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Relation of Anemia at Discharge to Survival After Acute Coronary Syndromes
Relation of Anemia at Discharge to Survival After Acute Coronary Syndromes Joseph Vaglio, MD, MBAa,e, David M. Safley, MDa,b, Mohamed Rahman, MDc, Mikhail Kosiborod, MDd, Philip Jones, MSa, Randall Thompson, MDa, Harlan M. Krumholz, MDd, and John A. Spertus, MD, MPHa,b,* Two-year survival rate was assessed among 1,038 patients who had acute coronary syndromes that were classified by discharge hematocrit values as normal (>39%, n ⴝ 360, 34.7%), mildly anemic (33.1% to 39%, n ⴝ 430, 41.4%), or moderately/severely anemic (<33%, n ⴝ 248, 23.9%). Worsening anemia was associated with a decreased 2-year survival rate (normal 95.8%, mild anemia 91.2%, moderate/severe anemia 81.5%, p < 0.001). In multivariable analyses, adjusted hazard ratios for all-cause mortality were 1.57 (95% confidence interval 0.82 to 2.96) for mild anemia and 2.46 (95% confidence interval 1.25 to 4.85) for moderate/severe anemia. © 2005 Elsevier Inc. All rights reserved. (Am J Cardiol 2005;96:496 – 499) To address the current controversy regarding the relation between anemia and prognosis,1– 4 we examined the association between anemia and survival in an observational, prospective registry of patients who had acute coronary syndrome (ACS) for which detailed patient and clinical data were available to address potential confounding that may have influenced previous studies. Patients were stratified into 3 anemia categories (none, mild, and moderate/severe) according to hematocrit values at discharge and prospectively followed to assess 2-year survival. Our goal was to clarify the independent effect of anemia on long-term survival after ACS. •••
Patients were prospectively enrolled into an ACS registry at the Mid America Heart Institute and the Truman Medical Center (Kansas City, Missouri). All 10,911 consecutive patients who were admitted between March 1, 2001 and October 31, 2002 and had a troponin blood test ordered were screened by trained data collectors for a possible ACS. Those who had potential unstable angina or acute myocardial infarction (AMI) were identified for possible study participation. AMI was defined by a positive troponin blood test in the setting of symptoms or electrocardiographic changes (ST-segment elevation and non–ST-segment elevation changes) consistent with an AMI.5 Unstable angina was diagnosed if a patient had a negative troponin blood test and any 1 of the following: new-onset angina (⬍2 months) of at least Canadian Cardiovascular Society Classification class The aMid America Heart Institute of Saint Luke’s Hospital and the University of Missouri–Kansas City, Kansas City, Missouri; the cMeritcare Clinic, Fargo, North Dakota; the dYale University School of Medicine, New Haven, Connecticut; and the eMayo Graduate School of Medicine, Rochester, Minnesota. Manuscript received December 9, 2004; revised manuscript received and accepted April 8, 2005. This project was supported by Grant R-01 HS11282-01 from the Agency for Healthcare Research and Quality, Rockville, Maryland. * Corresponding author. Tel.: 816-932-8270; fax: 816-932-5613. E-mail address: [email protected] (J. Spertus). b
0002-9149/05/$ – see front matter © 2005 Elsevier Inc. All rights reserved. doi:10.1016/j.amjcard.2005.04.008
III, prolonged (⬎20 minutes) angina at rest, recent (⬍2 months) worsening of angina, or angina that occurred within 2 weeks of a previous AMI.6 All patients who had presumed unstable angina and were found to have a diagnostic study that excluded obstructive coronary disease (i.e., coronary angiography, nuclear or echocardiographic stress testing) or who had an additional diagnostic study that confirmed an alternative explanation for patients’ presentation (i.e., esophago-gastroduodenoscopy) were subsequently excluded. Three physicians reviewed the charts of all patients for whom diagnostic uncertainty remained and attained consensus on the final diagnosis. Ultimately 1,199 patients consented to participate in the registry. All