Atrial fibrillation is a common complication of acute

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1 Acute Myocardial Infarction Complicated by Atrial Fibrillation in the Elderly Prevalence and Outcomes Saif S. Rathore, AB; Alan K. Berger, MD; Kevin P. Weinfurt, PhD; Kevin A. Schulman, MD, MBA; William J. Oetgen, MD, MBA; Bernard J. Gersh, MB, ChB, DPhil; Allen J. Solomon, MD Background Although atrial fibrillation (AF) is a common complication of acute myocardial infarction (MI), patient characteristics and association with outcomes remain poorly defined in the elderly. Methods and Results We evaluated Medicare beneficiaries 65 years of age from the Cooperative Cardiovascular Project treated for acute MI between January 1994 and February 1996 to determine the prevalence and prognostic significance of AF complicating acute MI in elderly patients. Patients were categorized on the basis of the presence of AF, and those with AF were further subdivided by time of AF (present on arrival versus developing during hospitalization). AF and non-af patients were compared by univariate analysis, and logistic regression modeling was used to identify clinical predictors of AF. The influence of AF on outcomes was evaluated by unadjusted Kaplan-Meier survival curves and logistic regression models. AF was documented in patients (22.1%): presented with AF and developed AF during hospitalization. AF patients were older, had more advanced heart failure, and were more likely to have had a prior MI and undergone coronary revascularization. AF patients had poorer outcomes, including higher in-hospital (25.3% versus 16.0%), 30-day (29.3% versus 19.1%), and 1-year (48.3% versus 32.7%) mortality. AF remained an independent predictor of in-hospital (odds ratio [OR], 1.21), 30-day (OR, 1.20), and 1-year (OR, 1.34) mortality after multivariate adjustment. Patients developing AF during hospitalization had a worse prognosis than patients who presented with AF. Conclusions AF is a common complication of acute MI in elderly patients and independently influences mortality, particularly when it develops during hospitalization. (Circulation. 2000;101: ) Key Words: infarction fibrillation mortality Atrial fibrillation is a common complication of acute myocardial infarction (MI), with a reported incidence as high as 20%. 1 Despite its frequent occurrence, the prognostic significance of atrial fibrillation complicating acute MI remains controversial. Although some studies have identified increased in-hospital and long-term mortality associated with atrial fibrillation, 2 5 others have found no independent effect. 1,6 9 Further complicating the issue are comorbid conditions that may be associated with survival after acute MI. It remains unclear whether atrial fibrillation is a marker for overall poorer clinical status or independently influences patient outcomes. Previous studies of atrial fibrillation have been limited by small sample sizes, 6,8,9 enrollment at a few study centers, 1,5,6,9 short follow-up periods, 6,8 and evaluation of patients from clinical trial populations. 2 4,7 Although the prevalence of atrial fibrillation is known to increase with age, 1 few studies have investigated the incidence or prognostic significance of atrial fibrillation in elderly patients with acute MI. The Cooperative Cardiovascular Project (CCP), a data set of Medicare patients hospitalized for acute MI, permits such an evaluation. Using detailed clinical data from the CCP, we sought to determine the incidence of atrial fibrillation in elderly patients with acute MI, clinical factors associated with its presentation, and its association with patient outcomes. Methods The CCP Initiated by the Health Care Financing Administration in 1992 in collaboration with peer review organizations, the CCP is an ongoing national program developed to improve the quality of care for Received July 30, 1999; revision received September 9, 1999; accepted September 23, From the Clinical Economics Research Unit (S.S.R., K.P.W., K.A.S.) and Division of Cardiology (A.K.B., B.J.G., A.J.S.), Georgetown University Medical Center, Washington, DC, and Maryland HealthCare Associates, LLC, Clinton, Md, and Delmarva Foundation for Medical Care, Incorporated, Easton, Md (W.J.O.). Dr Berger is currently with the Division of Cardiology, Yale-New Haven Medical Center, New Haven, Conn, and Dr Gersh is now with the Division of Cardiovascular Diseases and Internal Medicine, Mayo Clinic, Rochester, Minn. Correspondence to Allen J. Solomon, MD, Division of Cardiology, Room M4222, Georgetown University Medical Center, 3800 Reservoir Rd NW, Washington, DC solomona@gunet.georgetown.edu 2000 American Heart Association, Inc. Circulation is available at 969

