JACC: Heart Failure
Volume 5, Issue 12, December 2017 DOI: 10.1016/j.jchf.2017.08.014
PDF Article
Clinical Research

Implantable Cardioverter-Defibrillators in Patients With a Continuous-Flow Left Ventricular Assist Device
An Analysis of the INTERMACS Registry

Kevin J. Clerkin, Veli K. Topkara, Ryan T. Demmer, Jose M. Dizon, Melana Yuzefpolskaya, Justin A. Fried, Xingchen Mai, Donna M. Mancini, Koji Takeda, Hiroo Takayama, Yoshifumi Naka, Paolo C. Colombo and A. Reshad Garan

Author + information

vol. 5 no. 12 916-926
DOI: 
https://doi.org/10.1016/j.jchf.2017.08.014
Published By: 
JACC: Heart Failure
Print ISSN: 
2213-1779
Online ISSN: 
2213-1787
History: 
  • Received June 25, 2017
  • Revision received August 16, 2017
  • Accepted August 18, 2017
  • Published online November 27, 2017.
Copyright & Usage: 
2017 American College of Cardiology Foundation

Author Information

  1. Kevin J. Clerkin, MD, MSca,
  2. Veli K. Topkara, MD, MSca,
  3. Ryan T. Demmer, PhD, MPHb,
  4. Jose M. Dizon, MDa,
  5. Melana Yuzefpolskaya, MDa,
  6. Justin A. Fried, MDa,
  7. Xingchen Mai, MDa,
  8. Donna M. Mancini, MDc,
  9. Koji Takeda, MD, PhDd,
  10. Hiroo Takayama, MD, PhDd,
  11. Yoshifumi Naka, MDd,
  12. Paolo C. Colombo, MDa and
  13. A. Reshad Garan, MDa,∗ (arg2024{at}cumc.columbia.edu)
  1. aDepartment of Medicine, Division of Cardiology, Columbia University College of Physicians and Surgeons, New York, New York
  2. bDepartment of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
  3. cDepartment of Medicine, Division of Cardiology, Icahn School of Medicine at Mount Sinai, New York, New York
  4. dDepartment of Surgery, Division of Cardiac Surgery, Columbia University College of Physicians and Surgeons, New York, New York
  1. ↵∗Address for correspondence:
    Dr. A. Reshad Garan, Center for Advanced Cardiac Care, Department of Medicine, Division of Cardiology, Columbia University Medical Center, 177 Fort Washington Avenue, MHB 5GN-435, New York, New York 10032.

Abstract

Objectives This study sought to determine if the presence of implantable cardioverter-defibrillators (ICD) provided a mortality benefit during continuous-flow left ventricular assist device (LVAD) support.

Background An ICD decreases mortality in selected patients with advanced heart failure and have been associated with reduced mortality in patients with pulsatile LVAD. However, it is unclear whether that benefit extends to patients with a contemporary continuous-flow LVAD.

Methods Propensity score matching was used to generate a cohort of patients with similar baseline characteristics. The primary outcome was freedom from death during LVAD support. Secondary endpoints included freedom from unexpected death, likelihood of transplantation and recovery, and adverse events.

Results Among 16,384 eligible patients in the Interagency Registry for Mechanically Assisted Circulatory Support registry, 2,209 patients with an ICD and 2,209 patients without one had similar propensity scores and were included. The presence of an ICD was associated with an increased mortality risk (hazard ratio: 1.20; 95% confidence interval [CI]: 1.04 to 1.39; p = 0.013) and an increased risk of unexpected death during device support (HR: 1.33; 95% CI: 1.03 to 1.71; p = 0.03). Patients with an ICD were more likely to undergo transplantation (HR: 1.16; 95% CI: 0.99 to 1.35; p = 0.06) and less likely to have LVAD explant for recovery (HR: 0.53, 95% CI: 0.29 to 0.98; p = 0.04). Patients with an ICD had a higher rate of treated ventricular arrhythmias (rate ratio: 1.27; 95% CI: 1.10 to 1.48; p = 0.001) and rehospitalization (rate ratio: 1.08; 95% CI: 1.04 to 1.12; p < 0.0001), but rates of hemorrhagic stroke were similar (rate ratio: 1.01; 95% CI: 0.81 to 1.26; p = 0.98).