participating patients were interviewed by a trained data collector to ascertain their baseline sociodemographic, economic, and health status (symptoms, function, and quality of life) characteristics. Detailed chart abstractions were performed to ascertain patients’ medical history, laboratory results, disease severity, and processes of inpatient care. Vital status was obtained through a query of the Social Security Master Death File and review of hospital records. Approval from the institutional review boards of the 2 institutions was obtained before the conduct of the study and informed consent to participate was signed by each participant. Patients who were treated with coronary artery bypass surgery (n ⫽ 126) were excluded from this analysis because the etiology of their universal anemia is caused by the surgery itself and these patients represent a clinically distinct population. Other exclusions were those who did not undergo repeat hematocrit after admission (n ⫽ 24), those who died during hospitalization (n ⫽ 7), and those who were lost to follow-up (n ⫽ 4). Anemia was defined as a hematocrit level ⬍39%7 and was further stratified into mild or moderate/severe anemia groups (hematocrit level 33.1% to 39% or ⱕ33%, respectively).3 Although previous studies of the acute effects of anemia on inpatient events and short-term mortality have www.AJConline.org
Coronary Artery Disease/Anemia and Survival After ACS
497
Table 1 Baseline characteristics by hematocrit group Variable
Age (yrs) Men Caucasian Clinical Body mass index (kg/m2) Hypertension Diabetes mellitus Arthritis Cancer Congestive heart failure Alcohol abuse Current smoking Left ventricular ejection fraction Admit creatinine (mg/dl) Admit pulse (beats/min) Admit systolic blood pressure (mm Hg) Admit disatolic blood pressure (mm Hg) AMI Medical treatment only
Hematocrit at Discharge (%)
p Value
39–55 (n ⫽ 360)
33–39 (n ⫽ 430)
ⱕ33 (n ⫽ 248)
56 ⫾ 12 291 (81%) 283 (79%)
62 ⫾ 13 250 (58%) 348 (81%)
67 ⫾ 13 102 (41%) 193 (78%)
⬍0.001 ⬍0.001 0.471
30 ⫾ 6 224 (62%) 67 (19%) 37 (10%) 19 (5%) 16 (4%) 32 (9%) 154 (43%) 0.49 ⫾ 0.13 1.1 ⫾ 0.8 76 ⫾ 17 140 ⫾ 26 78 ⫾ 16 172 (48%) 265 (74%)
29 ⫾ 6 273 (64%) 103 (24%) 70 (16%) 30 (7%) 26 (6%) 17 (4%) 135 (32%) 0.47 ⫾ 0.13 1.1 ⫾ 0.6 77 ⫾ 18 136 ⫾ 26 74 ⫾ 17 247 (58%) 280 (65%)
29 ⫾ 6 178 (72%) 98 (40%) 47 (19%) 37 (15%) 33 (13%) 9 (4%) 51 (21%) 0.45 ⫾ 0.14 1.4 ⫾ 1.4 82 ⫾ 19 138 ⫾ 29 71 ⫾ 16 158 (64%) 153 (62%)
0.02 0.04 ⬍0.001 0.007 ⬍0.001 ⬍0.001 0.003 ⬍0.001 0.01 ⬍0.001 ⬍0.001 0.06 ⬍0.001 ⬍0.001 0.004
All data presented as mean ⫾ SD or number (percentage).
used patients’ hematocrit level at hospital admission,3,8 our objective was to assess the effect of anemia on long-term survival after ACS. Therefore, anemia at hospital discharge was chosen for the primary analysis because it represents patients’ hematologic state closest to the initiation of follow-up (i.e., closest to “time 0” from which their prognosis was assessed) and because other risk factors for subsequent survival are also considered and addressed at the time of discharge. To place this study in the context of previous work, a secondary analysis was conducted to examine the influence of anemia at the time of admission for ACS and to compare outcomes between patients who had anemia at discharge and those who had preexisting anemia. Baseline characteristics of the 3 anemia groups were compared. Categorical data were reported as frequencies, and differences between groups were compared using chisquare or Fisher’s exact test, as appropriate. Continuous data were reported as mean ⫾ SD and differences between groups were tested with analysis of variance. In multivariable analyses, the mean effect ⫾ SE were reported. The primary analysis evaluated the time to all-cause mortality. Survival curves for the 3 hematocrit groups were derived by Kaplan-Meier analysis and compared using logrank tests. A multivariable proportional hazards model was then constructed to control for demographic and clinical variables, including age, gender, race, diabetes, chronic obstructive pulmonary disease/asthma, renal function (glomerular filtration rate calculated by the Cockroft/Gault formula), previous AMI, left ventricular dysfunction (ejection fraction ⬍40%), and treatment group (medical therapy only vs percutaneous revascularization). These factors were selected a priori based on previous studies, clinical experi-
