident nonfatal hospitalized MIs among 35- to 74-year old residents of 4 communities in the ARIC Study from 1987 through 2009. Prevalence of AF in the setting of MI increased from 11% to 15% during the 23-year study period. The multivariable adjusted odds ratio for prevalent AF, per 5-year increment, was 1.11 (95% confidence interval [CI]: 1.04–1.19). Overall, in patients with MI, AF was associated with increased 1-year case fatality (OR 1.47, 95% CI 1.07–2.01) compared to those without AF. However, there was no evidence that the impact of AF on MI survival changed over time or differed over time by sex, race or MI classification (all p-values > 0.10). In conclusion, co-occurrence of AF in MI slightly increased between 1987 and 2009. The adverse impact of AF on survival in the setting of MI was consistent throughout. In the setting of MI, co-occurrence of AF should be viewed as a critical clinical event, and treatment needs unique to this population should be explored further.
Keywords: atrial fibrillation, myocardial infarction, treatment outcome, surveillance, survival
Despite the significant decline in the incidence rate of myocardial infarction (MI) since the end of the 20th century,1–3 the estimated annual incidence of MI in the US remains high at 525,000 cases.4 A recent systematic review and meta-analysis reported that approximately 1 in 10 MI patients had concomitant AF,5 which was associated with a significantly increased risk of death.5 However, little is known about the temporal trends related to the association of AF with prognosis of MI patients. Two studies reported a significantly higher mortality rate among MI patients who developed AF compared to those who did not, with no evidence of a clinically meaningful improvement in survival during the study period among those with coexisting AF and MI.6,7 Both studies were relatively small and lacked precision in trend analyses. Furthermore, the prior studies on prognosis of patients with co-occurring AF and MI have been conducted in predominately white communities, which is a limitation because the decline in incidence and mortality rates for MI have been slower among blacks compared to whites, especially among men,1 and blacks have a lower risk of AF compared to whites.8 Our aims were to estimate the prevalence of AF in the setting of MI over time as well as by sex, race and MI classification; to describe the impact of AF on mortality; and to assess the temporal trends in mortality among MI patients with and without concomitant AF overall and among subgroups utilizing a large community-based biracial study.
METHODS
The community surveillance component of the ARIC Study, described previously, was designed to provide knowledge about the burden of and trends in CHD morbidity and mortality in 4 US communities (details included in supplemental material).9,10
Presence of AF during the MI hospitalization was defined by the presence of AF International Classification of Diseases, 9th revision, Clinical Modification, (ICD-9-CM) hospital discharge diagnosis codes of 427.3x in any position. Validity of ICD codes for the identification of AF has been described elsewhere.11 We did not distinguish between AF that started before versus during the MI hospitalization.
All-cause mortality, at 28-days and 1-year, was determined by medical record review, state death records linkage, and linkage with the National Death Index. Deaths were classified based on the duration from date of hospital admission until date of death.
Patient characteristics, including age, sex, and race were abstracted from medical records by trained and certified study staff as were data on cardiovascular-related comorbidities, including a history of hypertension, stroke and diabetes. Prescription medications at admission, during hospitalization or at discharge and procedures were classified as yes or no. New therapies have been introduced during the study period and the impact of these therapies was estimated beginning in the year for which complete treatment information was available: ACE or angiotensin II inhibitors, 1992; Antiplatelet agents other than aspirin, 1997; and lipid-lowering agents, 1999.
Adjustment for disease severity and clinical comorbidities was performed with a modified Predicting Risk of Death in Cardiac Disease Tool (PREDICT) score.12 The PREDICT score, developed in a community-based study, utilizes information routinely collected during a hospitalization with MI, including cardiogenic shock, clinical history (cardiac events and procedures), age, severity of ECG changes, congestive HF, kidney function, and the Charlson Comorbidity Index, to determine mortality risk. Data on renal function has not always been collected in ARIC community surveillance, so a validated modification of the PREDICT score, ranging from 0 to 21, was used.13,14
Hospitalized non-fatal first incident definite and probable MIs were eligible for inclusion. Patients whose race was not white or black as well as nonwhites from the Minneapolis and Washington County field centers were excluded (n = 442) due to insufficient sample size. Patients with unknown mortality status at 28-days or 1-year (n = 342) or with incomplete covariate data (n = 91) were also excluded.