2 970 Circulation March 7, 2000 TABLE 1. Study Cohort and CCP Sample Population Exclusions Patients Exclusion Criteria Excluded, n Total sample Exclusions* Patient age 65 y No confirmed MI on admission Readmission for MI Interhospital transfer Patient did not receive ECG or no ECG with documentation Mortality status unknown 3 Any 1 of the above exclusions Study sample *Exclusion criteria are not mutually exclusive. Medicare beneficiaries with acute MI. 10 The CCP cohort includes all Medicare beneficiaries discharged from a nonfederal short-term care hospital in the United States with a primary discharge diagnosis of acute MI (International Classification of Disease, ninth revision [ICD-9], code 410) between January 1994 and February 1996, except for acute MI readmissions (ICD-9 code 410.x2). 11 Patients were identified on the basis of hospital bills (UB-92 claims) in the Medicare National Claims History File associated with hospitalizations during a random 8-month period, which varied for each state. 12 Medical records for each sampled hospitalization were forwarded to clinical data abstraction centers. CCP data abstraction and management have been reported elsewhere 13 and include 140 predefined clinical variables associated with each hospitalization. Data were collected within the following categories: demographics; medications; patient medical histories; symptoms on arrival; diagnostic tests, including ECG examination, laboratory test results, and inhospital treatment and events; and discharge treatment and disposition. Data quality was ensured through the use of trained technicians and software abstraction modules and was monitored by random record reabstraction. Data reliability averaged 94%. 14 Study Sample We limited our analysis to patients 65 years of age presenting with confirmed acute MI. Confirmed acute MI was defined as an elevation of creatine kinase-mb level 5%, an elevation of lactate dehydrogenase enzyme (LDH) levels with isoenzyme reversal (LDH 1 LDH 2), or 2 of the following 3 criteria: chest pain during the prior 48 hours, a 2-fold elevation in creatine kinase, or diagnostic ECG changes (ST-segment elevation or new Q waves). Patients with multiple admissions during the sample period were identified, and readmissions for acute MI were excluded. Patients transferred between hospitals were excluded because we could not evaluate their full hospitalization. We excluded patients for whom ECG data were not available. Finally, we excluded 3 patients for whom we could not evaluate mortality status. All remaining patients (n ) constituted the study cohort (Table 1). Study Outcomes Our principal outcome of interest was the development of atrial fibrillation at any point during the MI hospitalization. Atrial fibrillation was defined as a diagnosis of atrial fibrillation or flutter reported on a patient s ECG if accompanied by an ECG report or physician s interpretation. Because the timing of atrial fibrillation may influence its prognostic significance, we further classified patients on the basis of when atrial fibrillation was first recognized. Patients with atrial fibrillation documented on their admission ECG (performed within 6 hours of arrival) were classified as having atrial fibrillation on arrival. This group included patients with chronic atrial fibrillation and those who developed atrial fibrillation early in their infarction. Patients who did not have atrial fibrillation on arrival but subsequently developed this arrhythmia during their hospitalization were classified as developing atrial fibrillation during hospitalization. Our second outcome of interest was mortality during hospitalization, at 30 days, and at 1 year. We examined the influence of atrial fibrillation on mortality using data obtained from the Medicare Enrollment Database. 15 We also examined the association of atrial fibrillation and in-hospital outcomes, including reinfarction, cerebrovascular accident, intensive care unit (ICU) admission, congestive heart failure, and length of hospitalization. Statistical Analyses We first sought to determine the prevalence and time of onset of atrial fibrillation during the acute MI hospitalization. Development of atrial fibrillation and time of atrial fibrillation recognition were evaluated for bivariate associations with patients demographic and clinical characteristics with 2 and t test analyses. Variables incorporated into our analysis included demographic characteristics race and sex and characteristics previously identified as predictors of acute MI mortality in the Global Utilization of Streptokinase and Tissue Plasminogen Activator for Occluded Coronary Arteries (GUSTO) trial. 