ence, and statistical criteria (p ⬍0.05) for retention in the final model. Although a history of cancer was associated with severity of anemia, it was not associated with 2-year survival on univariate analysis (p ⫽ 0.29) and was therefore not included in the model. Continuous variables were examined for nonlinear trends using spline methods. Model fit was evaluated by analysis of residuals and discriminatory power was assessed by the c-statistic. Of the 1,038 patients included in this analysis, 430 (41.4%) met criteria for mild anemia, and 248 (23.9%) had moderate/severe anemia. Baseline characteristics are presented in Table 1. Increased severity of anemia at discharge was associated with female gender and a larger number of co-morbid illnesses, specifically hypertension (62% of patients had normal hematocrit vs 64% with mild anemia vs 72% with moderate/severe anemia, p ⫽ 0.04), diabetes (19% vs 24% vs 40%, p ⬍0.001), and higher serum creatinine levels (1.1 vs 1.1 vs 1.4 mg/dl, p ⬍0.001). Higher hematocrit levels were associated with self-reported smoking and alcohol use. Type of ACS was also significantly associated with anemia at discharge, with moderate/severe anemia being more common in patients who presented with AMI than in those who presented with unstable angina (63.7% vs 36.3%, p ⬍0.001). In-hospital treatment differences at the time of ACS are presented in Table 2. No significant differences in therapy for ACS between hematocrit groups were noted, except for the use of intravenous heparin (66% vs 76% vs 77%, p ⫽ 0.02) and oral antiplatelet agents other than aspirin (e.g., clopidogrel or ticlopidine, 59% vs 73%, p ⬍ 0.001). Most medications prescribed at discharge did not differ significantly among patients who had normal or lower hematocrit values.
498
The American Journal of Cardiology (www.AJConline.org)
Table 2 Treatment of acute coronary syndrome by hematocrit group Hematocrit at Discharge (%)
Acute therapies Primary angioplasty Thrombolysis Intravenous antiplatelet agent Unfractionated heparin Aspirin within 24 h  Blockade within 24 h Discharge medications Aspirin Oral antiplatelet—Other Angiotensin-converting enzyme inhibitor Angiotensin receptor blocker Antihyperlipidemic  Blocker Calcium channel blocker Diuretic Nitrates
p Value
⬎39–55 (n ⫽ 360)
⬎33–39 (n ⫽ 430)
ⱕ33 (n ⫽ 248)
96 (27%) 31 (9%) 152 (42%) 236 (66%) 353 (98%) 300 (83%)
139 (32%) 30 (7%) 215 (50%) 326 (76%) 423 (99%) 374 (87%)
79 (32%) 13 (5%) 118 (48%) 191 (77%) 240 (98%) 208 (84%)
0.2 0.3 0.08 0.02 0.3 0.3
337 (94%) 213 (59%) 257 (71%) 22 (6%) 287 (80%) 288 (80%) 45 (13%) 82 (23%) 49 (14%)
409 (95%) 312 (73%) 312 (73%) 35 (8%) 323 (75%) 348 (81%) 66 (15%) 100 (23%) 71 (17%)
235 (95%) 182 (73%) 177 (71%) 23 (9%) 191 (77%) 206 (83%) 31 (13%) 95 (38%) 43 (17%)
0.6 ⬍0.001 0.9 0.3 0.3 0.6 0.4 ⬍0.001 0.3
All data presented as numbers (percentage).
Mean follow-up for patients in this study was 22 months. In unadjusted analyses, more severe anemia at time of discharge was significantly associated with decreased 2-year survival rate (normal 95.8% vs mild anemia 91.2% vs moderate/severe anemia 81.5%, p ⬍0.001). KaplanMeier survival curves are shown in Figure 1. After multivariable adjustment, anemia at discharge remained significantly associated with 2-year survival rate from ACS (Figure 2). Despite adjusting for potentially confounding variables, a significant association between anemia and mortality was observed (adjusted hazard ratio 1.57, 95% confidence interval [CI] 0.82 to 2.96, for mild anemia; 2.46, 95% CI 1.25 to 4.85, for moderate/severe anemia; p ⫽ 0.025 for trend). Additional factors significantly associated with mortality included age (relative hazard 1.38 per 10
Figure 1. Unadjusted 2-year all-cause mortality by hematocrit (HCT) group.