Conclusions Among patients with a continuous flow LVAD, the presence of an ICD was not associated with reduced mortality.

Key Words

Heart failure (HF) affects more than 5 million people in the United States, with 250,000 advancing to stage D (1). Continuous-flow left ventricular assist devices (CF-LVAD) are now the most common form of durable support for stage D HF, with more than 2,500 implants annually in the United States and a 1-year survival of about 80% (2). Ventricular arrhythmias (VA) are common in this population; one-third of ambulatory patients with advanced HF experience VA (3). Implantable cardioverter-defibrillators (ICD) reduce the risk of mortality in appropriately selected patients and the Heart Rhythm Society/American College of Cardiology/American Heart Association guidelines provide a Class I recommendation for ICD therapy for New York Heart Association (NYHA) functional class II and III patients with a left ventricular ejection fraction of <35% (4). However, ICD therapy is not indicated (class III recommendation) for NYHA functional class IV patients with drug-refractory HF who are not candidates for heart transplantation or patients with <1 year of life expectancy (4). Most major societal guidelines do not address ICD use in LVAD patients (4,5). The International Society for Heart and Lung Transplantation’s 2013 guidelines for mechanical circulatory support provide a class I recommendation to reactivate an ICD after LVAD surgery and a Class IIa recommendation for ICD placement after LVAD for those without one (6). Two recent studies involving the United Network for Organ Sharing (UNOS) registry (7) and a meta-analysis of previously published studies (8) found a 19% and 39% relative risk reduction in death associated with ICD use during device support, respectively; however, both studies included patients with the previous generation pulsatile LVAD in addition to current generation CF-LVAD. A propensity score–matched analysis limited to CF-LVAD patients implanted with a bridge to transplant strategy in the UNOS registry found that the presence of an ICD was not associated with a survival advantage during device support (9). However, this study was limited to patients listed for transplantation and lacked a number of covariates of interest (e.g., arrhythmia history and anti-arrhythmic medication use). We therefore sought to use the Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) registry to determine if the presence of an ICD was associated with a mortality benefit during CF-LVAD support.

Methods

Patient selection

Data for this study were obtained from the INTERMACS registry, funded by the National Heart, Lung and Blood Institute, National Institutes of Health, Department of Health and Human Services under Contract No. HHSN268201100025C. The INTERMACS registry is a prospective national registry of more than 19,000 patients supported with U.S. Food and Drug Administration–approved durable mechanical circulatory support devices and has previously been described elsewhere (10). The INTERMACS Data and Clinical Coordinating Center and each participating institution have received institutional review board/ethics review board approval for either active informed consent or a waiver of consent to enroll participants, link data, and perform analytic studies. All procedures are compliant with the Health Insurance Portability and Accountability Act, and INTERMACS has received a Federal Certificate of Confidentiality and other protection for the identities of patients and devices identified within the Registry. Analysis of the INTERMACS registry was performed for all patients who received a CF-LVAD between June 1, 2006, and June 30, 2016. There were 18,733 adult candidates (age ≥18 years) who received a durable CF-LVAD (Figure 1). Patients who received a biventricular assist device at time of implantation, right ventricular (RV) assist device only, or total artificial heart were excluded from the analysis. Similarly, patients with an unknown ICD status, pulsatile device, and those receiving their second LVAD were excluded. Patients were analyzed from the date of LVAD implantation to transplant, death, or device explant for recovery. The primary outcome was freedom from death while on LVAD support. Secondary endpoints included freedom from unexpected death, likelihood of transplantation and recovery, and adverse events including arrhythmia, stroke (hemorrhagic), and infection. Pre-specified subgroup analyses were performed for patients who were suspected to derive the greatest benefit from an ICD.

Figure 1
Figure 1

Study Population

BiVAD = biventricular assist device; CF-LVAD = continuous-flow left ventricular assist device; ICD = implantable cardioverter-defibrillator; INTERMACS = Interagency Registry for Mechanically Assisted Circulatory Support; LVAD = left ventricular assist device; RVAD = right ventricular assist device; TAH = total artificial heart.