16 These variables included age, systolic blood pressure on arrival, pulse rate, MI location, Killip class, height, weight, prior history of infarction, history of CABG, smoking status, current diabetes mellitus, hypertension, and cerebrovascular disease. Significant patient demographic and clinical characteristics from the bivariate analyses (P 0.05) were incorporated into a multivariable logistic regression model, with development of atrial fibrillation as the dependent variable. Variables were removed from the model by backward stepwise selection with a significance level of P In the second portion of our study, we evaluated the association of atrial fibrillation with patient outcomes, including in-hospital events and in-hospital mortality, at 30 days and 1 year by 2 and t test analysis. Kaplan-Meier plots were used to illustrate unadjusted mortality at 1 year for patients without atrial fibrillation, those presenting with atrial fibrillation, and those developing atrial fibrillation during hospitalization. Logistic regression modeling was used to identify the unadjusted risk of in-hospital mortality attributable to any atrial fibrillation, atrial fibrillation on arrival, and atrial fibrillation during hospitalization. The independent risk of in-hospital mortality attributable to atrial fibrillation, atrial fibrillation on arrival, and atrial fibrillation developing during hospitalization was then determined by addition of patient demographic and clinical characteristics to the model. Because antiarrhythmic agents may induce ventricular proarrhythmia and increase a patient s mortality risk, antiarrhythmic agents used on admission and during hospitalization were identified and incorporated into the mortality model. Logistic regression modeling was repeated to evaluate the association of atrial fibrillation and mortality at 30 days and 1 year. The 1-year mortality model was augmented to include antiarrhythmic agents prescribed on discharge, in addition to agents used on admission and during hospitalization. To maximize regression modeling, age, systolic blood pressure, and pulse rate were evaluated for their relationship with 30-day mortality to determine appropriate model fitting transformations with fractional polynomial modeling. 17 Logistic model fit was evaluated by inspection of predicted and expected frequencies, and model discrimination was assessed by the c statistic. Because of significant missing data rates for height (16.1%) and weight (8.6%), analyses were performed on the smaller cohort with full data (including height and weight) and the larger study cohort, with height and weight omitted. Findings were unchanged; thus, height and weight were subsequently excluded from final analytical models. All models demonstrated appropriate calibration and discrimination (c ). Logistic regression models were also applied to 3 modified cohorts to determine whether any mortality risk attributable to atrial fibrillation was limited to particular subsets of arrhythmia patients. In the first cohort, we excluded all patients who underwent CABG because they may have developed atrial fibrillation as a complication

3 Rathore et al Atrial Fibrillation and Acute MI Outcomes 971 TABLE 2. Patient Characteristics Atrial Fibrillation During Acute MI Atrial Fibrillation Onset Characteristic Present (n ) Absent (n ) P On Arrival (n ) During Stay (n ) Mean age, y 79.2 (73, 85) 76.8 (71, 82) (74, 85) 78.6 (73, 84) Female, % NS White/black/other race, % 92/5/3 89/7/ /4/3 92/5/3 NS Diabetes mellitus, % NS NS Hypertension, % NS NS Current smoker, % Prior CABG, % Prior acute MI, % NS Prior CVD, % Mean systolic BP, mm Hg Heart rate, bpm Killip class (I/II/III/IV), % 36/12/47/4 51/12/34/ /12/49/4 38/12/46/ Anterior MI location, % Time to presentation, % h h h Unknown/silent CVD indicates cerebrovascular disease; BP, blood pressure. Values in parentheses are 25th and 75th percentiles. P of surgery. To account for the possibility that atrial fibrillation may be a marker for terminal illness, we excluded all patients with a life expectancy of 6 months from our second cohort. In our third cohort, we excluded patients who died during hospitalization to account for the possibility that atrial fibrillation may be a marker for more severe illness or represent a patient subset at greater risk for mortality. All calculations were performed by use of the SAS 6.12 (SAS Institute) and STATA 6.0 (STATA Corp) software packages. Results Of the patients in the study cohort, (21%) had atrial fibrillation during the course of their acute MI: patients (10.8%) had atrial fibrillation on arrival, and (11.3%) developed atrial fibrillation during hospitalization. Atrial fibrillation patients were older and more likely to be white; had higher Killip classes, higher