years, p ⫽ 0.001), diabetes (hazard ratio 1.81, 95% CI 1.16 to 2.81), chronic lung disease (hazard ratio 2.06, 95% CI 1.23 to 3.46), previous AMI (hazard ratio 1.85, 95% CI 1.16 to 2.94), ejection fraction ⬍40% (hazard ratio 3.03, 95% CI 2.17 to 5.03), no revascularization (hazard ratio 2.56, 95% CI 1.61 to 4.07), and glomerular filtration rate (per 10 ml/min decrease; hazard ratio 1.18, 95% CI 1.08 to 1.30; Figure 3). The c-statistic for the final model was 0.81. To better illuminate the relation between anemia at admission and long-term mortality, a secondary analysis was conducted using the same multivariable model. Anemia on admission was not significantly associated with mortality (hazard ratio 1.44, 95% CI 0.87 to 2.39, for those with mild anemia; hazard ratio 1.38, 95% CI 0.72 to 2.62, for those
Figure 2. Adjusted 2-year all cause mortality by hematocrit group and controlled for age, gender, race, diabetes, chronic obstructive pulmonary disease/ asthma, renal function, previous AMI, left ventricular dysfunction, and treatment group (medical therapy only vs percutaneous revascularization).
Coronary Artery Disease/Anemia and Survival After ACS
Figure 3. Hazard ratios. GFR ⫽ glomerular filtration rate. Other abbreviation as in Figure 1.
with moderate/severe anemia). A subgroup analysis compared hazard ratios between patients who were consistently anemic (admission and discharge) and those who had newonset anemia (discharge only; Figure 4). Among patients who had mild anemia at discharge, there were no significant differences in survival based on their anemia status at admission (hazard ratio 1.92, 95% CI 0.82 to 4.51, for those without anemia; hazard ratio 1.66, 95% CI 0.81 to 3.42, for those with mild or moderate/severe anemia). Conversely, moderate/severe anemia at discharge was associated with decreased survival for patients who had consistent anemia (hazard ratio 2.63, 95% CI 1.27 to 5.42) or new-onset anemia (hazard ratio 3.05, 95% CI 1.03 to 9.06). The substantially greater effect of anemia at discharge on mortality suggests that this is a much more important determinant of outcome than the presence of anemia at admission. •••
Figure 4. Adjusted hazard ratios for anemia at admission/discharge (any ⫽ mild or moderate/severe anemia at admission; none ⫽ no anemia at admission; mild ⫽ mild anemia at discharge; severe ⫽ moderate/severe anemia at discharge).
499
This study demonstrates that moderate/severe anemia (hematocrit ⱕ33%) at hospital discharge is independently associated with a 2.5-fold greater odds of dying within 2 years of admission for ACS. Further, we demonstrated that, whereas anemia immediately before discharge was associated with survival, anemia assessed at the time of initial clinical presentation was not. These findings were independent of numerous other potentially confounding factors and provide new insights to the current controversy that surrounds the association of anemia with survival after ACS. A previous study by Wu et al3 of an observational cohort of elderly patients who had AMI showed that admission hematocrit level was correlated with adjusted inpatient and 30-day mortality. Although this study used admission hematocrit as the variable of interest, it also included inpatient mortality. Our findings of a nonsignificant trend for admission hematocrit associated with 2-year survival were consistent with the statistically significant observations of this much larger study (n ⫽ 78,974). Our work extends this previous effort by showing a continuing divergence of the survival curves beyond 30 days and by clarifying the greater importance of discharge hematocrit on prognosis. Such findings were consistent with the findings of Wu et al,3 that patients who had anemia and received a blood transfusion (presumably improving their hematocrit at discharge) had better short-term survival than those who did not receive a transfusion. Further research to clarify the value of treating patients who have anemia at discharge to improve their hematocrit is needed to explore the potential of further improving their prognosis. 1. Al Falluji N, Lawrence-Nelson J, Kostis JB, Lacy CR, Ranjan R, Wilson AC. Effect of anemia on 1-year mortality in patients with acute myocardial infarction. Am Heart J 2002;144:636 – 641. 2. Anand I, McMurray JJ, Whitmore J, Warren M, Pham A, McCamish MA, Burton PB. Anemia and its relationship to clinical outcome in heart failure. Circulation 2004;110:149 –154. 3. Wu WC, Rathore SS, Wang Y, Radford MJ, Krumholz HM. Blood transfusion in elderly patients with acute myocardial infarction. N Engl J Med 2001;345:1230 –1236. 4. Rao SV, Jollis JG, Harrington RA, Granger CB, Newby LK, Armstrong PW, Moliterno DJ, Lindblad L, Pieper K, Topol EJ, et al. Relationship of blood transfusion and clinical outcomes in patients with acute coronary syndromes. JAMA 2004;292:1555–1562. 5. Alpert JS, Thygesen K, Antman E, Bassand JP. Myocardial infarction redefined—a consensus document of the Joint European Society of Cardiology/American College of Cardiology Committee for the redefinition of myocardial infarction. J Am Coll Cardiol 2000;36:959 –969. 6. Braunwald E. Unstable angina. A classification. Circulation 1989;80: 410 – 414. 7. Nutritional Anaemias. Report of a WHO Scientific Group. WHO Technical Report Series. Geneva: World Health Organization, 1968. 8. Hebert PC, Wells G, Blajchman MA, Marshall J, Martin C, Pagliarello G, Tweeddale M, Schweitzer I, Yetisir E. A multicenter, randomized, controlled clinical trial of transfusion requirements in critical care. Transfusion Requirements in Critical Care Investigators, Canadian Critical Care Trials Group. N Engl J Med 1999;340:409 – 417.