The temporal trend in prevalence of coexisting AF among MI patients was assessed with a logistic regression model using year (continuous) as the main independent variable adjusted for age (5-year groups), sex, a composite race and field center variable, number of ICD-9-CM diagnosis codes, MI classification (STEMI/NSTEMI/Unclassified) and severity (PREDICT). The impact of AF on survival overall was assessed with logistic regression models adjusted for age, sex, race, field center, MI classification, number of ICD-9-CM codes, severity (PREDICT), presentation characteristics (first systolic blood pressure and first pulse), medications, and therapeutic procedures, and within subgroups defined by sex, race, and MI classification. Trends in the association of AF with 1-year case fatality among MI patients were examined with multivariable logistic regression models. Pre-specified 2-way multiplicative interactions of trends in prevalence and mortality with sex, race, and MI classification were examined. A p<0.10 was considered evidence of effect modification.
All analyses weighted the contribution of each hospitalization by the inverse of its sampling probability to generate point, variance and 2-tailed P values that account for the sampling design. All statistical analyses were performed using survey procedures in SAS (version 9.2; SAS Institute, Inc, Cary, NC).
RESULTS
Our final analytic sample included 13,155 definite and probable first incident MIs, for a weighted sample of 20,049. Baseline patient characteristics over time, in 4-year intervals, are shown in Table 1, while Table 2 shows prevalence of medications and therapeutic procedures. The age and sex distributions of the sample were stable over the study period, with an overall mean age of 59 years at the time of hospitalization; women accounted for 36% of the sample. The prevalence of AF accompanying MI increased slightly over the 23-year study period (Table 1), although this was due primarily to a low prevalence of concomitant AF in the first few years. The proportion of MIs classified as NSTEMI increased during the study period.
Table 1.
Baseline characteristics of patients hospitalized with incident definite or probable myocardial infarction by event year groups in the Community Surveillance component of the Atherosclerosis Risk in Communities Study, 1987 – 2009
| Variable | 1987 – 1990 (n = 3330) | 1991 – 1994 (n = 3735) | 1995 – 1998 (n = 3770) | 1999 – 2002 (n = 3501) | 2003 – 2006 (n = 3215) | 2007– 2009 (n = 2499) |
|---|---|---|---|---|---|---|
| Age (years) | 59.8 | 59.9 | 59.6 | 59.0 | 58.9 | 58.8 |
| Women | 1140 (34%) | 1313 (35%) | 1380 (37%) | 1276 (36%) | 1144 (36%) | 955 (38%) |
| Community and race groups | ||||||
| Forsyth County, NC blacks | 271 (8%) | 325 (9%) | 459 (12%) | 364 (10%) | 369 (11%) | 420 (17%) |
| Forsyth County, NC whites | 966 (29%) | 1124 (30%) | 1174 (31%) | 975 (28%) | 899 (28%) | 763 (31%) |
| Jackson, MS blacks | 286 (9%) | 388 (10%) | 432 (11%) | 579 (17%) | 582 (18%) | 397 (16%) |
| Jackson, MS whites | 496 (15%) | 537 (14%) | 367 (10%) | 289 (8%) | 181 (6%) | 151 (6%) |
| Minneapolis, MN whites | 701 (21%) | 724 (19%) | 668 (18%) | 743 (21%) | 749 (23%) | 433 (17%) |
| Washington County, MD whites | 610 (18%) | 637 (17%) | 670 (18%) | 551 (16%) | 435 (14%) | 336 (13%) |
| Comorbidities | ||||||
| Hypertension | 1807 (54%) | 2138 (57%) | 2215 (59%) | 2240 (64%) | 2053 (64%) | 1855 (74%) |
| Stroke | 155 (5%) | 259 (7%) | 301 (8%) | 280 (8%) | 219 (7%) | 198 (8%) |
| Diabetes mellitus | -- | 641 (17%) | 1076 (29%) | 1043 (30%) | 1139 (35%) | 946 (38%) |
| PREDICT score* | 6.2 | 6.5 | 6.5 | 5.7 | 5.7 | 6.8 |
| Presentation characteristics | ||||||
| Hospital arrival < 2 hours† | 995 (30%) | 1113 (30%) | 1143 (30%) | 1064 (30%) | 798 (25%) | 623 (25%) |
| First systolic blood pressure (mm Hg) | 144.2 | 148.3 | 147.4 | 149.2 | 145.5 | 148.0 |
| First pulse rate (bpm) | 84.1 | 85.3 | 85.8 | 86.9 | 87.6 | 89.5 |
| Atrial fibrillation | 351 (11%) | 489 (13%) | 513 (14%) | 471 (13%) | 527 (16%) | 366 (15%) |
| Myocardial infarction classification | ||||||
| ST-elevation myocardial infarction | 793 (24%) | 1071 (29%) | 1038 (28%) | 689 (20%) | 512 (16%) | 517 (21%) |
| Non ST-elevation myocardial infarction | 2214 (66%) | 2157 (58%) | 2221 (59%) | 2373 (68%) | 2326 (72%) | 1789 (72%) |
| Unclassified | 323 (10%) | 506 (14%) | 510 (14%) | 438 (13%) | 377 (12%) | 194 (8%) |
Continuous variables presented as mean
Categorical variables presented as count (%)
History of diabetes not routinely collected until 1991
Modified PREDICT score did not include kidney function
Hospital arrival < 2 hours was determined based on duration from earliest symptom onset time to hospital arrival time
Table 2.
