Sudden cardiac death (SCD) is a leading cause of mortality in patients with cardiomyopathy. Although angiotensin-converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARBs) decrease cardiac mortality in these cohorts, their role in preventing SCD has not been well established. We sought to determine whether the use of ACEi or ARB in patients with cardiomyopathy is associated with a lower incidence of appropriate implantable cardiac defibrillator (ICD) shocks in the Genetic Risk Assessment of Defibrillator Events study that included subjects with an ejection fraction of ≤30% and ICDs. Treatment with ACEi/ARB versus no-ACEi/ARB was physician dependent. There were 1,509 patients (mean age [SD] 63 [12] years, 80% men, mean [SD] EF 21% [6%]) with 1,213 (80%) on ACEi/ARB and 296 (20%) not on ACEi/ARB. We identified 574 propensity-matched patients (287 in each group). After a mean (SD) of 2.5 (1.9) years, there were 334 (22%) appropriate shocks in the entire cohort. The use of ACEi/ARB was associated with lower incidence of shocks at 1, 3, and 5 years in the matched cohort (7.7%, 16.7%, and 18.5% vs 13.2%, 27.5%, and 32.0%; RR = 0.61 [0.43 to 0.86]; p = 0.005). Among patients with glomerular filtration rate (GFR) >60 and 30 to 60 ml/min/1.73 m 2 , those on no-ACEi/ARB were at 45% and 77% increased risk of ICD shock compared with those on ACEi/ARB, respectively. ACEi/ARB were associated with significant lower incidence of appropriate ICD shock in patients with cardiomyopathy and GFR ≥30 ml/min/1.73 m 2 and with neutral effect in those with GFR <30 ml/min/1.73 m 2 .
Sudden cardiac death (SCD) is a leading cause of cardiovascular mortality in patients with left ventricular (LV) systolic dysfunction. Angiotensin-converting enzyme inhibitors (ACEis) and angiotensin receptor blockers (ARBs) antagonize the action of angiotensin II, a known precursor of interstitial fibrosis, which is associated with ventricular arrhythmia. Although ACEi/ARB decrease cardiac mortality in patients with LV dysfunction, their role in preventing SCD has not been well established. In 1 study, Obeyesekere et al showed that the absence of ACEi/ARB therapy was a predictor of appropriate implantable cardiac defibrillator (ICD) shock; however, the study was of small sample size and limited events and excluded patients in the secondary prevention population. Hence, the aim of the study is to explore the role of ACEi/ARB in predicting appropriate ICD shocks in a large multicenter registry of patients with severe systolic dysfunction. We hypothesized that ACEi/ARB use is associated with a decreased incidence of appropriate shock in patients with cardiomyopathy. We also sought to elucidate the role of ACEi/ARB in predicting appropriate ICD shocks in (1) distinct glomerular filtration rate (GFR) strata, (2) in ischemic versus nonischemic cardiomyopathy, and lastly (3) based on indication for ICD implantation cohorts (primary vs secondary prevention).
Methods
Subjects included in this study are from the National Heart, Lung, and Blood Institute (NHLBI)-sponsored, prospective, observational, multicenter Genetic Risk Assessment of Defibrillator Events (GRADE) study, designed to identify genetic modifiers of arrhythmic risk. Inclusion criteria were patients who were ≥18 years with a diagnosis of at least moderate systolic LV dysfunction (EF ≤30%) and who had an ICD at the University of Pittsburgh Medical Center (Pittsburgh, Pennsylvania, co-ordinating center), Emory University Medical Center (Atlanta, Georgia), Massachusetts General Hospital (Boston, Massachusetts), Ohio State University Medical Center (Columbus, Ohio), Mid-Ohio Cardiology (Columbus, Ohio), or the Pittsburgh Veterans Affairs Medical Center (Pittsburgh, Pennsylvania). Subjects were excluded if they had intractable class IV heart failure and conditions (other than HF) that were expected to limit survival to <6 months. The institutional review boards of participating medical centers approved the study, and each patient gave written informed consent before participation. This study was conducted according to the guidelines laid down in the Declaration of Helsinki, and the trial was registered at www.clinicaltrials.gov ( NCT 02045043 ).