admission heart rates, lower systolic blood pressures, more anterior MIs, and higher rates of prior cerebrovascular disease; and were less likely to smoke than patients without this arrhythmia (Table 2). Sex was not associated with the occurrence of atrial fibrillation. Clinical characteristics of patients with atrial fibrillation differed, depending on the time of atrial fibrillation recognition. Patients with atrial fibrillation documented on arrival were older, had a higher heart rate, had more advanced heart failure, and were more likely to have a history of CABG, prior MI, and cerebrovascular disease compared with patients developing atrial fibrillation in hospital (Table 2). Finally, sex was associated with time of atrial fibrillation onset because women were more likely to present with atrial fibrillation. Time of atrial fibrillation onset was comparable among racial groups. Multivariate modeling indicated that advanced heart failure (Killip class IV) was the most significant predictor of the development of atrial fibrillation (odds ratio [OR], 1.58; 95% CI, 1.45 to 1.73). Other significant predictors included heart rate, age, systolic blood pressure, anterior MI location, race, prior MI, prior cerebrovascular disease, hypertension, time to presentation, and current smoking status (Table 3). Prior CABG was not significantly associated with the development of atrial fibrillation. Patients with atrial fibrillation had significantly worse outcomes, including higher in-hospital, 30-day, and 1-year mortality (Table 4). When stratified by time of onset, patients developing atrial fibrillation during hospitalization had higher in-hospital and 30-day mortality rates compared with those presenting with atrial fibrillation and patients without atrial fibrillation. The difference in mortality rates between patients presenting with and developing atrial fibrillation decreased over time and was not significant at 1 year (the Figure). Patients with atrial fibrillation had more frequent inhospital events, including reinfarction, cerebrovascular accident, congestive heart failure, and ICU admission (Table 4). In addition, patients with atrial fibrillation remained in the hospital 2 days longer on average (9.6 versus 7.6 days, P ) than patients without this arrhythmia. In-hospital events were more frequent and length of stay was longer for patients developing atrial fibrillation during hospitalization compared with patients presenting with atrial fibrillation. Patients with atrial fibrillation remained at significantly greater risk for mortality in hospital (OR, 1.21; 95% CI, 1.17 to 1.26), at 30 days (OR, 1.20; 95% CI, 1.16 to 1.24), and at 1 year (OR, 1.34; 95% CI, 1.30 to 1.39) after adjustment for

4 972 Circulation March 7, 2000 TABLE 3. Predictors of Atrial Fibrillation Characteristic OR (95% CI) Heart rate ( 10-beat 1.13 ( ) increments) Age ( 5-year increments) 1.17 ( ) Systolic blood pressure 0.94 ( ) ( 10-mm Hg increments) Killip class I 1.00 (referent) II 1.17 ( ) III 1.46 ( ) IV 1.58 ( ) Anterior MI location 1.14 ( ) Race White 1.00 (referent) Black 0.66 ( ) Prior cerebrovascular disease 1.18 ( ) Prior MI 0.94 ( ) Time to presentation, h ( ) ( ) ( ) Unknown/silent 1.00 (referent) Hypertension 1.09 ( ) Smoker 0.94 ( ) Variables ranked, highest to lowest, by 2 statistic from logistic regression model of development of atrial fibrillation. demographic characteristics, clinical factors and the use of antiarrhythmic agents (Table 5). The prognostic significance of atrial fibrillation varied by time of onset. Patients presenting with atrial fibrillation were statistically comparable to patients without atrial fibrillation for in-hospital mortality (OR, 1.05; 95% CI, 0.99 to 1.10) and had a small risk for 30-day (OR, 1.06; 95% CI, 1.01 to 1.11) and 1-year (OR, 1.16; 95% CI, 1.11 to 1.21) mortality. In contrast, patients developing atrial fibrillation during hospitalization had the highest risk of in-hospital (OR, 1.35; 95% CI, 1.28 to 1.42), TABLE 4. Atrial Fibrillation and Outcomes Atrial Fibrillation During Acute MI Kaplan-Meier curve for unadjusted mortality at 1 year. Upper curve indicates survival among patients without atrial fibrillation (AF); middle curve, survival among patients who presented with atrial fibrillation; and lower curve, survival among patients who developed atrial fibrillation during hospitalization. AMI indicates acute MI. 30-day (OR, 1.31; 95% CI, 1.25 to 1.37), and 1-year (OR, 1.51; 95% CI, 1.44 to 1.58) mortality. Findings were unchanged when evaluated in the 3 restricted cohorts excluding coronary artery bypass, terminally ill, and in-hospital mortality patients (results not shown). Discussion Use of the CCP cohort provides a unique opportunity to