Medication* and therapeutic procedures during hospitalization with incident definite or probable myocardial infarction by event year groups in the Community Surveillance component of the Atherosclerosis Risk in Communities Study, 1987 – 2009
| Variable | 1987 – 1990 (n = 3330) | 1991 – 1994 (n = 3735) | 1995 – 1998 (n = 3770) | 1999 – 2002 (n = 3501) | 2003 – 2006 (n = 3215) | 2007– 2009 (n = 2499) |
|---|---|---|---|---|---|---|
| Medication | ||||||
| Aspirin | 2251 (68%) | 3233 (87%) | 3358 (89%) | 3173 (91%) | 2846 (89%) | 2280 (91%) |
| β blockers | 1549 (47%) | 2252 (60%) | 2671 (71%) | 2832 (81%) | 2796 (87%) | 2236 (89%) |
| Calcium channel blockers | 2151 (65%) | 2197 (59%) | 1497 (40%) | 852 (24%) | 702 (22%) | 634 (25%) |
| ACE or angiotensin II inhibitors | -- | 664 (18%) | 1724 (46%) | 2162 (62%) | 2115 (66%) | 1624 (65%) |
| Warfarin | 302 (9%) | 545 (15%) | 635 (17%) | 476 (14%) | 430 (13%) | 338 (14%) |
| Lipid-lowering medications | -- | -- | 248 (7%) | 2047 (58%) | 2284 (71%) | 1829 (73%) |
| Antiplatelet agents other than aspirin | -- | -- | 823 (22%) | 1992 (57%) | 2011 (63%) | 1504 (60%) |
| Procedures | ||||||
| Thrombolytic agents† | 737 (22%) | 998 (27%) | 708 (19%) | 366 (10%) | 52 (2%) | 52 (2%) |
| Percutaneous coronary intervention | 538 (16%) | 855 (23%) | 999 (27%) | 1202 (34%) | 1325 (41%) | 1020 (41%) |
| Coronary artery bypass graft | 466 (14%) | 478 (13%) | 577 (15%) | 438 (13%) | 301 (9%) | 189 (8%) |
On admission, during hospitalization, or at discharge
Thrombolytic agents include intracoronary and intravenous
The following medications were not routinely collected until the year indicated in parentheses: ACE or angiotensin II inhibitors (1992), antiplatelet agents other than aspirin (1997) and lipid-lowering agents (1999)
The prevalence of coexisting AF in the setting of MI increased over the study period. After adjustment there was no evidence that the time trend in prevalence of co-occurring AF and MI differed by sex (p for interaction = 0.43) or race (p for interaction = 0.69); however, there was evidence of a different AF time trend by MI classification (p for interaction = 0.005) (Figure 1). The prevalence of AF in patients with NSTEMI or unclassified MI (neither STEMI nor NSTEMI) increased during the study period, while among STEMI patients the prevalence of AF decreased.
Figure 1.
