| | Does aspirin use adversely influence intermediate-term postdischarge outcomes for hospitalized patients who are treated with angiotensin-converting enzyme inhibitors or angiotensin receptor blockers? Findings from Organized Program to Facilitate Life-Saving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF)Received 29 September 2009; accepted 11 November 2009. BackgroundConflicting data exist regarding a potential deleterious association between aspirin (ASA) and angiotensin-converting enzyme inhibitors (ACEIs) when used concurrently in patients with heart failure (HF). How such an interaction may be influenced by underlying etiology of HF and whether it extends to patients treated with angiotensin receptor blockers (ARBs), however, are not known. MethodsEligible patients from the OPTIMIZE-HF registry were dichotomized into those with ischemic or nonischemic HF. Potential associations between ASA and ACEI or ARB use and 60- to 90-day postdischarge outcomes were assessed using Cox proportional and logistic regression modeling. Models were adjusted for factors known to influence the outcome of interest and by propensity score for ACEI or ARB prescription after an index HF admission. ResultsMortality was not increased (hazard ratio [95% CI]) when ASA was used in conjunction with ACEI (0.51 [0.29-0.87]) or ARB (0.29 [0.09-0.96]) in patients with ischemic or nonischemic (ACEI 0.71 [0.42-1.21], ARB 1.42 [0.74-2.74]) HF. Regression model parameter estimates trended toward harm reduction, but interaction terms for mortality and a composite of mortality or rehospitalization were nonsignificant (P for all >.05). ConclusionsWhen combined with ACEI or ARB, ASA had no demonstrable adverse effect on intermediate-term postdischarge outcomes for patients with ischemic or nonischemic HF. Aspirin (ASA) and angiotensin-converting enzyme inhibitors (ACEIs) are frequently used in patients with heart failure (HF). Several animal and human studies, however, have reported a potential deleterious association when these 2 agents are used in conjunction.1, 2, 3, 4, 5, 6, 7 The mechanism for this hypothesized adverse interaction is thought to involve disparate effects at the prostaglandin level, with ASA causing an attenuation of ACEI-mediated bradykinin potentiation.7, 8, 9, 10 Theoretical consequences of this include a reduction of bradykinin-induced systemic arterial vasodilatation and a loss of beneficial bradykinin-related cardiac remodeling effect by ACE inhibition, both of which may be magnified in patients with HF who often have up-regulation of bradykinin receptors.8 Nonetheless, whether these effects impart a clinically important detriment remains a matter of controversy.11, 12, 13, 14, 15 Angiotensin receptor blockers (ARBs) have emerged in the past decade as an alternative to ACEIs for management of patients with hypertension and HF.16, 17, 18 Although ARBs produce a hemodynamic effect similar to ACEIs, they do so independent of the bradykinin pathway. It would seem, therefore, that ARBs are less likely to be affected by concurrent ASA therapy; but published data on the interaction (if any) between these agents are nonexistent. To address this uncertainty, we sought to investigate the effect of ASA on intermediate-term (60- to 90-day postdischarge) outcomes for patients hospitalized with acute HF who are treated with ACEIs or ARBs. Because existing evidence strongly supports the use of ASA in patients with underlying coronary artery disease (CAD) or ischemic heart disease,19, 20, 21, 22 we divided, a priori, our study population into 2 cohorts based on documented etiology of HF (ischemic vs nonischemic). Methods  Study design This study was designed as a retrospective analysis of the Organized Program to Facilitate Life-Saving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF) registry. The rationale and design of OPTIMIZE-HF have been discussed in detail elsewhere.23 In brief, OPTIMIZE-HF was a performance improvement program for patients hospitalized with HF. Using uniform case ascertainment methodology,23, 24 OPTIMIZE-HF compiled a comprehensive database of important characteristics (demographic, pathophysiologic, and clinical), treatment patterns, and outcomes for 48,612 hospitalized patients with HF. Data collection was monitored and coordinated independent of the registry sponsor (GlaxoSmithKline, Philadelphia, PA ) by Outcome Sciences, Inc (Cambridge, MA). A prespecified 10% of the total OPTIMIZE-HF population was selected for 60- to 90-day follow-up, and incident data on mortality and rehospitalization were prospectively collected. Baseline characteristics and outcomes for the follow-up population (n = 5,791) have been previously described.24 Each participating center (n = 259) was required to have institutional review board approval of the OPTIMIZE-HF protocol before study initiation. For hospitals that participated in follow-up data collection (n = 91), written informed consent was mandatory. Because this present study examined previously collected deidentified data, approval was granted by the Wayne State University School of Medicine (Detroit, MI) Human Investigations Committee with exemption from full board review. Study population This analysis focused on patients >18 years of age who participated in follow-up data collection, survived to hospital discharge without transfer to another short-term hospital or hospice, were not enrolled in a clinical trial testing alternatives to ACEIs as first-line