Propensity score matching

The ICD and non-ICD cohorts significantly differed in baseline characteristics (Table 1). To create more comparable groups of patients, propensity score matching was performed based on covariates (selected a priori) available in the INTERMACS registry. The propensity score was calculated using a nonparsimonious multivariable logistic regression model including clinical (etiology of HF, duration of HF, device strategy at implantation, type of device, INTERMACS profile at implantation, recurrent ventricular tachyarrhythmias [frequent shocks from ICD or requirement for external defibrillator, usually more than twice weekly], NYHA functional class, intravenous inotrope use, intra-aortic balloon pump use, extracorporeal membrane oxygenation use, ventilator use, amiodarone use, beta-blocker use, body mass index, MELD-XI = Model for End-stage Liver Disease score excluding International Normalized Ratio [a surrogate for RV and hepatic dysfunction], severe diabetes, glomerular filtration rate, serum sodium, serum albumin, history of smoking, peripheral vascular disease, pulmonary hypertension, pulmonary disease, ability to work, previous cardiac surgery) and demographic characteristics (age, sex, ethnicity, implanting center volume). Notable baseline covariates with excessive missing data precluding inclusion in the propensity score were RV function and hemodynamic data. Patients were matched 1:1 using a greedy matching algorithm (nearest match without replacement) based on the propensity score of each patient. A caliper width of 20% of the SD of the logit of the propensity score was used (eliminating 99% of the bias due to measured confounding variables) (11). An absolute standardized difference of <10% was considered to represent relative balance (12).

View this table:
Table 1

Patient Characteristics of the Entire Cohort and Propensity Score–Matched Cohort

Statistical analysis

Demographic and clinical variables were expressed as mean ± SD for continuous variables and count (with percentage) for categorical variables. Missing data were assumed to be missing completely at random and handled with multiple imputation using a Markov chain Monte Carlo method to generate 10 imputations. Absolute standardized differences were estimated for all the baseline covariates (between those with and without an ICD) before and after matching to assess group balance. The ICD group comparisons were made with McNemar’s test and the Wilcoxon rank-sum test where appropriate. Kaplan-Meier survival analysis and Cox proportional-hazards regression (stratifying on the matched pairs) were performed to determine if survival differed by ICD status. Competing risk analysis of transplantation, death, and recovery were estimated using cause-specific hazard regression. Subgroup analyses were performed subsetting the entire cohort based on pre-specified groups (implant strategy, age [60 years], etiology of HF, duration of HF, INTERMACS profile, recurrent ventricular tachycardia, amiodarone use, beta-blocker use, type of device, and duration of LVAD support) and then performing Cox proportional hazard regression, adjusting for the group propensity score. The rates of adverse events were compared with rate ratios (RRs). Sensitivity analyses were performed to determine whether there was a consistency of the findings using alternative methods. These included using the entire cohort through stratification into quintiles by propensity score (13), adjusted Cox proportional hazard regression (using the propensity score and ICD status only to avoid collinearity) (14), and both combined, which has been suggested to be superior to matching alone for estimating the treatment effect (15). A 2-tailed p value of <0.05 was considered significant. Analyses were performed using SAS version 9.4 (SAS Institute, Inc., Cary, North Carolina). Figures were created using SAS version 9.4 (SAS Institute, Inc.) and R version 3.3.1 (R Foundation for Statistical Computing, Vienna, Austria).

Results

A total of 16,384 patients met study entry criteria, of which 13,247 (80.9%) had an ICD and 3,137 (19.1%) did not. The baseline characteristics for the study cohort differed in most baseline characteristics as demonstrated by an absolute standardized difference of >10% (Table 1). The greatest differences (absolute standardized difference >40%) were in duration of HF, INTERMACS profile, recurrent VAs, ventilator use, and beta-blocker use. Propensity score matching generated a cohort of 4,418 patients; 2,209 patients with and 2,209 patients without an ICD. The absolute standardized difference was <10% for all baseline characteristics, indicating suitable matching (Table 1).