Patients were prospectively enrolled into an ACS registry at the Mid America Heart Institute and the Truman Medical Center (Kansas City, Missouri). All 10,911 consecutive patients who were admitted between March 1, 2001 and October 31, 2002 and had a troponin blood test ordered were screened by trained data collectors for a possible ACS. Those who had potential unstable angina or acute myocardial infarction (AMI) were identified for possible study participation. AMI was defined by a positive troponin blood test in the setting of symptoms or electrocardiographic changes (ST-segment elevation and non–ST-segment elevation changes) consistent with an AMI.5 Unstable angina was diagnosed if a patient had a negative troponin blood test and any 1 of the following: new-onset angina (⬍2 months) of at least Canadian Cardiovascular Society Classification class The aMid America Heart Institute of Saint Luke’s Hospital and the University of Missouri–Kansas City, Kansas City, Missouri; the cMeritcare Clinic, Fargo, North Dakota; the dYale University School of Medicine, New Haven, Connecticut; and the eMayo Graduate School of Medicine, Rochester, Minnesota. Manuscript received December 9, 2004; revised manuscript received and accepted April 8, 2005. This project was supported by Grant R-01 HS11282-01 from the Agency for Healthcare Research and Quality, Rockville, Maryland. * Corresponding author. Tel.: 816-932-8270; fax: 816-932-5613. E-mail address: [email protected] (J. Spertus). b
0002-9149/05/$ – see front matter © 2005 Elsevier Inc. All rights reserved. doi:10.1016/j.amjcard.2005.04.008
III, prolonged (⬎20 minutes) angina at rest, recent (⬍2 months) worsening of angina, or angina that occurred within 2 weeks of a previous AMI.6 All patients who had presumed unstable angina and were found to have a diagnostic study that excluded obstructive coronary disease (i.e., coronary angiography, nuclear or echocardiographic stress testing) or who had an additional diagnostic study that confirmed an alternative explanation for patients’ presentation (i.e., esophago-gastroduodenoscopy) were subsequently excluded. Three physicians reviewed the charts of all patients for whom diagnostic uncertainty remained and attained consensus on the final diagnosis. Ultimately 1,199 patients consented to participate in the registry. All participating patients were interviewed by a trained data collector to ascertain their baseline sociodemographic, economic, and health status (symptoms, function, and quality of life) characteristics. Detailed chart abstractions were performed to ascertain patients’ medical history, laboratory results, disease severity, and processes of inpatient care. Vital status was obtained through a query of the Social Security Master Death File and review of hospital records. Approval from the institutional review boards of the 2 institutions was obtained before the conduct of the study and informed consent to participate was signed by each participant. Patients who were treated with coronary artery bypass surgery (n ⫽ 126) were excluded from this analysis because the etiology of their universal anemia is caused by the surgery itself and these patients represent a clinically distinct population. Other exclusions were those who did not undergo repeat hematocrit after admission (n ⫽ 24), those who died during hospitalization (n ⫽ 7), and those who were lost to follow-up (n ⫽ 4). Anemia was defined as a hematocrit level ⬍39%7 and was further stratified into mild or moderate/severe anemia groups (hematocrit level 33.1% to 39% or ⱕ33%, respectively).3 Although previous studies of the acute effects of anemia on inpatient events and short-term mortality have www.AJConline.org
Coronary Artery Disease/Anemia and Survival After ACS
497
Table 1 Baseline characteristics by hematocrit group Variable
Age (yrs) Men Caucasian Clinical Body mass index (kg/m2) Hypertension Diabetes mellitus Arthritis Cancer Congestive heart failure Alcohol abuse Current smoking Left ventricular ejection fraction Admit creatinine (mg/dl) Admit pulse (beats/min) Admit systolic blood pressure (mm Hg) Admit disatolic blood pressure (mm Hg) AMI Medical treatment only
Hematocrit at Discharge (%)
p Value
39–55 (n ⫽ 360)
33–39 (n ⫽ 430)
ⱕ33 (n ⫽ 248)