therapy, and did not have contraindications to ACEI or ARBs at discharge (n = 5,701). Within this pool, patients were dichotomized by documented HF etiology into ischemic (n = 2,411) and nonischemic (n = 3,290) cohorts. Six subgroups were then formulated within each cohort based on discharge medications as follows: no ASA, ACEI, or ARB; ASA only; ACEI only; ARB only; ASA plus ACEI; and ASA plus ARB. Because of limited representation in both the ischemic (n = 40) and nonischemic (n = 69) cohorts, patients discharged on all 3 medications (ie, ASA, ACEI, and ARB) or a combination of ACEI and ARB without ASA were excluded from the final analysis. Outcome measures Outcomes of interest were death and a composite of death or rehospitalization within 90 days of discharge from the hospital after an episode of acute decompensated HF. To avoid the issue of competing risk, rehospitalization was not considered as an individual outcome. Statistical analysis Descriptive analyses were performed for the overall study population and ischemic/nonischemic cohorts. Relevant data are reported by mean with SD or median with interquartile range for continuous variables and percentages of nonmissing values for categorical variables. Within each cohort, patient characteristics and treatments were compared across predefined subgroups using Pearson χ2 test for categorical variables and Kruskal-Wallis test for continuous variables. Heart failure medication use and contraindications or intolerance were assessed at discharge from the index hospital stay and during follow-up. Unadjusted analyses were performed in 3 groups based on discharge medications as follows: patients on ASA only, patients on ACEIs only, and patients on ARBs only. Unadjusted Kaplan-Meier survival curves were derived, and the log-rank test was used to compare the survival distribution among groups. The numbers at risk are included to indicate the completeness of follow-up through 90 days. The results of the univariate analysis are presented as hazard ratio (HR) with corresponding 95% CI for the mortality model and odds ratio (OR) with 95% CI for the composite model. Adjusted analyses were performed using Cox proportional hazards regression models for postdischarge death and logistic regression models for the combination of postdischarge death and rehospitalization (as date of event was not available). For modeling purposes, discharge use of ASA, ACEIs, or ARBs (as 3 main effects) and interactions between any of 2 medications were forced into previously derived and validated OPTIMIZE-HF models of mortality and a composite of mortality or rehospitalization (Table I).24 Patients with missing data for model covariates were excluded from adjusted analyses. Comparison between patients included (mortality = 4,732 [83%], composite = 3,784 [66.4%]) and excluded (mortality = 969 [17%], composite = 1,917 [33.6%]) in multivariable modeling revealed no significant differences in baseline characteristics or outcomes (data not shown). Results of multivariable analysis are presented as HR with corresponding 95% CI for the mortality model and OR with 95% CI for the composite model. | | |  | Mortality model | |
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| Admission SBP, per 10–mm Hg increase, up to 140 mm Hg | | | Admission SCr <4 mg/dL, per unit increase, up to 4 mg/dL | | | Age, per 10-y increase | | | History of pulmonary reactive airway disease | | | Admission weight (per 10-kg increase) | | | Lower extremity edema | | | Discharge medications—lipid-lowering agent | | | Sodium, per 1-U increase, up to 140 mEq/L | | | History of depression | | | Discharge SBP, per 10–mm Hg increase, up to 130 mm Hg | | | Liver disease | | | Admission SBP, per 10–mm Hg increase, >140 mm Hg | | | Discharge medications—any β-blocker | | | Propensity score for ACEI or ARB use at discharge | | | | | | Composite model | | | Admission hemoglobin (up to 11 g/dL) | | | Admission SCr up to and including 3.8 mg/dL | | | Admission SCr >3.8 mg/dL | | | Admission medications—diuretic | | | History of pulmonary disease (COPD, reactive airway disease) | | | >0 HF hospitalizations in past 6 m | | | Admission medications—nitrates | | | Admission medications—digoxin | | | History of CVA/TIA | | | Admission SBP (in increments of 10 mm Hg) | | | Coronary angiography performed during hospitalization | | | Mechanical ventilation performed during hospitalization | | | AICD placed during hospitalization | | | Discharge medication—lipid-lowering agent | | | History of liver disease | | | Left ventricular systolic dysfunction | | | Propensity score for ACEI or ARB use at discharge | | | | |
Propensity score analysis was performed to account for potential medication selection bias. The linearity assumption for continuous measures was evaluated using restricted cubic spline transformations. When needed, appropriate transformations such as piecewise linear splines were applied. A P value of .05 was used for both entry and retention in the final propensity score model (Table II), and the propensity score was included as a covariate in mortality and composite models. In addition, the general estimating equation was used to account for within-hospital clustering of characteristics in both models; and sensitivity analysis was conducted to explore the impact of ACEI or ARB eligibility on observed medication effects. The correlation within hospital was taken into account with the use of robust-sandwich standard error estimate