In the matched cohort, the median duration of CF-LVAD support was similar for both the ICD and non-ICD groups (12.3 months [IQR: 4.7 to 25.8 months] vs. 12.5 months [IQR: 5.3 to 24.9 months]; p = 0.63). The presence of an ICD was associated with a 20% greater risk of death during LVAD support when compared with those without an ICD (95% confidence interval [CI]: 1.04 to 1.39; p = 0.013) (Figure 2). Recognizing that an ICD mitigates the risk of sudden and unexpected death, a subsequent survival analysis was performed for freedom from unexpected death. This demonstrated that again ICDs were not associated with a decreased risk, but rather an increased risk of unexpected death (hazard ratio [HR]: 1.33; 95% CI: 1.03 to 1.71; p = 0.03) (Figure 3). An exploratory analysis limiting the mode of death to only “Circulatory: Sudden Unexplained Death” and “Circulatory: Cardiac Arrhythmia” identified 37 deaths (1.67%) in the ICD group and 46 deaths (2.08%) in the No ICD group. In this group there was a nonsignificant reduction in risk over time (HR: 0.81; 95% CI: 0.43 to 1.53; p = 0.52). Although cause of death did not differ overall between the 2 groups (chi-square p = 0.23), withdrawal of support, neurological dysfunction, and multisystem organ failure account for a majority of the increased mortality in the ICD group (Online Table 1).

Figure 2
Figure 2

Freedom From Death After LVAD Implantation

Freedom from death after left ventricular assist device (LVAD) implantation for the propensity score–matched cohort. CI = confidence interval; HR = hazard ratio; ICD = implantable cardioverter-defibrillator.

Figure 3
Figure 3

Freedom From Unexpected Death After LVAD Implantation

Freedom from unexpected death after LVAD implantation for the propensity score–matched cohort. Abbreviations as in Figure 2.

A cause-specific hazard model was created treating death, transplantation, and LVAD explant for recovery as competing events (Figure 4). The likelihood of transplantation was 16% greater in those with an ICD, although this finding only approached statistical significance (95% CI: 0.99 to 1.35; p = 0.06). An LVAD explant for recovery, however, was less likely to occur in those with an ICD (HR: 0.53; 95% CI: 0.29 to 0.98; p = 0.04).

Figure 4
Figure 4

Competing Outcomes Curves

Competing outcomes curves for events terminating device support. Outcome events are mutually exclusive. Abbreviations as in Figure 2.

Adverse events

There was a greater rate of any arrhythmia in the ICD group during device support (RR: 1.11; 95% CI: 1.01 to 1.22; p = 0.03) (Table 2). This trend was largely attributable to a 27% increased rate of VA requiring defibrillation or cardioversion (95% CI: 1.10 to 1.48; p = 0.001). There was no difference in infection, bacteremia, neurological dysfunction, or hemorrhagic stroke. However, there was an increased rate of rehospitalization in the ICD group (RR: 1.08; 95% CI: 1.04 to 1.12; p < 0.0001).

View this table:
Table 2

Adverse Events on Device Support

Subgroup analysis

An exploratory subgroup analysis was performed to investigate for effect modification by a priori selected covariates (Figure 5). Tests for interaction failed to demonstrate heterogeneity of treatment effect among subgroups (p = 0.09 to 0.99). Only 2 subgroups (LVAD support for ≥2 years and no beta-blocker use) had a point estimate for the HR favoring ICD use, although neither approached significance. Conversely, a number of subgroups showed an association between improved survival and the no ICD group: those with a NICM, chronic HF, INTERMACS profile 1 or 2, no recurrent pre-implant VA, current beta-blocker use, amiodarone use in the prior year, and device support of <2 years duration. However, only a duration of LVAD support of <2 years remained significant after adjustment for multiple comparisons.

Figure 5
Figure 5

Risk of Death for Individual Subgroups

Interaction testing was not significant for any subgroup. BTC = bridge to candidacy; BTT = bridge to transplant; DT = destination therapy; HF = heart failure; ICM = ischemic cardiomyopathy; NICM = nonischemic cardiomyopathy; VA = ventricular arrhythmia; other abbreviations as in Figures 1 and 2.