study the role of atrial fibrillation in elderly acute MI patients. First, this is the first study to evaluate the role of atrial fibrillation in an exclusively elderly population. The advanced age of our study cohort allowed evaluation of a population traditionally excluded from clinical trials and rarely seen in large numbers in most centers. Second, the study provides a national perspective on the role of atrial fibrillation and is not restricted to a few centers or geographical areas. Third, the CCP contains data on Medicare beneficiaries treated for acute MI, thereby including more critically ill patients and those with comorbidities who are often excluded from clinical trial populations. Finally, the size of the CCP database provides the largest evaluation of atrial fibrillation complicating acute MI to date. With this size, we gain statistical power to detect trends in atrial fibrillation and outcomes that other studies have generally been underpowered to evaluate. Atrial Fibrillation Onset Outcome Present Absent P On Arrival During Stay P Mortality, % In hospital d y NS Hospital events, % Congestive heart failure Cerebrovascular accident Admission to ICU Reinfarction Length of stay (mean), d

5 Rathore et al Atrial Fibrillation and Acute MI Outcomes 973 TABLE 5. Atrial Fibrillation and Mortality: Findings From Multiple Logistic Regression Analysis Atrial Fibrillation Onset Mortality Atrial Fibrillation On Arrival During Stay In hospital Unadjusted 1.77 ( ) 1.65 ( ) 1.90 ( ) Adjusted* 1.21 ( ) 1.05 ( ) 1.35 ( ) 30 d Unadjusted 1.76 ( ) 1.69 ( ) 1.84 ( ) Adjusted* 1.20 ( ) 1.06 ( ) 1.31 ( ) 1y Unadjusted 1.92 ( ) 1.91 ( ) 1.93 ( ) Adjusted* 1.34 ( ) 1.16 ( ) 1.51 ( ) Values are OR (95% CI). *Model adjusted for patient age, race, sex, and GUSTO clinical predictors identified by bivariate analysis, including heart rate, systolic blood pressure, Killip class, hypertension, time to presentation, current smoking status, anterior MI, prior cerebrovascular disease, prior acute MI, and antiarrhythmic agent use on admission, during hospitalization, and at discharge (1-year mortality model only). Atrial fibrillation was a common complication of acute MI in this elderly cohort, with a prevalence of 22.1%. Patients developing atrial fibrillation were older and represented a sicker population with poorer outcomes compared with other elderly acute MI patients. Our findings build on previous research documenting the common occurrence of atrial fibrillation during acute MI and its association with adverse outcomes during hospitalization and after discharge. 1 9,18 Patients developing atrial fibrillation during hospitalization had worse in-hospital outcomes, suggesting that different times of atrial fibrillation onset may represent different pathophysiologies and thus influence prognosis differently. Atrial fibrillation was associated with higher mortality during hospitalization, at 30 days, and at 1 year. Mortality rates were significantly higher than those reported for patients in the GUSTO trial during hospitalization (25.3% versus 13.8%), at 30 days (29.3% versus 14.3%), and at 1 year (48.3% versus 21.5%). 4 However, GUSTO enrolled thrombolytic-eligible patients 19 who, in general, were healthier and younger than the cohort of elderly acute MI patients in the CCP. Our mortality rates were similar to the 30-day mortality of 25.1% and 1-year mortality of 38.4% in the expanded Secondary Prevention Reinfarction Israeli Nifedipine Trial (SPRINT) registry 3 Although SPRINT used a more inclusive enrollment, 20 its population also included a significantly younger cohort than our study population. 2,3 This difference is particularly striking because the mean age for atrial fibrillation patients in the CCP (79.2 years) is more than a full decade older than arrhythmia patients enrolled in SPRINT and GUSTO. Whereas previous studies have provided conflicting findings concerning the association of atrial fibrillation and mortality, 1 9 we found atrial fibrillation to be an independent risk factor for short- and long-term mortality. The prognostic significance of atrial fibrillation, however, varied, depending on time of atrial fibrillation onset. Patients with atrial fibrillation on arrival had a small risk of mortality, while those developing atrial fibrillation during hospitalization had a markedly increased risk of mortality. A similar finding was reported in the GUSTO trial, in which only atrial fibrillation developed during hospitalization was independently associated with mortality. 