56 ⫾ 12 291 (81%) 283 (79%)
62 ⫾ 13 250 (58%) 348 (81%)
67 ⫾ 13 102 (41%) 193 (78%)
⬍0.001 ⬍0.001 0.471
30 ⫾ 6 224 (62%) 67 (19%) 37 (10%) 19 (5%) 16 (4%) 32 (9%) 154 (43%) 0.49 ⫾ 0.13 1.1 ⫾ 0.8 76 ⫾ 17 140 ⫾ 26 78 ⫾ 16 172 (48%) 265 (74%)
29 ⫾ 6 273 (64%) 103 (24%) 70 (16%) 30 (7%) 26 (6%) 17 (4%) 135 (32%) 0.47 ⫾ 0.13 1.1 ⫾ 0.6 77 ⫾ 18 136 ⫾ 26 74 ⫾ 17 247 (58%) 280 (65%)
29 ⫾ 6 178 (72%) 98 (40%) 47 (19%) 37 (15%) 33 (13%) 9 (4%) 51 (21%) 0.45 ⫾ 0.14 1.4 ⫾ 1.4 82 ⫾ 19 138 ⫾ 29 71 ⫾ 16 158 (64%) 153 (62%)
0.02 0.04 ⬍0.001 0.007 ⬍0.001 ⬍0.001 0.003 ⬍0.001 0.01 ⬍0.001 ⬍0.001 0.06 ⬍0.001 ⬍0.001 0.004
All data presented as mean ⫾ SD or number (percentage).
used patients’ hematocrit level at hospital admission,3,8 our objective was to assess the effect of anemia on long-term survival after ACS. Therefore, anemia at hospital discharge was chosen for the primary analysis because it represents patients’ hematologic state closest to the initiation of follow-up (i.e., closest to “time 0” from which their prognosis was assessed) and because other risk factors for subsequent survival are also considered and addressed at the time of discharge. To place this study in the context of previous work, a secondary analysis was conducted to examine the influence of anemia at the time of admission for ACS and to compare outcomes between patients who had anemia at discharge and those who had preexisting anemia. Baseline characteristics of the 3 anemia groups were compared. Categorical data were reported as frequencies, and differences between groups were compared using chisquare or Fisher’s exact test, as appropriate. Continuous data were reported as mean ⫾ SD and differences between groups were tested with analysis of variance. In multivariable analyses, the mean effect ⫾ SE were reported. The primary analysis evaluated the time to all-cause mortality. Survival curves for the 3 hematocrit groups were derived by Kaplan-Meier analysis and compared using logrank tests. A multivariable proportional hazards model was then constructed to control for demographic and clinical variables, including age, gender, race, diabetes, chronic obstructive pulmonary disease/asthma, renal function (glomerular filtration rate calculated by the Cockroft/Gault formula), previous AMI, left ventricular dysfunction (ejection fraction ⬍40%), and treatment group (medical therapy only vs percutaneous revascularization). These factors were selected a priori based on previous studies, clinical experi-
ence, and statistical criteria (p ⬍0.05) for retention in the final model. Although a history of cancer was associated with severity of anemia, it was not associated with 2-year survival on univariate analysis (p ⫽ 0.29) and was therefore not included in the model. Continuous variables were examined for nonlinear trends using spline methods. Model fit was evaluated by analysis of residuals and discriminatory power was assessed by the c-statistic. Of the 1,038 patients included in this analysis, 430 (41.4%) met criteria for mild anemia, and 248 (23.9%) had moderate/severe anemia. Baseline characteristics are presented in Table 1. Increased severity of anemia at discharge was associated with female gender and a larger number of co-morbid illnesses, specifically hypertension (62% of patients had normal hematocrit vs 64% with mild anemia vs 72% with moderate/severe anemia, p ⫽ 0.04), diabetes (19% vs 24% vs 40%, p ⬍0.001), and higher serum creatinine levels (1.1 vs 1.1 vs 1.4 mg/dl, p ⬍0.001). Higher hematocrit levels were associated with self-reported smoking and alcohol use. Type of ACS was also significantly associated with anemia at discharge, with moderate/severe anemia being more common in patients who presented with AMI than in those who presented with unstable angina (63.7% vs 36.3%, p ⬍0.001). In-hospital treatment differences at the time of ACS are presented in Table 2. No significant differences in therapy for ACS between hematocrit groups were noted, except for the use of intravenous heparin (66% vs 76% vs 77%, p ⫽ 0.02) and oral antiplatelet agents other than aspirin (e.g., clopidogrel or ticlopidine, 59% vs 73%, p ⬍ 0.001). Most medications prescribed at discharge did not differ significantly among patients who had normal or lower hematocrit values.