Three-year moving average of AF prevalence in hospitalizations with incident definite or probable myocardial infarction overall and by subtypes (ST-Elevation myocardial infarction [STEMI], non-ST-Elevation myocardial infarction [NSTEMI], and unclassified) in the Community Surveillance component of the Atherosclerosis Risk in Communities Study, 1987 – 2009
Overall, the presence (versus absence) of AF complicating MI was associated with more than a 2-fold increased odds of post-MI death at 28-days and 1-year, after adjustment for age group, sex, race, field center and year (Table 3). This association did not differ by sex, race or MI classification.
Table 3.
Odds ratios for 28-day and 1-year all-cause case fatality comparing patients with versus without atrial fibrillation in the setting of hospitalized incident definite or probable myocardial infarction in the Community Surveillance component of the Atherosclerosis Risk in Communities Study, 1987 – 2009
| Case Fatality (months) | ||
|---|---|---|
| 1 | 12 | |
|
| ||
| Variable | OR* (95% CI) | OR (95% CI) |
| Number of deaths | 204 (1.0%) | 1431 (7.1%) |
| Model 1: Age, sex, race, field center and year | 2.23 (1.13 – 4.42) | 2.15 (1.63 – 2.83) |
| Model 2: Model 1 + MI classification† and # ICD-9-CM | 2.13 (1.06 – 4.29) | 1.93 (1.45 – 2.58) |
| Model 3: Model 2 + presentation characteristicsŧ | 1.92 (0.92 – 4.02) | 1.72 (1.26 – 2.35) |
| Model 4: Model 3 + Medication§ | 2.20 (0.97 – 4.99) | 1.55 (1.12 – 2.12) |
| Model 5: Model 3 + therapeutic procedures|| | 1.71 (0.84 – 3.49) | 1.56 (1.15 – 2.12) |
| Model 6: Model 2 + presentation characteristics, medications and procedures | 2.10 (0.94 – 4.70) | 1.47 (1.07 – 2.01) |
OR = odds ratio; Comparison of co-occurring atrial fibrillation and myocardial infarction (MI) to MI
MI classification = ST-Elevation MI, non ST-Elevation MI and unclassified
Presentation characteristics = first systolic blood pressure, first pulse and the modified PREDICT score
Medications = aspirin, β blockers, Calcium channel blockers, ACE or angiotensin II inhibitors, warfarin, lipid-lowering medications and antiplatelet agents other than aspirin
Therapeutic procedures = percutaneous coronary intervention and coronary artery bypass graft
Among those with AF and MI, there was no evidence of improved 1-year survival over time (Table 4). Conversely, among those without AF, 1-year survival improved over time. There was no statistical evidence that the trend in 1-year MI survival differed for those with versus without AF (p for interaction = 0.45). The impact of AF on 1-year case fatality did not differ by sex, race or MI classification. Within strata defined by AF status as well as sex, race or MI classification, respectively, temporal trends in survival were similar; the point estimates suggested improved survival among all strata, except men with AF, over the study period. A sensitivity analysis, excluding those who had a cardiac operative procedure performed during the index hospitalization, was performed and results were consistent with the primary analysis.
Table 4.
Temporal trends in 1-year all-cause case fatality stratified by atrial fibrillation status among those hospitalized with incident definite or probable myocardial infarction in the Community Surveillance component of the Atherosclerosis Risk in Communities Study, 1987 – 2009. Results presented as odds ratios (OR)* of mortality per 5-year increment
| Atrial Fibrillation | No Atrial Fibrillation | |||||
|---|---|---|---|---|---|---|
|
| ||||||