4 This difference may be explained by the fact that patients with atrial fibrillation on arrival likely included a cohort of patients with chronic atrial fibrillation, 4 whereas patients who developed atrial fibrillation during hospitalization likely exhibited this arrhythmia as a consequence of their infarct. Sakata et al 5 observed an increased mortality risk for patients developing atrial fibrillation during hospitalization after excluding patients presenting with chronic atrial fibrillation. Although the time of atrial fibrillation onset may represent different processes, the presence of atrial fibrillation remains a marker of prognostic significance in the elderly. Atrial fibrillation has consistently been identified as an independent mortality risk at long-term follow-up. However, findings have been inconclusive for short-term mortality; GUSTO noted an independent effect of atrial fibrillation related mortality 30 days after infarction, 4 whereas SPRINT found no effect. 3 Furthermore, no study has found atrial fibrillation to be an independent predictor of mortality during hospitalization. 1 9 This pattern had suggested that atrial fibrillation took on prognostic significance only if patients survived the peri-infarction period. However, our findings differ from those of previous analyses. We observed an independent, increased risk of mortality in hospital, at 30 days, and at 1 year among patients with atrial fibrillation. Thus, our data suggest that atrial fibrillation influences mortality during the infarction and recovery period in elderly patients and is not limited to long-term follow-up. The cause of atrial fibrillation during acute MI remains unclear. Possible mechanisms include pericarditis, atrial ischemia or infarction, increased catecholamines, metabolic abnormalities, and increased atrial pressures. As in prior studies, 1 3,5 7 we noted poorer clinical status and significant comorbidity among patients with atrial fibrillation, including advanced Killip class, increased heart rate, and lower systolic blood pressure. These findings suggest that hemodynamic factors may influence the development of atrial fibrillation and parallel reports of poorer hemodynamic status documented in other studies. 4 6,8,21 Although previous studies identified age, hemodynamic, and ECG factors 4,6,22 as the primary predictors of atrial fibrillation, we found advanced Killip class to be the greatest predictor of atrial fibrillation. The diminished importance of age in our analysis may reflect the advanced age (mean age, 77.4 years) of our cohort compared with most previous analyses. Our study has several limitations. We relied on data from a retrospective chart analysis. As a result, we were unable to determine the precise onset or duration of atrial fibrillation, and thus we could not distinguish effects attributable to paroxysmal versus chronic atrial fibrillation. Patients with atrial fibrillation on arrival may include those with chronic arrhythmias and those with new-onset arrhythmias. Similarly, we were unable to evaluate the permanence of atrial fibrillation after hospitalization. In addition, we were unable to

6 974 Circulation March 7, 2000 evaluate patients specific clinical sequence of in-hospital events. Given that in-hospital events likely influence mortality and that we adjusted only for patient history and arrival findings, the risk of mortality attributable to atrial fibrillation developing during hospitalization may be overestimated. Conclusions Atrial fibrillation is a common complication of acute MI in the elderly, occurring in 22% of patients in our study cohort. Patients with atrial fibrillation were older, were in worse health, and had significantly worse outcomes during hospitalization and after discharge. Although baseline clinical status may have predisposed patients to poorer outcomes, atrial fibrillation was independently associated with increased mortality. The influence of atrial fibrillation was greatest for patients developing atrial fibrillation during hospitalization. Greater attention to the management of atrial fibrillation complicating acute MI in the elderly, particularly among high-risk patients, may be warranted. Acknowledgments This research was supported by contracts P623 and P624 sponsored by the Delmarva Foundation for Medical Care, Inc, and the US Health Care Financing Administration. The contents of this publication do not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the US government. The authors assume full responsibility for the accuracy and completeness of the ideas presented. This article is a direct result of the Health Care Quality Improvement Program initiated by the Health Care Financing Administration, which has encouraged identification of quality improvement projects derived from analysis of patterns of care. References 1. Goldberg RJ, Seeley D, Becker RC. 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