498
The American Journal of Cardiology (www.AJConline.org)
Table 2 Treatment of acute coronary syndrome by hematocrit group Hematocrit at Discharge (%)
Acute therapies Primary angioplasty Thrombolysis Intravenous antiplatelet agent Unfractionated heparin Aspirin within 24 h  Blockade within 24 h Discharge medications Aspirin Oral antiplatelet—Other Angiotensin-converting enzyme inhibitor Angiotensin receptor blocker Antihyperlipidemic  Blocker Calcium channel blocker Diuretic Nitrates
p Value
⬎39–55 (n ⫽ 360)
⬎33–39 (n ⫽ 430)
ⱕ33 (n ⫽ 248)
96 (27%) 31 (9%) 152 (42%) 236 (66%) 353 (98%) 300 (83%)
139 (32%) 30 (7%) 215 (50%) 326 (76%) 423 (99%) 374 (87%)
79 (32%) 13 (5%) 118 (48%) 191 (77%) 240 (98%) 208 (84%)
0.2 0.3 0.08 0.02 0.3 0.3
337 (94%) 213 (59%) 257 (71%) 22 (6%) 287 (80%) 288 (80%) 45 (13%) 82 (23%) 49 (14%)
409 (95%) 312 (73%) 312 (73%) 35 (8%) 323 (75%) 348 (81%) 66 (15%) 100 (23%) 71 (17%)
235 (95%) 182 (73%) 177 (71%) 23 (9%) 191 (77%) 206 (83%) 31 (13%) 95 (38%) 43 (17%)
0.6 ⬍0.001 0.9 0.3 0.3 0.6 0.4 ⬍0.001 0.3
All data presented as numbers (percentage).
Mean follow-up for patients in this study was 22 months. In unadjusted analyses, more severe anemia at time of discharge was significantly associated with decreased 2-year survival rate (normal 95.8% vs mild anemia 91.2% vs moderate/severe anemia 81.5%, p ⬍0.001). KaplanMeier survival curves are shown in Figure 1. After multivariable adjustment, anemia at discharge remained significantly associated with 2-year survival rate from ACS (Figure 2). Despite adjusting for potentially confounding variables, a significant association between anemia and mortality was observed (adjusted hazard ratio 1.57, 95% confidence interval [CI] 0.82 to 2.96, for mild anemia; 2.46, 95% CI 1.25 to 4.85, for moderate/severe anemia; p ⫽ 0.025 for trend). Additional factors significantly associated with mortality included age (relative hazard 1.38 per 10
Figure 1. Unadjusted 2-year all-cause mortality by hematocrit (HCT) group.
years, p ⫽ 0.001), diabetes (hazard ratio 1.81, 95% CI 1.16 to 2.81), chronic lung disease (hazard ratio 2.06, 95% CI 1.23 to 3.46), previous AMI (hazard ratio 1.85, 95% CI 1.16 to 2.94), ejection fraction ⬍40% (hazard ratio 3.03, 95% CI 2.17 to 5.03), no revascularization (hazard ratio 2.56, 95% CI 1.61 to 4.07), and glomerular filtration rate (per 10 ml/min decrease; hazard ratio 1.18, 95% CI 1.08 to 1.30; Figure 3). The c-statistic for the final model was 0.81. To better illuminate the relation between anemia at admission and long-term mortality, a secondary analysis was conducted using the same multivariable model. Anemia on admission was not significantly associated with mortality (hazard ratio 1.44, 95% CI 0.87 to 2.39, for those with mild anemia; hazard ratio 1.38, 95% CI 0.72 to 2.62, for those
Figure 2. Adjusted 2-year all cause mortality by hematocrit group and controlled for age, gender, race, diabetes, chronic obstructive pulmonary disease/ asthma, renal function, previous AMI, left ventricular dysfunction, and treatment group (medical therapy only vs percutaneous revascularization).
