Acute Myocardial Infarction Complicated by Atrial Fibrillation in the Elderly: Prevalence
and Outcomes
Saif S. Rathore, Alan K. Berger, Kevin P. Weinfurt, Kevin A. Schulman, William J. Oetgen,
Bernard J. Gersh and Allen J. Solomon
Circulation. 2000;101:969-974
doi: 10.1161/01.CIR.101.9.969
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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 106 780 Medicare beneficiaries ⱖ65 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 23 565 patients (22.1%): 11 510 presented with
AF and 12 055 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;101:969-974.)
Key Words: infarction 䡲 fibrillation 䡲 mortality
A
trial 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
234 769 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, 1999.
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 20007. E-mail solomona@gunet.georgetown.edu
© 2000 American Heart Association, Inc.
Circulation is available at http://www.circulationaha.org
969
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TABLE 1.
March 7, 2000
Study Cohort and CCP Sample Population Exclusions
Patients
Excluded, n
Exclusion Criteria
Total sample
234 769
Exclusions*
Patient age ⬍65 y
17 593
No confirmed MI on admission
45 349
Readmission for MI
23 773
Interhospital transfer
81 306
Patient did not receive ECG or no ECG
with documentation
23 574
Mortality status unknown
3
Any 1 of the above exclusions
Study sample
127 989
106 780
*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 elsewhere13 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 ⱖ65 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⫽106 780) 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⬍0.05.
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⫽360.75).
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
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Rathore et al
TABLE 2.
Atrial Fibrillation and Acute MI Outcomes
971
Patient Characteristics
Atrial Fibrillation During Acute MI
Atrial Fibrillation Onset
Characteristic
Present
(n⫽23 565)
Absent
(n⫽83 215)
P
On Arrival
(n⫽11 510)
During Stay
(n⫽12 055)
P
Mean age, y
79.2 (73, 85)
76.8 (71, 82)
⬍0.0001
79.7 (74, 85)
78.6 (73, 84)
⬍0.0001
50.1
50.7
NS
52.0
48.2
0.001
92/5/3
89/7/4
0.001
93/4/3
92/5/3
NS
Female, %
White/black/other race, %
Diabetes mellitus, %
31.0
31.0
NS
30.6
31.4
NS
Hypertension, %
62.6
61.9
NS
62.2
62.9
NS
Current smoker, %
11.8
14.6
0.001
10.6
12.9
0.001
Prior CABG, %
11.4
12.5
0.001
12.1
10.7
0.001
0.001
Prior acute MI, %
33.2
32.7
NS
34.3
32.3
Prior CVD, %
17.9
14.3
0.001
19.8
16.1
Mean systolic BP, mm Hg
Heart rate, bpm
138
145
⬍0.0001
137
⬍0.0001
102.2
90.0
139
0.001
⬍0.05
⬍0.0001
95.8
86.8
Killip class (I/II/III/IV), %
36/12/47/4
51/12/34/2
0.001
35/12/49/4
38/12/46/4
0.001
Anterior MI location, %
51.8
46.6
0.001
48.3
55.2
0.001
49.2
53.6
49.2
49.1
Time to presentation, %
⬍6 h
0.001
0.001
6–12 h
7.8
9.2
7.0
8.5
⬎12 h
12.4
14.0
10.9
13.9
Unknown/silent
31.6
23.2
32.9
31.4
CVD indicates cerebrovascular disease; BP, blood pressure. Values in parentheses are 25th and 75th percentiles.
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 106 780 patients in the study cohort, 23 565 (21%) had
atrial fibrillation during the course of their acute MI: 11 510
patients (10.8%) had atrial fibrillation on arrival, and 12 055
(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⬍0.0001) 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
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TABLE 3.
March 7, 2000
Predictors of Atrial Fibrillation
Characteristic
OR (95% CI)
Heart rate (⫹10-beat
increments)
1.13 (1.12–1.13)
Age (⫹5-year increments)
1.17 (1.16–1.18)
Systolic blood pressure
(⫹10-mm Hg increments)
0.94 (0.93–0.94)
Killip class
I
1.00 (referent)
II
1.17 (1.12–1.23)
III
1.46 (1.41–1.51)
IV
1.58 (1.45–1.73)
Anterior MI location
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.
1.14 (1.11–1.18)
Race
White
1.00 (referent)
Black
0.66 (0.62–0.71)
Prior cerebrovascular disease
1.18 (1.14–1.23)
Prior MI
0.94 (0.91–0.97)
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).
Time to presentation, h
⬍6
0.94 (0.90–0.97)
6–12
0.84 (0.79–0.89)
⬎12
0.86 (0.82–0.90)
Unknown/silent
1.00 (referent)
Hypertension
1.09 (1.06–1.13)
Smoker
0.94 (0.90–0.99)
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.
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
Outcome
Present
Absent
P
Atrial Fibrillation Onset
On Arrival
P
During Stay
Mortality, %
In hospital
25.3
16.0
0.001
23.9
26.6
0.001
30 d
29.3
19.1
0.001
28.4
30.2
0.002
1y
48.3
32.7
0.001
48.2
48.5
NS
Congestive heart failure
60.1
42.2
0.001
57.9
62.1
0.001
Cerebrovascular accident
2.8
1.7
0.001
2.4
3.2
0.001
Admission to ICU
6.4
4.6
0.001
4.9
7.8
0.001
Reinfarction
4.4
3.6
0.001
3.2
5.6
0.001
9.6
7.6
⬍0.0001
8.1
11.0
⬍0.0001
Hospital events, %
Length of stay (mean), d
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Rathore et al
TABLE 5. Atrial Fibrillation and Mortality: Findings From
Multiple Logistic Regression Analysis
Atrial Fibrillation Onset
Mortality
Atrial Fibrillation
On Arrival
During Stay
Unadjusted
1.77 (1.71–1.84)
1.65 (1.57–1.72)
1.90 (1.82–1.99)
Adjusted*
1.21 (1.17–1.26)
1.05 (0.99–1.10)
1.35 (1.28–1.42)
Unadjusted
1.76 (1.71–1.82)
1.69 (1.61–1.76)
1.84 (1.76–1.92)
Adjusted*
1.20 (1.16–1.24)
1.06 (1.01–1.11)
1.31 (1.25–1.37)
Unadjusted
1.92 (1.87–1.98)
1.91 (1.84–1.99)
1.93 (1.86–2.01)
Adjusted*
1.34 (1.30–1.39)
1.16 (1.11–1.21)
1.51 (1.44–1.58)
In hospital
30 d
1y
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 patients19 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) registry3 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 fibril-
Atrial Fibrillation and Acute MI Outcomes
973
lation 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 al5 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 factors4,6,22 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
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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 500-96-P623 and 500-96P624 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.
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