for the regression coefficients in models. SAS version 8.2 (SAS Institute Inc, Cary, NC) was used for all statistical analyses. | Primary cause of admission—HF | | | Admission characterization of HF—pulmonary congestion | | | Other conditions for HF—noncompliance with medications | | | Admission symptom—palpitations | | | White | | | Peripheral vascular disease | | | Renal disorder | | | No known HF before this admission | | | Rales | | | Admission medications | | |  Any β-blocker | | | ACEI | | | Aldosterone antagonist | | | ARB | | | Digoxin | | | Diuretic | | | Diastolic blood pressure (10 mm Hg) | | | Admission hemoglobin (in g/dL) | | | Age <70 y | | | Heart beat ≥120 beat/min | | | Admission serum creatinine up to 4 mg/dL | | | Coronary angiography performed during hospitalization | | | Dialysis performed during hospitalization | | | Left ventricular assist device placed during hospitalization | | | Pacemaker placed during hospitalization | | | Right cardiac catheterization performed during hospitalization | | | | |
All analyses were performed independently by the Duke Clinical Research Institute (Durham, NC), and no extramural funding was used to support this work. The authors are solely responsible for the design and conduct of this study, the drafting and editing of the paper, and its final contents. All authors have read and agree to the manuscript as written. Results Patient characteristics Baseline characteristics for the overall study population (n = 5,701) as well as the ischemic (n = 2,411) and the nonischemic (n = 3,290) cohorts are presented in Table III. In general, patients with ischemic HF were slightly older (mean age 73.7 ± 11.3 vs 70.8 ± 15.2 years); less likely to be female (39.9% vs 55.3%) or black (11.8% vs 23.2%); and more likely to have CAD/ischemic heart disease (80.2% vs 27.8%), diabetes mellitus (combined type 1 and type 2 48.1% vs 38.7%), or hyperlipidemia (48.7% vs 33.0%) than those with a nonischemic etiology. Patients with ischemic HF were also more frequently hospitalized in the preceding 6 months for HF (41.8% vs 32.4%), less hypertensive on admission (mean systolic blood pressure 136.2 ± 30.3 vs 144.4 ± 33.2 mm Hg), and more frequently on a β-blocker or statin therapy on admission (63.0% vs 48.8% and 49.2% vs 27.1%, respectively) and at discharge (71.4% vs 65.3% and 52.6% vs 29.3%, respectively). In addition, patients with ischemic HF had a lower mean (SD) left ventricular ejection fraction (LVEF) than those with nonischemic disease (33.7% [15.2] vs 39.5% [17.9]); and a greater proportion (65.6% vs 50.0%) had left ventricular systolic dysfunction (LVSD, defined as LVEF <40%). | | | | | Overall study population | Ischemic cohort | Nonischemic cohort | |
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| No. of patients (%) | 5701 | 2411 (42.3) | 3290 (57.7) | | | Mean age, y (SD) | 72.0 (13.8) | 73.7 (11.3) | 70.8 (15.2) | | | Female, n (%) | 2782 (48.8) | 961 (39.9) | 1821 (55.3) | | | White, n (%) | 4446 (78.0) | 2051 (85.1) | 2395 (72.8) | | | Black, n (%) | 1040 (18.2) | 283 (11.8) | 757 (23.2) | | | Hispanic, n (%) | 113 (2.0) | 56 (2.3) | 57 (1.7) | | | Mean LVEF, % (SD) | 36.9 (17.0) | 33.7 (15.2) | 39.5 (17.9) | | | LVEF <40%, n (% of those with LVEF assessed) | 2592 (57.0) | 1346 (65.6) | 1246 (50.0) | | | Hospitalized for HF in prior 6 m, n (%) | 1681 (36.5) | 842 (41.8) | 839 (32.4) | | | Type 2 diabetes mellitus, n (%) | 1481 (26.0) | 689 (28.6) | 792 (24.1) | | | Type 1 diabetes mellitus, n (%) | 951 (16.7) | 471 (19.5) | 480 (14.6) | | | History of CAD/ischemic heart disease, n (%) | 2848 (50.0) | 1933 (80.2) | 915 (27.8) | | | Hyperlipidemia, n (%) | 2259 (39.6) | 1174 (48.7) | 1085 (33.0) | | | Atrial arrhythmia, n (%) | 1192 (33.5) | 833 (34.5) | 1079 (31.9) | | | COPD, n (%) | 1741 (30.5) | 692 (28.7) | 1049 (31.9) | | | Reactive airway disease, n (%) | 484 (8.5) | 113 (4.7) | 371 (11.3) | | | Smoker within past year, n (%) | 1041 (18.9) | 413 (17.8) | 628 (19.7) | | | Chronic kidney disease, n (%) | 1154 (20.2) | 504 (20.9) | 650 (19.8) | | | Peripheral vascular disease, n (%) | 903 (15.8) | 440 (18.2) | 463 (14.1) | | | Hypertension, n (%) | 4111 (72.1) | 1680 (69.7) | 2431 (73.9) | | | Depression, n (%) | 773 (13.6) | 269 (11.2) | 504 (15.3) | | | Liver disease, n (%) | 126 (2.2) | 32 (1.3) | 94 (2.9) | | | Thyroid abnormality, n (%) | 950 (16.7) | 387 (16.1) | 563 (17.1) | | | History of prior CVA/TIA, n (%) | 874 (15.3) | 401 (16.6) | 473 (14.4) | | | Admission rales, n (%) | 3467 (62.1) | 1506 (63.9) | 1961 (60.7) | | | Admission lower extremity edema, n (%) | 3629 (65.1) | 1511 (64.3) | 2118 (65.6) | | | Mean admission SBP, mm Hg (SD) | 140.9 (32.2) | 136.2 (30.3) | 144.4 (33.2) | | | Median admission SCr, mg/dL (IQR) | 1.3 (1.0, 1.8) | 1.4 (1.1, 1.8) | 1.2 (1.0, 1.7) | | | Mean admission Hgb, g/dL (SD) | 12.2 (2.1) | 12.1 (2.0) | 12.3 (2.1) | | | Mean admission sodium, mEq/L (SD) | 137.6 (4.6) | 137.7 (4.7) | 137.6 (4.5) | | | Median admission BNP, pg/mL (IQR) | 815.0 (424.0, 1700.0) | 946.0 (484.6, 2030.0) | 733.5 (381.0, 1490.0) | | | Median admission troponin, ng/mL (IQR) | 0.2 (0.1, 0.4) | 0.2 (0.1, 0.4) | 0.2 (0.1, 0.4) | | | Median admission weight, kg (IQR) | 80.0 (66.0, 97.5) | 80.0 (67.1, 96.1) | 80.0 (65.3, 98.4) | | | Median weight change, kg (IQR) | −1.8 (−4.5, 0.0) | −2.0 (−4.5, 0.0) | −1.8 (−4.5, 0.0) | | | Admission β-blocker, n (%) | 3113 (54.6) | 1520 (63.0) | 1593 (48.4) | | | Admission ACEI, n (%) | 2372 (41.6) | 1100 (45.6) | 1272 (38.7) | | | Admission ARB, n (%) | 706 (12.4) | 293 (12.2) | 413 (12.6) | | | Admission diuretic, n (%) | 3885 (68.1) | 1752 (72.7) | 2133 (64.8) | | | Admission digoxin, n (%) | 1395 (24.5) | 672 (27.9) | 723 (22.0) | | | Admission statin, n (%) | 2079 (36.5) | 1187 (49.2) | 892 (27.1) | | | Mean discharge SBP, mm Hg (SD) | 123.9 (22.4) | 121.8 (22.0) | 125.4 (22.5) | | | Median discharge BNP, pg/dL (IQR) | 575.5 (296.0, 1180.0) | 667.5 (357.5, 1390.0) | 504.0 (258.2, 1067.0) | | | Discharge β-blocker, n (%) | 3847 (67.9) | 1711 (71.4) | 2136 (65.3) | | | Discharge diuretic, n (%) | 4687 (82.2) | 2012 (83.5) | 2675 (81.3) | | | Discharge digoxin, n (%) | 1701 (29.9) | 766 (31.8) | 936 (28.4) | | | Discharge statin, n (%) | 2232 (39.2) | 1346 (55.8) | 964 (29.3) | | | | |