Coronary Artery Disease/Anemia and Survival After ACS
Figure 3. Hazard ratios. GFR ⫽ glomerular filtration rate. Other abbreviation as in Figure 1.
with moderate/severe anemia). A subgroup analysis compared hazard ratios between patients who were consistently anemic (admission and discharge) and those who had newonset anemia (discharge only; Figure 4). Among patients who had mild anemia at discharge, there were no significant differences in survival based on their anemia status at admission (hazard ratio 1.92, 95% CI 0.82 to 4.51, for those without anemia; hazard ratio 1.66, 95% CI 0.81 to 3.42, for those with mild or moderate/severe anemia). Conversely, moderate/severe anemia at discharge was associated with decreased survival for patients who had consistent anemia (hazard ratio 2.63, 95% CI 1.27 to 5.42) or new-onset anemia (hazard ratio 3.05, 95% CI 1.03 to 9.06). The substantially greater effect of anemia at discharge on mortality suggests that this is a much more important determinant of outcome than the presence of anemia at admission. •••
Figure 4. Adjusted hazard ratios for anemia at admission/discharge (any ⫽ mild or moderate/severe anemia at admission; none ⫽ no anemia at admission; mild ⫽ mild anemia at discharge; severe ⫽ moderate/severe anemia at discharge).
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This study demonstrates that moderate/severe anemia (hematocrit ⱕ33%) at hospital discharge is independently associated with a 2.5-fold greater odds of dying within 2 years of admission for ACS. Further, we demonstrated that, whereas anemia immediately before discharge was associated with survival, anemia assessed at the time of initial clinical presentation was not. These findings were independent of numerous other potentially confounding factors and provide new insights to the current controversy that surrounds the association of anemia with survival after ACS. A previous study by Wu et al3 of an observational cohort of elderly patients who had AMI showed that admission hematocrit level was correlated with adjusted inpatient and 30-day mortality. Although this study used admission hematocrit as the variable of interest, it also included inpatient mortality. Our findings of a nonsignificant trend for admission hematocrit associated with 2-year survival were consistent with the statistically significant observations of this much larger study (n ⫽ 78,974). Our work extends this previous effort by showing a continuing divergence of the survival curves beyond 30 days and by clarifying the greater importance of discharge hematocrit on prognosis. Such findings were consistent with the findings of Wu et al,3 that patients who had anemia and received a blood transfusion (presumably improving their hematocrit at discharge) had better short-term survival than those who did not receive a transfusion. Further research to clarify the value of treating patients who have anemia at discharge to improve their hematocrit is needed to explore the potential of further improving their prognosis. 1. Al Falluji N, Lawrence-Nelson J, Kostis JB, Lacy CR, Ranjan R, Wilson AC. Effect of anemia on 1-year mortality in patients with acute myocardial infarction. Am Heart J 2002;144:636 – 641. 2. Anand I, McMurray JJ, Whitmore J, Warren M, Pham A, McCamish MA, Burton PB. Anemia and its relationship to clinical outcome in heart failure. Circulation 2004;110:149 –154. 3. Wu WC, Rathore SS, Wang Y, Radford MJ, Krumholz HM. Blood transfusion in elderly patients with acute myocardial infarction. N Engl J Med 2001;345:1230 –1236. 4. Rao SV, Jollis JG, Harrington RA, Granger CB, Newby LK, Armstrong PW, Moliterno DJ, Lindblad L, Pieper K, Topol EJ, et al. Relationship of blood transfusion and clinical outcomes in patients with acute coronary syndromes. JAMA 2004;292:1555–1562. 5. Alpert JS, Thygesen K, Antman E, Bassand JP. Myocardial infarction redefined—a consensus document of the Joint European Society of Cardiology/American College of Cardiology Committee for the redefinition of myocardial infarction. J Am Coll Cardiol 2000;36:959 –969. 6. Braunwald E. Unstable angina. A classification. Circulation 1989;80: 410 – 414. 7. Nutritional Anaemias. Report of a WHO Scientific Group. WHO Technical Report Series. Geneva: World Health Organization, 1968. 8. Hebert PC, Wells G, Blajchman MA, Marshall J, Martin C, Pagliarello G, Tweeddale M, Schweitzer I, Yetisir E. A multicenter, randomized, controlled clinical trial of transfusion requirements in critical care. Transfusion Requirements in Critical Care Investigators, Canadian Critical Care Trials Group. N Engl J Med 1999;340:409 – 417.