A total of 1,808 patients of the GRADE study, enrolled from March 2002 to July 2010 within 5 years of ICD implantation, were considered for the current analysis. Of these, 252 patients with no available follow-up data on first appropriate shock outcome and 47 patients without ACEi/ARB medication use data were excluded. The final study population consisted of 1,509 subjects and was divided to 2 primary comparison groups: 1,213 ACEi/ARB (80%) and 296 no-ACEi/ARB (20%). Baseline measurements recorded at the first visit included demographic characteristics, LVEF (by echocardiography, nuclear study, or left ventriculogram), New York Heart Association functional class, medication profile, serum electrolytes, electrocardiographic parameters, echocardiographic parameters, hemodynamic measurements, model and settings of the ICD, cause of heart failure (ischemic vs nonischemic), and indication for device (primary vs secondary prevention). The LV EF was determined by 2-dimensional echocardiography in most subjects.
Patients with ischemic HF included those with a documented history of myocardial infarction, percutaneous transluminal coronary angioplasty, coronary artery bypass graft, or ≥50% diameter stenosis of any of the 3 major coronary epicardial arteries.
Duration of follow-up was defined as the interval from the date of enrollment or ICD implantation (whichever came later) to the date of the first end point or last follow-up when the data were censored. Clinical follow-up was done yearly by telephone by the research co-ordinator, and ICD interrogation was performed. ICD shocks, implantation of ventricular assist device, heart transplantation, and mortality data were collected, and the validities of these data were ascertained by ICD interrogation and hospital medical record documentation. ICD telemetry from all device downloads was sent to the co-ordinating center for review. Appropriate ICD shocks were adjudicated by 2 cardiologists and a third in cases of disagreement. ICD programming was left to the discretion of the local electrophysiologist to select the cut-off rate for fast ventricular tachycardia (VT) and ventricular fibrillation (VF). Shocks for supraventricular tachycardia were excluded from the analyses. Episodes that only required anti-tachycardia pacing (ATP) were excluded from the analyses. Episodes that required both ATP and appropriate ICD shocks were included.
The primary end point in this study was time to first appropriate ICD shock for VT or VF. Secondary end points included all-cause death and the composite end point of death, ventricular assist device, or cardiac transplantation.
Patients with missing appropriate ICD shock follow-up or discharge ACEi/ARB status were excluded from the study. A total of 25 other patient factors ( Table 1 ) were considered in this analysis, and 669 of 1,509 study patients had 100% complete data (44%). Only 5 patient factors (QRS interval, QT C interval, systolic blood pressure, body mass index, and creatinine) had missing data in >5%. Data on medical history and medications intake were imputed assuming normal condition and no medication, respectively. Missing values were imputed using the median or the mode of the variable as applicable. Few patients had missing GFR levels, and they were categorized as having normal GFR (>60 ml/min/1.73 m 2 ). There was no difference in results when missing GFR data were excluded, and only unimputed data were used.
Variable | Un Matched Cohort | p-value | Propensity Matched Cohort | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| ACEi/ARB (N=1213) | No ACEi/ARB (N=296) | Diff | ACEi/ARB (N=287) | No ACEi/ARB (N=287) | Diff | ||||||