Marginal distribution of medication use at discharge for the ischemic and nonischemic cohorts is presented in Figure 1, A and B. Most patients in the ischemic cohort were discharged on combination therapy with ACEI and ASA (n = 837, 35.3%), whereas in the nonischemic cohort, monotherapy with ACEI was most common (n = 973, 30.2%). A relatively high proportion of patients in the ischemic (n = 383, 16.1%) and nonischemic (n = 730, 22.7%) cohorts, however, were discharged without prescription for ASA, ACEI, or ARB. Baseline characteristics for patients who received ACEI alone, ARB alone, ACEI plus ASA, and ARB plus ASA by cohort are presented in Tables IV and V in an accompanying online supplement. Statistically significant intergroup differences existed for patients within both cohorts for a number of variables including age; LVEF; smoking status; history of atrial arrhythmia, chronic kidney disease, or peripheral vascular disease; admission serum creatinine, hemoglobin, and sodium; body weight; use of ACEI, ARB, or statins; and discharge use of β-blockers, diuretics, or statins. Mortality model A total of 2,018 patients (84.0%) in the ischemic cohort and 2,714 (82.4%) in the nonischemic cohort were eligible for inclusion in mortality models. Among these patients, 343 (7.2%) deaths occurred during the follow-up period, with relatively equal distribution between the ischemic (n = 141, 7.0%) and the nonischemic (n = 202, 7.4%) cohorts. Overall and by cohort, survival was lowest for patients who were not prescribed ASA, ACEIs, or ARBs at discharge (unadjusted Kaplan-Meier curves provided in Figure 2, A-C). For patients with ischemic HF, unadjusted hazard of mortality was lower (HR [95% CI]) with individual use of all 3 medications at the time of hospital discharge (ACEI 0.55 [0.39-0.77], ARB 0.35 [0.17-0.72], and ASA 0.70 [0.50-0.96]); but in those with a nonischemic etiology, only ACEI appeared to confer benefit (ACEI 0.46 [0.34-0.62], ARB 0.82 [0.61-1.10], and ASA 0.78 [0.51-1.18]). After multivariable adjustment, neither ACEI nor ARB (as individual factors without ASA) had any clear effect on mortality in both ischemic (1.04 [0.62-1.75] and 0.62 [0.24-1.59]) and nonischemic (0.77 [0.51-1.16] and 0.88 [0.49-1.58]) cohorts. For ischemic patients, ASA combined with ACEI (0.51 [0.29-0.87]) or ARB (0.29 [0.09-0.96]) appeared to provide some measure of hazard reduction; but the interaction parameter estimates (ACEI and ASA −0.72 [P = .09], ARB and ASA −0.75 [P = .33]) did not achieve statistical significance. For nonischemic patients, the addition of ASA to ACEI (0.71 [0.42-1.21]) or ARB (1.42 [0.74-2.74]) therapy did not appear to increase or decrease hazard; but again, the interaction parameter estimates were not statistically significant (ACEI and ASA −0.08 [P = .74], ARB and ASA −0.48 [P = .22]). Composite model Fewer patients in the ischemic (1,706 [71.1%]) and nonischemic (2,078 [63.2%]) cohorts were eligible for inclusion in composite outcome analysis. A total of 1,397 (36.9%) events occurred in these patients, with similar rates in the ischemic (38.9%, n = 664) and nonischemic (35.3%, n = 733) cohorts. Unadjusted risk (OR [95% CI]) of the composite outcome was lower in both ischemic and nonischemic patients with HF who received ACEIs (0.65 [0.53-0.80] and 0.62 [0.51-0.75]) or ARBs (0.60 [0.43-0.85] and 0.67 [0.50-0.90]) at discharge but not ASA (0.93 [0.76-1.14] and 0.96 [0.80-1.16]). On multivariable modeling, odds of the composite outcome remained lower in ischemic patients who received ACEI (0.72 [0.55-0.96]) and ARB (0.71 [0.51-1.00]) at discharge but not ASA (1.03 [0.85-1.25]). In nonischemic patients, the direction and relative magnitude of the univariate association between all 3 medications and outcome were unchanged (ACEI 0.70 [0.54-0.90], ARB 0.70 [0.54-0.92], and ASA 0.98 [0.84-1.15]). For both cohorts, there was no statistical evidence of an interaction between ASA and ACEI (P [ischemic] = .18 and P [nonischemic] = .63) or ARB (P [ischemic] = .12 and P [nonischemic] = .76). Discussion In this study of the OPTIMIZE-HF registry, ASA use did not adversely influence 60- to 90-day outcomes for patients hospitalized with acute HF who were prescribed concurrent ACEI or ARB therapy at discharge. For postdischarge mortality, the addition of ASA actually trended towards benefit; but as evidenced by the width of related CIs, our analysis was probably underpowered to examine this interaction as a 2-sided occurrence. These findings extended to all patients with HF irrespective of underlying etiology (ischemic or nonischemic) and were independent of potential interhospital variability or propensity for ACEI or ARB use at