| n / N | OR per 5-year Increment | Interaction p-value (subgroup* year) | n / N | OR per 5-year Increment | Interaction p-value (subgroup* year) | |
| Overall | 367 / 2717 | 0.86 (0.60 – 1.21) | -- | 1063 / 17332 | 0.74 (0.62 – 0.88) | -- |
| Men | 229 / 1731 | 1.05 (0.64 – 1.70) | 0.32 | 630 / 11110 | 0.72 (0.57 – 0.92) | 0.21 |
| Women | 139 / 986 | 0.71 (0.43 – 1.19) | 433 / 6222 | 0.82 (0.63 – 1.06) | ||
| Whites | 249 / 2140 | 0.98 (0.68 – 1.41) | 0.33 | 621 / 13036 | 0.84 (0.66 – 1.05) | 0.40 |
| Blacks | 119 / 577 | 0.79 (0.42 – 1.45) | 442 / 4296 | 0.63 (0.48 – 0.82) | ||
| STEMI | 45 / 391 | 0.68 (0.32 – 1.44) | 0.63 | 173 / 4228 | 0.71 (0.50 – 1.00) | 0.13 |
| NSTEMI | 245 / 1945 | 0.84 (0.57 – 1.24) | 726 / 11136 | 0.73 (0.58 – 0.90) | ||
| Unclassified | 77 / 381 | 0.68 (0.32 – 1.44) | 165 / 1968 | 0.59 (0.35 – 1.00) | ||
AF = atrial fibrillation
Overall, there was no statistical evidence that 1-year survival over time differed between those with or without AF (p for interaction = 0.45)
Adjusted for age, sex, race, field center, MI classification (STEMI/NSTEMI/Unclassified), number of ICD-9-CM codes, presentation characteristics (first systolic blood pressure, first pulse and MI severity), medications (aspirin, β blockers, Calcium channel blockers, ACE or angiotensin II inhibitors, warfarin, lipid-lowering medications and antiplatelet agents other than aspirin), and therapeutic procedures (percutaneous coronary intervention and coronary artery bypass graft
DISCUSSION
In this population-based sample of validated MI hospitalizations, the prevalence of concomitant AF in MI increased slightly from 1987 to 2009 and was approximately 15% in the most recent years. The secular trend in the prevalence of AF in the setting of MI differed by MI classification; the prevalence of coexisting AF increased over time among NSTEMI and unclassified MIs and decreased among STEMIs. Co-occurrence of AF in the setting of MI was associated with an increased risk of death and this association did not differ by sex, race or MI classification. Finally, improvements over time in 1-year survival among MI patients were greater in those without AF compared to those with AF, but this difference was not statistically significant.
The percent of patients with co-occurring AF increased over time among those with NSTEMI and unclassified MIs, while simultaneously decreasing among STEMIs. It is not surprising that AF was more common among NSTEMIs as these patients tend to be older and have more comorbidities.15–17 However, we adjusted for age group, sex, race, field center, MI classification, severity of MI and number of ICD-9-CM diagnosis codes. This is not the first study to report an increasing prevalence of AF complicating NSTEMI; in the Worcester Heart Attack Study, the adjusted OR of having AF in the setting of NSTEMI was 1.96 (95% CI: 1.38 – 2.79) in 2005 compared to 1997, while in STEMI the corresponding OR was 1.53 (95% CI: 0.97 – 2.44).2 In addition to the aging population, the prevalence of comorbidities, including known risk factors for AF, has increased over time, especially among NSTEMIs, and could be driving the trend of increasing co-occurrence of AF and NSTEMI.18 Potential explanations for the difference between STEMI and NSTEMI include changes in patient characteristics over the study period, changes in treatment strategies resulting in STEMI patients undergoing catheterization and subsequently reducing AF risk, or the impact of AF on the ECG ST segments, making it more difficult to classify an event as STEMI in the presence of AF.