| Mean | SD | Mean | SD | Mean | SD | Mean | SD | ||||
| Age (years) | 63 | 12 | 64 | 12 | 8.9% | 0.2 | 65 | 12 | 64 | 12 | 8.1% |
| Systolic Blood Pressure (mm Hg) | 120 | 19 | 129 | 18 | 2.6% | 0.7 | 120 | 19 | 120 | 18 | 1.8% |
| Glomerular filtration rate (imputed), (ml/min/1.73m 2 ) | 63 | 20 | 58 | 20 | 25% | <.001 | 60 | 18 | 59 | 19 | 3.6% |
| Glomerular filtration rate(unimputed), (ml/min/1.73m 2 ) | 64 | 24 | 57 | 23 | 32% | <.001 | 59.0 | 22 | 58 | 23 | 4.4% |
| Ejection Fraction (%) | 21 | 6 | 20 | 6.0 | 9.0% | 0.2 | 20 | 6 | 20 | 6 | 2.3% |
| QRS interval (ms) | 136 | 36 | 135 | 33 | 3.0% | 0.7 | 135 | 36 | 136 | 34 | 2.3% |
| QTC interval (ms) | 472 | 52 | 471 | 54 | 2.7% | 0.6 | 468 | 49 | 471 | 54 | 6.3% |
| N | % | N | % | Diff | p-value | N | % | N | % | Diff | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Men | 981 | 81% | 230 | 78% | 7.8% | 0.22 | 229 | 80% | 224 | 78% | 4.3% | |
| White | 1035 | 85% | 239 | 81% | 12% | 0.05 | 235 | 82% | 234 | 82% | 0.9% | |
| Age (years) | < 50 | 152 | 13% | 31 | 11% | 6.5% | 0.36 | 28 | 10% | 30 | 11% | 2.3% |
| 50-59 | 296 | 24% | 71 | 24% | 1.0% | 61 | 21% | 69 | 24% | 6.7% | ||
| 60-69 | 407 | 34% | 92 | 31% | 5.3% | 97 | 34% | 88 | 31% | 6.7% | ||
| ≥ 70 | 358 | 30% | 102 | 35% | 11% | 101 | 35% | 100 | 35% | 0.7% | ||
| Body mass index (kg/m 2 ) | <21 | 46 | 4% | 12 | 4% | 1.4% | 0.92 | 8 | 3% | 12 | 4% | 7.6% |
| 21-25 | 194 | 16% | 50 | 17% | 2.4% | 54 | 19% | 49 | 17% | 4.5% | ||
| 25-30 | 512 | 42% | 132 | 45% | 4.8% | 127 | 44% | 129 | 45% | 1.4% | ||
| 30-35 | 286 | 24% | 64 | 22% | 4.7% | 69 | 24% | 60 | 21% | 7.5% | ||
| 35-40 | 120 | 10% | 25 | 8% | 5.0% | 19 | 7% | 25 | 9% | 7.9% | ||
| >40 | 55 | 5% | 13 | 4% | 0.7% | 10 | 4% | 12 | 4% | 3.6% | ||
| Glomerular filtration rate (ml/min/1.73 m 2 ) | >60 | 177 | 60% | 845 | 70% | 21% | <.001 | 184 | 64% | 177 | 62% | 5.0% |
| 30-60 | 93 | 31% | 327 | 27% | 9.6% | 87 | 30% | 90 | 31% | 2.3% | ||
| <30 | 26 | 9% | 41 | 3% | 23% | 16 | 6% | 20 | 7% | 6% | ||
| New York Heart Association class | I | 151 | 12% | 52 | 18% | 14% | 0.045 | 42 | 15% | 52 | 18% | 9.4% |
| II | 728 | 60% | 156 | 53% | 15% | 160 | 56% | 152 | 53% | 5.6% | ||
| III | 324 | 27% | 87 | 29% | 6.0% | 85 | 30% | 82 | 29% | 2.3% | ||
| IV | 10 | .8% | 1 | .3% | 6.4% | 0 | 0% | 1 | 0.3% | 8.4% | ||
| Ischemic etiology | 854 | 70% | 221 | 75% | 9.6% | 0.15 | 229 | 80% | 213 | 74% | 13.3% | |
| Device Indications | Secondary | 292 | 24% | 77 | 26% | 4.5% | 0.49 | 74 | 26% | 76 | 27% | 1.6% |
| Defibrillator with biventricular pacing | 523 | 43% | 136 | 46% | 5.7% | 0.38 | 123 | 43% | 131 | 46% | 5.6% | |
| Prior myocardial infarction | 649 | 54% | 169 | 57% | 7.2% | 0.27 | 173 | 60% | 162 | 56% | 7.8% | |
| Diabetes mellitus | 404 | 33% | 116 | 39% | 12% | 0.06 | 119 | 42% | 110 | 38% | 6.4% | |
| Hypertension | 778 | 64% | 181 | 61% | 6.2% | 0.34 | 179 | 62% | 176 | 61% | 2.2% | |
| Hyperlipidemia | 784 | 65% | 188 | 64% | 2.3% | 0.7 | 184 | 64% | 182 | 63% | 1.5% | |
| Smoker | 632 | 52% | 154 | 52% | 0.2% | 0.99 | 149 | 52% | 148 | 52% | 0.70% | |
| Medications | Beta Blockers | 1043 | 86% | 243 | 82% | 11% | 0.09 | 233 | 81% | 238 | 83% | 4.5% |
| Diuretics | 881 | 73% | 207 | 70% | 6.0% | 0.35 | 189 | 66% | 203 | 71% | 10.5% | |
| Aldactone/ Eplerenone | 336 | 28% | 69 | 23% | 10% | 0.13 | 69 | 24% | 68 | 24% | 0.82% | |
| Digoxin | 572 | 47% | 107 | 36% | 23% | 0.001 | 108 | 38% | 105 | 37% | 2.2% | |
| Anti-Arrhythmics | 249 | 21% | 63 | 21% | 1.9% | 0.77 | 62 | 22% | 62 | 22% | 0.0% | |
| Amiodarone | 194 | 16% | 55 | 19% | 6.9% | 0.28 | 51 | 18% | 54 | 19% | 2.7% | |