discharge. Results of this study support the notion that in actual clinical practice ASA does not appear to exert a deleterious effect on outcomes associated with ACEI in patients with HF, but the existence of contradictory data renders the issue a matter of ongoing debate. In the Studies of Left Ventricular Dysfunction trial, for example, a reduction in the expected individual contributory survival benefit from both enalapril and ASA was found when the 2 medications were used in combination.1 A subsequent meta-analysis, however, combining the Studies of Left Ventricular Dysfunction data with the results of 5 other long-term randomized clinical trials of ACEIs found no evidence of an interaction between ASA and ACEI (P = .07) and a clear reduction in risk of major clinical outcomes for patients who received ASA at baseline (OR 0.80 [99% CI 0.73-0.88]) and those who did not (OR 0.71 [99% CI 0.62-0.81]).25 More recently, 2 clinical trials that prospectively evaluated antithrombotic therapy in patients with HF (The Warfarin/Aspirin Study in Heart Failure26 and The Warfarin and Antiplatelet Therapy in Chronic Heart Failure27 trials) reported an increase in HF admissions among individuals who received ASA. Of importance, these studies were all clinical trials conducted in an outpatient setting with chronic HF patients who had LVSD. Because our data were derived from a registry that included all patients with HF rather than those who meet stringent inclusion and exclusion criteria, they are more likely to reflect the general population and, consequently, real-world outcomes. Although OPTIMIZE-HF did not collect data beyond the intermediate-term (60 to 90 days) postdischarge period, our results are remarkably consistent with recently published findings from the Enhanced Feedback for Effective Cardiac Treatment study, which noted that, among patients (n = 7,352, 56% with an ischemic etiology) discharged after a first hospitalization for HF, users of ACEIs were less likely to die or require HF readmission in the ensuing year than nonusers, even if they were receiving ASA.28 The absence of an interaction between ASA and ACEIs was persistent in a number of subgroups including patients who had no history of CAD. This, combined with data from the National Heart Care Project, which showed no attenuation of benefit in Medicare patients with CAD discharged on ACEI and ASA after hospitalization for acute HF,29 supports the consistency we found in apparent lack of interaction across HF etiologies. Potential adverse effects of ASA when used in conjunction with ARBs have been less well investigated and remain poorly defined. Because of pharmacologic properties that differ from ACEIs; however, one would expect a lower likelihood of interaction; and our study shows that, for intermediate-term outcomes, this is indeed true. The only other existing data come from a subgroup analysis of the Candesartan in Heart failure Assessment of Reduction in Mortality and morbidity study that reported no modification of the beneficial effects of candesartan on cardiovascular death or HF rehospitalization by ASA over 37.7 months of follow-up.30 Similar to our study, outcomes did not differ based on etiology of HF or by LVEF, indicating that combined treatment with ASA and ARBs can be considered with limited concern for interaction in a broad range of patients with HF. Study limitations Our study was subject to several important limitations. Although follow-up patients in OPTIMIZE-HF were identified prospectively, ASA use was not randomly assigned. Consequently, our results should not be viewed as reflective of an adequately powered clinical trial and cannot be interpreted as definitive evidence of a cause-and-effect relationship. In addition, despite covariate adjustment for a number of factors including LVSD and propensity matching, other measured or unmeasured variables may have influenced observed clinical outcomes. Among these, patient compliance with prescribed medications, prescribed duration and dosing of medications at discharge, and untracked alterations in outpatient therapy (especially ASA, ACEI, or ARB dose adjustments) may be particularly important. Furthermore, although we did account for potential variability in hospital characteristics and clustering of events using the general estimating equation, applicability of these data is limited to facilities that are similar to participating OPTIMIZE-HF institutions (described elsewhere24). Lastly, 90-day outcomes may not capture potential drug effects on cardiac remodeling and chronic hemodynamics, both of which may impact protracted morbidity and mortality for patients with HF. Conclusions Data from this study of a broad cohort of patients with HF from all regions of the country suggest that use of ASA is not associated with a statistically significant adverse effect on intermediate-term postdischarge outcomes when combined with ACEI or ARB therapy in either ischemic or nonischemic patients with HF. Disclosures The OPTIMIZE-HF registry was funded by GlaxoSmithKline, Philadelphia, PA. Gregg C. Fonarow, MD, reported that he has served as a consultant for GlaxoSmithKline (modest) and received honorarium from GlaxoSmithKline (significant). Appendix A. Online supplement | | | | | ACEI only | ARB only | ACEI + ASA | ARB + ASA | P | |