Regardless of the temporal trends, AF complicating MI is consistently associated with worse survival;5–7,19,20 in a meta-analysis of 23 studies that provided multivariable adjusted analyses, the pooled mortality OR associated with AF in MI patients was 1.46 (95% CI 1.35 – 1.58).5 Our results are consistent with previous studies. Given the independent negative impact of AF on survival following MI, the occurrence of AF in MI should be viewed as a minor event relative to more severe complications like ventricular tachycardia, but should be recognized as a critical condition. To date, prognostic risk scores for MI ignore AF in determining the risk of death and therapeutic decisions.21,22 Further consideration of AF in prognostic scores is warranted, especially because prevalence of AF in the community is estimated to increase as the population ages,23,24 and because AF often complicates MI.5,20
Moreover, patients with AF complicating MI have unique treatment needs that are not fully understood. Aspirin is a cornerstone of acute MI therapy and dual antiplatelet therapy (aspirin and clopidogrel) is considered the gold standard following percutaneous coronary intervention.25 However, the combination of oral anti-coagulants and antiplatelets is associated with a high frequency of major bleeding.26 Thus, the optimal treatment strategy is unclear when the risks of thromboembolism and bleeding are considered. The introduction of new direct oral anticoagulant agents for the prevention of thromboembolic complications in AF as well as for the treatment of acute coronary syndromes raises additional questions about the optimal treatment strategy.27,28
There are several limitations of this study. The diagnosis of AF relied on ICD-9-CM hospital discharge codes and is not otherwise adjudicated. Nonetheless, this method has been found to have acceptable validity in epidemiologic studies.8,11 Temporal trends in co-occurrence of AF and MI are based on the proportion of MIs in a given time with documented AF. It is possible that the trends would change if this analysis were based on rates of co-occurrence, which would scale the results to account for changes in the size of the population. The onset of AF was unknown and we included both AF occurring before and during the MI hospitalization. However, in a prior study the occurrence of AF before or after MI was associated with an increase in mortality over no AF in MI patients.6 In our study, patients who developed AF after hospital discharge were not identified and would be misclassified. Nevertheless, there is a positive association between time from incident MI to first-detected AF and risk of death;6 consequently, our reported association likely was underestimated. Coding practices likely have changed over time. In an effort to account for these changes, analyses were adjusted for the number of ICD-9-CM codes. A previous analysis in ARIC reported greater declines over time in first myocardial infarction after accounting for trends in cardiac biomarker utilization.1 The advent of more sensitive biomarkers has particularly impacted the diagnosis of NSTEMI, with less severe cardiac events being classified as NSTEMI. However, it is unclear if the net effect would increase or decrease the co-occurrence of AF; it is possible that transient increases in cardiac biomarkers associated with rapidly conducting AF would result in a small increase in concomitant AF. It is also plausible that classification of less severe cardiac events would result in fewer events of co-occurring AF.
Supplementary Material
Acknowledgments
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, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C. This study additionally was supported by NHLBI grants RC1-HL-099452 and T32-HL-07779 (L.G.S.B) and the American Heart Association grant 09SDG2280087.
Footnotes
DISCLOSURES: None.
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References