The ACEi/ARB and no-ACEi/ARB patient groups exhibited significant differences in demographic and risk factors ( Table 1 ) that may confound any association between the outcome (development of appropriate shock after ICD insertion) and ACEi/ARB medication intake. To minimize such confounding, we used propensity score matching to derive matched subcohorts of equal size. No-ACEi/ARB propensity score was derived through a nonparsimonious logistic multivariate regression model that considered no-ACEi/ARB as the dependent outcome variable. A total of 25 risk factors (identified from previously published trials and existing literature) were entered into the model. The resulting propensity scores were distinctly different for ACEi/ARB (yes) versus ACEi/ARB (no) patients (mean [SD] 0.813 [0.079] vs 0.768 [0.097], respectively; p <0.001). The corresponding C-statistic value (area under the ROC curve) was 0.64 ± 0.02 indicating fair-to-moderate discrimination. We obtained 1-to-1 matched cohorts where a given ACEi/ARB was always matched to the closest available no-ACEi/ARB counterpart to within ±1% difference. Adequacy of patient group matching was assessed by calculating the standardized difference, d (%), separately for each factor and based on whether they were continuous or categorical as previously published.
Continuous data were expressed as mean (SD), and categorical data were expressed as counts and percentages. Univariate comparisons were done with the chi-square test for categorical factors, whereas continuous factors were compared by independent t test or Mann-Whitney rank-sum test based on normality. Survival comparisons were done through Kaplan-Meier analysis (log-rank test). The corresponding hazard ratios (HRs [95% confidence interval]) were derived by proportional hazard Cox regression analysis.
Here, to control for potential interaction between ACEi/ARB medication and kidney function, a composite variable of 6 categories was developed as follows: (1) ACEi/ARB (yes), GFR >60 ml/min/1.73 m 2 , (2) ACEi/ARB (yes), GFR 30 to 60 ml/min/1.73 m 2 , (3) ACEi/ARB (yes), GFR <30 ml/min/1.73 m 2 , (4) ACEi/ARB (no), GFR >60 ml/min/1.73 m 2 , (5) ACEi/ARB (no), GFR 30 to 60 ml/min/1.73 m 2 , and (6) ACEi/ARB (no), GFR <30 ml/min/1.73 m 2 . A p <0.05 was used to indicate significance. Analyses were done using SPSS, version 21.0 software (IBM, Armonk, New York).
Results
There were 1,509 patients (mean age [SD] 63 [12] years, 80% men) with 1,213 (80%) on ACEi and/or ARB after enrollment. Compared with patients on ACEi/ARB, the patients not on ACEi/ARB (n = 296, 20%) had worse kidney function, more advanced heart failure symptoms, and were less likely to be taking digoxin, whereas other patient factors were similar ( Table 1 ). After propensity matching, there were 287 patients in each group who were well matched ( Table 1 ).
At a mean (SD) follow-up of 2.5 (1.9) years, a total of 334 patients had experienced 1 or more appropriate shock (22%) in the entire study population. Patients who had an appropriate shock had more co-morbidities and were less likely to be on ACEi/ARB ( Table 2 ).
| Variable | SHOCK (N=334) | NO SHOCK (N=1175) | p-value | ||
|---|---|---|---|---|---|
| Mean | SD | Mean | SD | ||
| Age (years) | 61 | 12 | 63 | 12 | 0.006 |
| Systolic Blood Pressure (mm Hg) | 117 | 18 | 120 | 19 | 0.004 |
| Glomerular filtration rate (ml/min/1.73 m 2 ) | 61 | 20 | 62 | 20 | 0.290 |
| Ejection Fraction (%) | 20 | 6 | 21 | 6 | <.001 |
| QRS interval (ms) | 140 | 35 | 135 | 35 | 0.015 |
| QTC interval (ms) | 475 | 52 | 471 | 53 | 0.330 |
Stay updated, free articles. Join our Telegram channel
Full access? Get Clinical Tree