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| No. of patients (% overall) | 469 (19.8) | 104 (4.4) | 837 (35.3) | 139 (5.9) | | | | Mean age, y (SD) | 73.2 (11.7) | 75.1 (10.8) | 72.7 (11.5) | 73.9 (10.0) | .002 | | | Female, n (%) | 186 (39.7) | 51 (49.0) | 325 (38.8) | 62 (54.3) | .231 | | | White, n (%) | 391 (85.2) | 89 (87.3) | 676 (83.6) | 119 (87.5) | .164 | | | Black, n (%) | 57 (12.2) | 13 (12.6) | 115 (13.9) | 14 (10.2) | .063 | | | Hispanic, n (%) | 9 (1.9) | 2 (1.9) | 21 (2.5) | 2 (1.4) | .813 | | | Mean LVEF, % (SD) | 32.1 (14.3) | 35.0 (14.2) | 31.6 (14.2) | 35.8 (17.3) | <.001 | | | LVEF <40%, n (% of those with LVEF assessed) | 276 (68.1) | 48 (60.0) | 553 (73.8) | 71 (61.9) | <.001 | | | Hospitalized for HF in prior 6 m, n (%) | 161 (40.8) | 30 (36.1) | 293 (41.9) | 46 (40.7) | .656 | | | Type 2 diabetes mellitus, n (%) | 137 (29.2) | 33 (31.7) | 250 (29.9) | 41 (29.5) | .636 | | | Type 1 diabetes mellitus, n (%) | 78 (16.6) | 18 (17.3) | 159 (19.0) | 35 (25.2) | .156 | | | History of CAD/ischemic heart disease, n (%) | 366 (78.0) | 85 (81.7) | 677 (80.9) | 118 (84.9) | .114 | | | Hyperlipidemia, n (%) | 233 (49.7) | 51 (49.0) | 408 (48.7) | 76 (54.7) | .644 | | | Atrial arrhythmia, n (%) | 208 (44.3) | 43 (41.3) | 239 (28.6) | 42 (30.2) | <.001 | | | COPD, n (%) | 131 (27.9) | 26 (25.0) | 213 (25.4) | 35 (25.2) | .006 | | | Reactive airway disease, n (%) | 27 (5.8) | 7 (6.7) | 32 (3.8) | 10 (7.2) | .341 | | | Smoker within past year, n (%) | 92 (20.4) | 14 (14.0) | 175 (21.7) | 13 (9.8) | <.001 | | | Chronic kidney disease, n (%) | 68 (14.5) | 20 (19.2) | 113 (13.5) | 30 (21.6) | <.001 | | | Peripheral vascular disease, n (%) | 81 (17.3) | 18 (17.3) | 141 (16.8) | 23 (16.5) | .248 | | | Hypertension, n (%) | 333 (71.0) | 72 (69.2) | 601 (71.8) | 107 (139) | .07 | | | Depression, n (%) | 46 (9.8) | 14 (13.5) | 92 (11.0) | 17 (12.2) | .490 | | | Liver disease, n (%) | 5 (1.1) | 1 (1.0) | 9 (1.1) | 3 (2.2) | .672 | | | Thyroid abnormality, n (%) | 73 (15.6) | 19 (18.3) | 116 (13.9) | 30 (21.6) | .163 | | | History of prior CVA/TIA, n (%) | 67 (14.3) | 18 (17.3) | 150 (17.9) | 21 (15.1) | .627 | | | Admission rales, n (%) | 288 (63.0) | 71 (68.9) | 533 (64.8) | 90 (65.2) | .787 | | | Admission lower extremity edema, n (%) | 293 (64.4) | 67 (66.3) | 532 (65.0) | 87 (64.0) | .991 | | | Mean admission SBP, mm Hg (SD) | 136.1 (31.1) | 139.3 (30.7) | 136.0 (28.9) | 140.5 (33.0) | .064 | | | Median admission SCr, mg/dL (IQR) | 1.3 (1.0, 1.7) | 1.4 (1.1, 1.8) | 1.2 (1.0, 1.6) | 1.4 (1.1, 1.8) | <.001 | | | Mean admission Hgb, g/dL (SD) | 12.2 (2.1) | 11.8 (2.2) | 12.3 (2.0) | 12.2 (2.0) | .002 | | | Mean admission sodium, mEq/L (SD) | 137.8 (4.5) | 137.7 (4.9) | 138.2 (4.0) | 137.9 (4.6) | .003 | | | Median admission BNP, pg/mL (IQR) | 907.0 (516.0, 1,850.0) | 886.0 (518.0, 1,640.0) | 939.0 (518.0, 2,130.0) | 797.0 (437.0, 1,570.0) | .417 | | | Median admission troponin, ng/mL (IQR) | 0.2 (0.1, 0.4) | 0.2 (0.1, 0.3) | 0.2 (0.1, 0.4) | 0.2 (0.1, 0.5) | .098 | | | Median admission weight, kg (IQR) | 82.1 (66.0, 96.6) | 84.0 (67.8, 95.2) | 83.6 (67.1, 97.5) | 87.3 (71.0, 100.0) | .031 | | | Median weight change, kg (IQR) | −2.0 (−4.1, 0.0) | −1.8 (−4.1, 0.0) | −2.0 (−5.0, 0.0) | −2.0 (−4.1, −0.5) | .805 | | | Admission β-blocker, n (%) | 291 (62.0) | 65 (62.5) | 544 (65.0) | 94 (67.6) | .160 | | | Admission ACEI, n (%) | 331 (70.6) | 7 (6.7) | 582 (69.5) | 7 (5.0) | <.001 | | | Admission ARB, n (%) | 15 (3.2) | 79 (76.0) | 15 (1.8) | 101 (72.7) | <.001 | | | Admission diuretic, n (%) | 358 (76.3) | 78 (75.0) | 591 (70.6) | 102 (73.4) | .383 | | | Admission digoxin, n (%) | 159 (33.9) | 37 (35.6) | 224 (26.8) | 34 (24.5) | .008 | | | Admission statin, n (%) | 216 (46.1) | 50 (48.1) | 437 (52.2) | 78 (56.1) | .057 | | | Mean discharge SBP, mm Hg (SD) | 120.8 (21.6) | 123.9 (23.0) | 120.7 (21.8) | 124.0 (21.6) | .080 | | | Median discharge BNP, pg/dL (IQR) | 618.0 (329.4, 1,270.0) | 585.0 (297.0, 1,190.0) | 628.4 (382.0, 1,290.0) | 600.0 (292.0, 848.0) | .168 | | | Discharge β-blocker, n (%) | 332 (71.1) | 71 (68.9) | 659 (78.9) | 98 (70.5) | <.001 | | | Discharge diuretic, n (%) | 404 (86.1) | 90 (86.5) | 721 (86.1) | 122 (87.8) | <.001 | | | Discharge digoxin, n (%) | 177 (37.7) | 40 (38.5) | 285 (34.1) | 32 (23.0) | <.001 | | | Discharge statin, n (%) | 225 (48.0) | 53 (51.0) | 481 (57.5) | 86 (61.9) | <.001 | | | | |
| | | | | ACEI only | ARB only | ACEI + ASA | ARB + ASA | P | |
|---|
| No. of patients (% overall) | 973 (30.2) | 211 (6.6) | 778 (24.2) | 152 (4.7) | | | | Mean age, y (SD) | 68.3 (16.1) | 71.7 (14.5) | 69.6 (15.0) | 71.8 (13.3) | <.001 | | | Female, n (%) | 520 (53.4) | 124 (58.8) | 393 (50.5) | 89 (58.6) | .005 | | | White, n (%) | 671 (71.7) | 145 (73.2) | 509 (67.1) | 107 (73.8) | <.001 | | | Black, n (%) | 244 (25.4) | 46 (22.2) | 227 (29.3) | 32 (21.2) | <.001 | | | Hispanic, n (%) | 16 (1.6) | 5 (2.4) | 16 (2.1) | 2 (1.3) | .879 | | | Mean LVEF, % (SD) | 36.6 (17.5) | 41.9 (18.2) | 36.3 (17.70 | 40.1 (16.8) | <.001 | | | LVEF <40%, n (% of those with LVEF assessed) | 436 (56.9) | 67 (45.9) | 372 (58.9) | 61 (50.4) | <.001 | | | Hospitalized for HF in prior 6 m, n (%) | 236 (30.7) | 53 (31.0) | 190 (30.8) | 43 (36.4) | .544 | | | Type 2 diabetes mellitus, n (%) | 238 (24.5) | 57 (27.0) | 189 (24.3) | 42 (27.6) | .045 | | | Type 1 diabetes mellitus, n (%) | 127 (13.1) | 34 (16.1) | 107 (13.8) | 30 (19.7) | .324 | | | History of CAD/ischemic heart disease, n (%) | 253 (26.0) | 53 (25.1) | 229 (29.4) | 55 (36.2) | <.001 | | | Hyperlipidemia, n (%) | 324 (33.3) | 78 (37.0) | 275 (35.3) | 64 (42.1) | .001 | | | Atrial arrhythmia, n (%) | 326 (33.5) | 92 (43.6) | 180 (23.1) | 46 (30.3) | <.001 | | | COPD, n (%) | 298 (30.6) | 73 (34.6) | 221 (28.4) | 45 (29.6) | .057 | | | Reactive airway disease, n (%) | 115 (11.8) | 27 (12.8) | 86 (11.1) | 19 (12.5) | .756 | | | Smoker within past year, n (%) | 199 (21.1) | 34 (17.2) | 179 (23.6) | 27 (18.5) | .004 | | | Chronic kidney disease, n (%) | 165 (17.0) | 43 (20.4) | 99 (12.7) | 34 (22.4) | <.001 | | | Peripheral vascular disease, n (%) | 121 (12.4) | 38 (18.0) | 93 (12.0) | 30 (19.7) | .007 | | | Hypertension, n (%) | 711 (73.1) | 175 (82.9) | 593 (76.2) | 129 (84.9) | <.001 | | | Depression, n (%) | 134 (13.8) | 38 (18.0) | 108 (13.9) | 30 (19.7) | .165 | | | Liver disease, n (%) | 24 (2.5) | 0 (0.0) | 22 (2.8) | 3 (2.0) | .007 | | | Thyroid abnormality, n (%) | 158 (16.2) | 43 (20.4) | 110 (14.1) | 23 (15.1) | .031 | | | History of prior CVA/TIA, n (%) | 133 (13.7) | 38 (18.0) | 109 (14.0) | 31 (20.4) | .029 | | | Admission rales, n (%) | 575 (60.1) | 140 (68.3) | 486 (63.5) | 85 (56.7) | .002 | | | Admission lower extremity edema, n (%) | 637 (66.8) | 135 (64.0) | 496 (65.3) | 97 (65.5) | .797 | | | Mean admission SBP, mm Hg (SD) | 145.2 (34.4) | 146.7 (31.6) | 147.6 (32.4) | 146.7 (31.6) | <.001 | | | Median admission SCr, mg/dL (IQR) | 1.2 (1.0, 1.6) | 1.3 (1.0, 1.8) | 1.2 (0.9, 1.5) | 1.3 (1.1, 1.9) | <.001 | | | Mean admission Hgb, g/dL (SD) | 12.5 (2.2) | 12.1 (2.0) | 12.5 (2.0) | 12.2 (1.9) | <.001 | | | Mean admission sodium, mEq/L (SD) | 137.7 (4.3) | 137.3 (4.8) | 138.1 (4.4) | 137.1 (4.6) | <.001 | | | Median admission BNP, pg/mL (IQR) | 729 (368.0, 1,520.0) | 633.5 (393.0, 1,260.0) | 806.0 (435.0, 1,540.0) | 754.5 (359.9, 1,760.0) | .008 | | | Median admission troponin, ng/mL (IQR) | 0.2 (0.1, 0.3) | 0.3 (0.1, 0.5) | 0.2 (0.1, 0.4) | 0.2 (0.0, 0.3) | .018 | | | Median admission weight, kg (IQR) | 81.2 (66.2, 101.1) | 81.0 (64.9, 102.0) | 81.2 (66.0, 99.0) | 80.9 (64.4, 100.7) | .009 | | | Median weight change, kg (IQR) | −1.8 (−4.5, 0.0) | −1.8 (−4.1, 0.0) | −2.0 (−5.0, 0.0) | −1.8 (−3.6, 0.0) | .330 | | | Admission β-blocker, n (%) | 485 (49.8) | 111 (52.6) | 367 (47.2) | 88 (57.9) | .009 | | | Admission ACEI, n (%) | 614 (63.1) | 20 (9.5) | 430 (55.3) | 13 (8.6) | <.001 | | | Admission ARB, n (%) | 16 (1.6) | 150 (71.1) | 25 (5.1) | 113 (74.2) | <.001 | | | Admission diuretic, n (%) | 630 (64.7) | 163 (77.3) | 474 (60.9) | 106 (69.7) | <.001 | | | Admission digoxin, n (%) | 217 (22.3) | 46 (21.8) | 158 (20.3) | 30 (19.7) | .244 | | | Admission statin, n (%) | 243 (25.0) | 61 (28.9) | 238 (30.6) | 55 (36.2) | <.001 | | | Mean discharge SBP, mm Hg (SD) | 124.7 (22.6) | 127.7 (23.5) | 125.5 (22.0) | 126.7 (21.9) | .112 | | | Median discharge BNP, pg/dL (IQR) | 458.0 (244.0, 994.0) | 525.5 (293.0, 998.0) | 499.0 (288.0, 1000.0) | 786.5 (370.0, 1,180.0) | .107 | | | Discharge β-blocker, n (%) | 683 (70.3) | 141 (66.8) | 568 (73.1) | 114 (75.0) | <.001 | | | Discharge diuretic, n (%) | 819 (84.2) | 189 (89.6) | 671 (86.2) | 132 (86.8) | <.001 | | | Discharge digoxin, n (%) | 299 (30.7) | 65 (30.8) | 227 (29.2) | 37 (24.3) | .231 | | | Discharge statin, n (%) | 253 (26.0) | 61 (28.9) | 300 (38.6) | 59 (38.8) | <.001 | | | | |
References 1. 1Al-Khadra AS, Salem DN, Rand WM, et al. Antiplatelet agents and survival: a cohort analysis from the Studies of Left Ventricular Dysfunction (SOLVD) trial. J Am Coll Cardiol. 1998;31:419–425. Abstract | Full Text |
Full-Text PDF (115 KB)
|
CrossRef
2. 2Minshall RD, Tan F, Nakamura F, et al. Potentiation of the actions of bradykinin by angiotensin I–converting enzyme inhibitors. The role of expressed human bradykinin B2 receptors and angiotensin I–converting enzyme in CHO cells. Circ Res. 1997;81:848–856. MEDLINE 3. 3Nguyen KN, Aursnes I, Kjekshus J. Interaction between enalapril and aspirin on mortality after acute myocardial infarction: subgroup analysis of the Cooperative New Scandinavian Enalapril Survival Study II (CONSENSUS II). Am J Cardiol. 1997;79:115–119. Abstract | Full Text |
Full-Text PDF (209 KB)
|
CrossRef
4. 4Pellacani A, Brunner HR, Nussberger J. Plasma kinins increase after angiotensin-converting enzyme inhibition in human subjects. Clin Sci (Lond). 1994;87:567–574. MEDLINE 5. 5Spaulding C, Charbonnier B, Cohen-Solal A, et al. Acute hemodynamic interaction of aspirin and ticlopidine with enalapril: results of a double-blind, randomized comparative trial. Circulation. 1998;98:757–765. MEDLINE 6. 6Peterson JG, Topol EJ, Sapp SK, et al. Evaluation of the effects of aspirin combined with angiotensin-converting enzyme inhibitors in patients with coronary artery disease. Am J Med. 2000;109:371–377. Abstract | Full Text |
Full-Text PDF (143 KB)
|
CrossRef
7. 7Meune C, Mourad JJ, Bergmann JF, et al. Interaction between cyclooxygenase and the renin-angiotensin-aldosterone system: rationale and clinical relevance. J Renin Angiotensin Aldosterone Syst. 2003;4:149–154. MEDLINE |
CrossRef
8. 8Emanueli C, Maestri R, Corradi D, et al. Dilated and failing cardiomyopathy in bradykinin B(2) receptor knockout mice. Circulation. 1999;100:2359–2365. MEDLINE 9. 9Meune C, Mahe I, Mourad JJ, et al. Aspirin alters arterial function in patients with chronic heart failure treated with ACE inhibitors: a dose-mediated deleterious effect. Eur J Heart Fail. 2003;5:271–279. MEDLINE |
CrossRef
10. 10Schror K. Role of prostaglandins in the cardiovascular effects of bradykinin and angiotensin-converting enzyme inhibitors. J Cardiovasc Pharmacol. 1992;20(Suppl 9):S68–S73.