- 1.Rosamond WD, Chambless LE, Heiss G, Mosley TH, Coresh J, Whitsel E, Wagenknecht L, Ni H, Folsom AR. Twenty-two-year trends in incidence of myocardial infarction, coronary heart disease mortality, and case fatality in 4 US communities, 1987–2008. Circulation. 2012;125:1848–1857. doi: 10.1161/CIRCULATIONAHA.111.047480. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.McManus DD, Gore J, Yarzebski J, Spencer F, Lessard D, Goldberg RJ. Recent trends in the incidence, treatment, and outcomes of patients with STEMI and NSTEMI. Am J Med. 2011;124:40–47. doi: 10.1016/j.amjmed.2010.07.023. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Roger VL, Weston SA, Gerber Y, Killian JM, Dunlay SM, Jaffe AS, Bell MR, Kors J, Yawn BP, Jacobsen SJ. Trends in incidence, severity, and outcome of hospitalized myocardial infarction. Circulation. 2010;121:863–869. doi: 10.1161/CIRCULATIONAHA.109.897249. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Go AS, Mozaffarian D, Roger VL, Benjamin EJ, Berry JD, Borden WB, Bravata DM, Dai S, Ford ES, Fox CS, Franco S, Fullerton HJ, Gillespie C, Hailpern SM, Heit JA, Howard VJ, Huffman MD, Kissela BM, Kittner SJ, Lackland DT, Lichtman JH, Lisabeth LD, Magid D, Marcus GM, Marelli A, Matchar DB, McGuire DK, Mohler ER, Moy CS, Mussolino ME, Nichol G, Paynter NP, Schreiner PJ, Sorlie PD, Stein J, Turan TN, Virani SS, Wong ND, Woo D, Turner MB. Heart disease and stroke statistics--2013 update: a report from the American Heart Association. Circulation. 2013;127:e6–e245. doi: 10.1161/CIR.0b013e31828124ad. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Jabre P, Roger VL, Murad MH, Chamberlain AM, Prokop L, Adnet F, Jouven X. Mortality associated with atrial fibrillation in patients with myocardial infarction: a systematic review and meta-analysis. Circulation. 2011;123:1587–1593. doi: 10.1161/CIRCULATIONAHA.110.986661. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Jabre P, Jouven X, Adnet F, Thabut G, Bielinski SJ, Weston SA, Roger VL. Atrial fibrillation and death after myocardial infarction: a community study. Circulation. 2011;123:2094–2100. doi: 10.1161/CIRCULATIONAHA.110.990192. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Saczynski JS, McManus D, Zhou Z, Spencer F, Yarzebski J, Lessard D, Gore JM, Goldberg RJ. Trends in atrial fibrillation complicating acute myocardial infarction. Am J Cardiol. 2009;104:169–174. doi: 10.1016/j.amjcard.2009.03.011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Alonso A, Agarwal SK, Soliman EZ, Ambrose M, Chamberlain AM, Prineas RJ, Folsom AR. Incidence of atrial fibrillation in whites and African-Americans: the Atherosclerosis Risk in Communities (ARIC) study. Am Heart J. 2009;158:111–117. doi: 10.1016/j.ahj.2009.05.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.White AD, Folsom AR, Chambless LE, Sharret AR, Yang K, Conwill D, Higgins M, Williams OD, Tyroler HA. Community surveillance of coronary heart disease in the Atherosclerosis Risk in Communities (ARIC) Study: methods and initial two years’ experience. J Clin Epidemiol. 1996;49:223–233. doi: 10.1016/0895-4356(95)00041-0. [DOI] [PubMed] [Google Scholar]
- 10.The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. The ARIC investigators. Am J Epidemiol. 1989;129:687–702. [PubMed] [Google Scholar]
- 11.Jensen PN, Johnson K, Floyd J, Heckbert SR, Carnahan R, Dublin S. A systematic review of validated methods for identifying atrial fibrillation using administrative data. Pharmacoepidemiol Drug Saf. 2012;21(Suppl 1):141–147. doi: 10.1002/pds.2317. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Jacobs DR, Jr, Kroenke C, Crow R, Deshpande M, Gu DF, Gatewood L, Blackburn H. PREDICT: A simple risk score for clinical severity and long-term prognosis after hospitalization for acute myocardial infarction or unstable angina: the Minnesota heart survey. Circulation. 1999;100:599–607. doi: 10.1161/01.cir.100.6.599. [DOI] [PubMed] [Google Scholar]
- 13.Watkins S, Thiemann D, Coresh J, Powe N, Folsom AR, Rosamond W. Fourteen-year (1987 to 2000) trends in the attack rates of, therapy for, and mortality from non-ST-elevation acute coronary syndromes in four United States communities. Am J Cardiol. 2005;96:1349–1355. doi: 10.1016/j.amjcard.2005.07.037. [DOI] [PubMed] [Google Scholar]
- 14.Singh M, Reeder GS, Jacobsen SJ, Weston S, Killian J, Roger VL. Scores for post-myocardial infarction risk stratification in the community. Circulation. 2002;106:2309–2314. doi: 10.1161/01.cir.0000036598.12888.de. [DOI] [PubMed] [Google Scholar]
- 15.Boyer NM, Laskey WK, Cox M, Hernandez AF, Peterson ED, Bhatt DL, Cannon CP, Fonarow GC. Trends in clinical, demographic, and biochemical characteristics of patients with acute myocardial infarction from 2003 to 2008: a report from the american heart association get with the guidelines coronary artery disease program. J Am Heart Assoc. 2012;1:e001206. doi: 10.1161/JAHA.112.001206. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Montalescot G, Dallongeville J, Van Belle E, Rouanet S, Baulac C, Degrandsart A, Vicaut E. STEMI and NSTEMI: are they so different? 1 year outcomes in acute myocardial infarction as defined by the ESC/ACC definition (the OPERA registry) Eur Heart J. 2007;28:1409–1417. doi: 10.1093/eurheartj/ehm031. [DOI] [PubMed] [Google Scholar]
- 17.Rogers WJ, Frederick PD, Stoehr E, Canto JG, Ornato JP, Gibson CM, Pollack CV, Jr, Gore JM, Chandra-Strobos N, Peterson ED, French WJ. Trends in presenting characteristics and hospital mortality among patients with ST elevation and non-ST elevation myocardial infarction in the National Registry of Myocardial Infarction from 1990 to 2006. Am Heart J. 2008;156:1026–1034. doi: 10.1016/j.ahj.2008.07.030. [DOI] [PubMed] [Google Scholar]
- 18.Yeh RW, Sidney S, Chandra M, Sorel M, Selby JV, Go AS. Population trends in the incidence and outcomes of acute myocardial infarction. N Engl J Med. 2010;362:2155–2165. doi: 10.1056/NEJMoa0908610. [DOI] [PubMed] [Google Scholar]
- 19.Initial National Priorities for Comparative Effectiveness Research. Washington, DC: National Academies Press; 2012. www.nap.edu/catalog/12648.html. [Google Scholar]
- 20.Schmitt J, Duray G, Gersh BJ, Hohnloser SH. Atrial fibrillation in acute myocardial infarction: a systematic review of the incidence, clinical features and prognostic implications. Eur Heart J. 2009;30:1038–1045. doi: 10.1093/eurheartj/ehn579. [DOI] [PubMed] [Google Scholar]
- 21.Antman EM, Cohen M, Bernink PJ, McCabe CH, Horacek T, Papuchis G, Mautner B, Corbalan R, Radley D, Braunwald E. The TIMI risk score for unstable angina/non-ST elevation MI: A method for prognostication and therapeutic decision making. JAMA. 2000;284:835–842. doi: 10.1001/jama.284.7.835. [DOI] [PubMed] [Google Scholar]
- 22.Eagle KA, Lim MJ, Dabbous OH, Pieper KS, Goldberg RJ, Van de Werf F, Goodman SG, Granger CB, Steg PG, Gore JM, Budaj A, Avezum A, Flather MD, Fox KA. A validated prediction model for all forms of acute coronary syndrome: estimating the risk of 6-month postdischarge death in an international registry. JAMA. 2004;291:2727–2733. doi: 10.1001/jama.291.22.2727. [DOI] [PubMed] [Google Scholar]
- 23.Go AS, Hylek EM, Phillips KA, Chang Y, Henault LE, Selby JV, Singer DE. Prevalence of diagnosed atrial fibrillation in adults: national implications for rhythm management and stroke prevention: the AnTicoagulation and Risk Factors in Atrial Fibrillation (ATRIA) Study. JAMA. 2001;285:2370–2375. doi: 10.1001/jama.285.18.2370. [DOI] [PubMed] [Google Scholar]
- 24.Miyasaka Y, Barnes ME, Gersh BJ, Cha SS, Bailey KR, Abhayaratna WP, Seward JB, Tsang TS. Secular trends in incidence of atrial fibrillation in Olmsted County, Minnesota, 1980 to 2000, and implications on the projections for future prevalence. Circulation. 2006;114:119–125. doi: 10.1161/CIRCULATIONAHA.105.595140. [DOI] [PubMed] [Google Scholar]
- 25.Steinhubl SR, Berger PB, Mann JT, 3rd, Fry ET, DeLago A, Wilmer C, Topol EJ. Early and sustained dual oral antiplatelet therapy following percutaneous coronary intervention: a randomized controlled trial. JAMA. 2002;288:2411–2420. doi: 10.1001/jama.288.19.2411. [DOI] [PubMed] [Google Scholar]
- 26.Lamberts M, Olesen JB, Ruwald MH, Hansen CM, Karasoy D, Kristensen SL, Kober L, Torp-Pedersen C, Gislason GH, Hansen ML. Bleeding after initiation of multiple antithrombotic drugs, including triple therapy, in atrial fibrillation patients following myocardial infarction and coronary intervention: a nationwide cohort study. Circulation. 2012;126:1185–1193. doi: 10.1161/CIRCULATIONAHA.112.114967. [DOI] [PubMed] [Google Scholar]
- 27.Shavadia J, Welsh RC. Acute Management of ST-Elevation Myocardial Infarction Patients Taking Dabigatran. Can J Cardiol. 2013;29:1531.e1513–1531.e1514. doi: 10.1016/j.cjca.2013.06.008. [DOI] [PubMed] [Google Scholar]
- 28.Mega JL, Braunwald E, Wiviott SD, Bassand JP, Bhatt DL, Bode C, Burton P, Cohen M, Cook-Bruns N, Fox KA, Goto S, Murphy SA, Plotnikov AN, Schneider D, Sun X, Verheugt FW, Gibson CM. Rivaroxaban in patients with a recent acute coronary syndrome. N Engl J Med. 2012;366:9–19. doi: 10.1056/NEJMoa1112277. [DOI] [PubMed] [Google Scholar]
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