CrossRef
11. 11Brunner-La Rocca HP. Interaction of angiotensin-converting enzyme inhibition and aspirin in congestive heart failure: long controversy finally resolved?. Chest. 2003;124:1192–1194. MEDLINE |
CrossRef
12. 12Hall D. Controversies in heart failure. Are beneficial effects of angiotensin-converting enzyme inhibitors attenuated by aspirin in patients with heart failure?. Cardiol Clin. 2001;19:597–603. Full Text |
Full-Text PDF (598 KB)
|
CrossRef
13. 13Konstam MA. Aspirin and heart failure: square evidence meets a round patient. Congest Heart Fail. 2003;9:203–205. MEDLINE |
CrossRef
14. 14Massie BM. Aspirin use in chronic heart failure: what should we recommend to the practitioner?. J Am Coll Cardiol. 2005;46:963–966. Abstract | Full Text |
Full-Text PDF (77 KB)
|
CrossRef
15. 15Takkouche B, Etminan M, Caamano F, et al. Interaction between aspirin and ACE Inhibitors: resolving discrepancies using a meta-analysis. Drug Saf. 2002;25:373–378. MEDLINE |
CrossRef
16. 16Granger CB, McMurray JJ, Yusuf S, et al. Effects of candesartan in patients with chronic heart failure and reduced left-ventricular systolic function intolerant to angiotensin-converting-enzyme inhibitors: the CHARM-Alternative trial. Lancet. 2003;362:772–776. Abstract | Full Text |
Full-Text PDF (93 KB)
|
CrossRef
17. 17Pitt B, Poole-Wilson PA, Segal R, et al. Effect of losartan compared with captopril on mortality in patients with symptomatic heart failure: randomised trial—the Losartan Heart Failure Survival Study ELITE II. Lancet. 2000;355:1582–1587. Abstract | Full Text |
Full-Text PDF (99 KB)
|
CrossRef
18. 18Willenheimer R, Helmers C, Pantev E, et al. Safety and efficacy of valsartan versus enalapril in heart failure patients. Int J Cardiol. 2002;85:261–270. Abstract | Full Text |
Full-Text PDF (172 KB)
|
CrossRef
19. 19Effect of ramipril on mortality and morbidity of survivors of acute myocardial infarction with clinical evidence of heart failure. The Acute Infarction Ramipril Efficacy (AIRE) Study Investigators. Lancet. 1993;342:821–828. Abstract 20. 20Fox KM. Efficacy of perindopril in reduction of cardiovascular events among patients with stable coronary artery disease: randomised, double-blind, placebo-controlled, multicentre trial (the EUROPA study). Lancet. 2003;362:782–788. Abstract | Full Text |
Full-Text PDF (137 KB)
|
CrossRef
21. 21Swedberg K, Held P, Kjekshus J, et al. Effects of the early administration of enalapril on mortality in patients with acute myocardial infarction. Results of the Cooperative New Scandinavian Enalapril Survival Study II (CONSENSUS II). N Engl J Med. 1992;327:678–684. MEDLINE 22. 22Yusuf S, Sleight P, Pogue J, et al. Effects of an angiotensin-converting-enzyme inhibitor, ramipril, on cardiovascular events in high-risk patients. The Heart Outcomes Prevention Evaluation Study Investigators. N Engl J Med. 2000;342:145–153. MEDLINE |
CrossRef
23. 23Fonarow GC, Abraham WT, Albert NM, et al. Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF): rationale and design. Am Heart J. 2004;148:43–51. Abstract | Full Text |
Full-Text PDF (275 KB)
|
CrossRef
24. 24O'Connor CM, Abraham WT, Albert NM, et al. Predictors of mortality after discharge in patients hospitalized with heart failure: an analysis from the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF). Am Heart J. 2008;156:662–673. Abstract | Full Text |
Full-Text PDF (287 KB)
|
CrossRef
25. 25Teo KK, Yusuf S, Pfeffer M, et al. Effects of long-term treatment with angiotensin-converting-enzyme inhibitors in the presence or absence of aspirin: a systematic review. Lancet. 2002;360:1037–1043. Abstract | Full Text |
Full-Text PDF (96 KB)
|
CrossRef
26. 26Cleland JG, Findlay I, Jafri S, et al. The Warfarin/Aspirin Study in Heart failure (WASH): a randomized trial comparing antithrombotic strategies for patients with heart failure. Am Heart J. 2004;148:157–164. Abstract | Full Text |
Full-Text PDF (137 KB)
|
CrossRef
27. 27Massie BM, Collins JF, Ammon SE, et al. Randomized trial of warfarin, aspirin, and clopidogrel in patients with chronic heart failure: the Warfarin and Antiplatelet Therapy in Chronic Heart Failure (WATCH) trial. Circulation. 2009;119:1616–1624.
CrossRef
28. 28McAlister FA, Ghali WA, Gong Y, et al. Aspirin use and outcomes in a community-based cohort of 7352 patients discharged after first hospitalization for heart failure. Circulation. 2006;113:2572–2578.
CrossRef
29. 29Masoudi FA, Wolfe P, Havranek EP, et al. Aspirin use in older patients with heart failure and coronary artery disease: national prescription patterns and relationship with outcomes. J Am Coll Cardiol. 2005;46:955–962. Abstract | Full Text |
Full-Text PDF (121 KB)
|
CrossRef
30. 30Chang S, Kosolcharoen P, Murray D, et al. Lack of interaction between angiotensin receptor blocker and aspirin in patients with heart failure. Circulation. 2006;114:II_767. a Department of Emergency Medicine and the Cardiovascular Research Institute, Wayne State University School of Medicine, Detroit, MI b Department of Internal Medicine, Wayne State University School of Medicine, Detroit, MI c Duke Clinical Research Institute, Durham, NC d Department of Cardiology, Detroit Medical Center, Detroit, MI e Department of Medicine, Ahmanson-UCLA Cardiomyopathy Center, UCLA Medical Center, Los Angeles, CA f Division of Cardiology, Northwestern University, Feinberg School of Medicine, Chicago, IL g Department of Medicine, Duke University School of Medicine, Durham, NC  Reprint requests: Phillip D. Levy, MD, MPH, Department of Emergency Medicine, Wayne State University School of Medicine, 4201 St Antoine, Detroit, MI 48201.
Presented at the American Heart Association Scientific Sessions, New Orleans, LA, November 2009. PII: S0002-8703(09)00881-3 doi:10.1016/j.ahj.2009.11.009 © 2010 Mosby, Inc. All rights reserved. | |
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