Sensitivity analysis

Recognizing that, despite adequate matching on measured confounders, there may be confounding by unmeasured covariates, a falsification hypothesis analysis was performed to assess for potential confounders to explain the primary outcome. This analysis evaluated the matched cohort for the incidence of LVAD malfunction and/or device thrombosis, which was not anticipated to be impacted by ICD status. This analysis demonstrated no significant difference (RR: 1.00; 95% CI: 0.91 to 1.11; p = 0.99). Additional sensitivity analyses were performed for the full study cohort of 16,384 using the propensity score to stratify and adjust a Cox proportional hazard model. This analysis was consistent with the matched cohort, failing to demonstrate an association between ICD use and decreased risk of mortality during LVAD support using adjustment (HR: 1.09; 95% CI: 0.99 to 1.19; p = 0.07), quintile stratification (HR: 1.09; 95% CI: 1.00 to 1.19; p = 0.05), and stratification and adjustment (HR: 1.09; 95% CI: 0.99 to 1.19; p = 0.07).

Discussion

In patients with stage D HF, CF-LVADs improve survival and quality of life. Within 6 months of implantation more than 80% of patients have NYHA functional class I or II symptoms and more than 97% have less than NYHA functional class IV symptoms (16). However, VAs remain common after LVAD implantation and as many as one-half will experience VAs (17). Further, increases in transplant waitlist times (18) and increased use of LVADs as destination therapy (nearly 50%) (2) have resulted in longer durations of device support. Although ICDs are often present at the time of LVAD surgery (80.9% in this study), clinicians are still left with a decision regarding ICD implantation in 1 in 5 LVAD patients. Furthermore, for those with ICDs, generator changes may be required after LVAD implantation. Many current society guidelines (American College of Cardiology/American Heart Association/Heart Rhythm Society and ESC) do not specifically address LVADs, but the International Society for Heart and Lung Transplantation provides a Class IIa recommendation for ICD implantation in LVAD patients without one (6). Our study examined the impact of ICDs in patients with CF-LVAD and found that the presence of an ICD was not associated with improved survival during LVAD support during a median follow-up of 12.4 months.

Prior single-center studies have lacked adequate statistical power and other registry analyses have lacked key information to conclusively examine the effect of ICDs in patients with CF-LVAD. The present analysis used the largest LVAD registry to attempt to answer this question and, after propensity score matching, generated a cohort with nearly as many patients without an ICD (n = 2,209) as were enrolled in MADIT (Multicenter Automatic Defibrillator Implantation Trial), MADIT II, SCD-HeFT (Sudden Cardiac Death in Heart Failure Trial; placebo arm), DINAMIT (Defibrillator in Acute Myocardial Infarction Trial), MUSTT (Multicenter Unsustained Tachycardia Trial), and DEFINITE (Defibrillators in Non-Ischemic Cardiomyopathy Treatment Evaluation) trials combined (n = 2,362) (19–24). Analysis of this large cohort with a median duration of follow-up of just more than 1 year failed to detect any evidence that the presence of an ICD improved survival. Interestingly, ICD presence was associated with a statistically significant 20% increase in mortality rates in the propensity score–matched cohort. This finding may be in part the result of propensity score matching, which resulted in an ICD group that had decreased prevalence of certain VA risk factors (−7% prior VA, −31% HF >2 years, −14% beta-blocker use, −7% amiodarone use) compared with the complete cohort. This was reflected in the sensitivity analyses of the entire study cohort, which found a nonsignificant 9% increased risk of death in the ICD group. Furthermore, exploratory analyses were performed looking at subgroups that may be at the highest risk (ischemic cardiomyopathy, prior VA, requirement of anti-arrhythmic medication, longer duration of HF, and prolonged LVAD support) to try to identify a specific group that may derive benefit. Importantly, in no subgroup was the presence of an ICD associated with improved survival, including those with a prior VA (Figure 5).

Post-LVAD arrhythmic events were common in this study; nearly one-quarter of the patients in each arm experienced significant arrhythmias during device support. Focusing specifically on treated VA, the rate was 27% greater in patients with an ICD. Despite this increase in treated VA, there was no association of improved survival with ICDs. Importantly, only clinically reported treated VA were captured in the registry, which is the likely cause of a lower prevalence of VA in this cohort compared with prior studies with more specific patient-level data (e.g., from routine ICD interrogation). Further, the nature of the dataset precludes the ability to determine whether the rate of VA was actually greater in those with an ICD or if those patients simply had more treated VA because the ICD delivered therapies for VA that might have resolved spontaneously. Additionally, there was an increased rate of rehospitalization in the ICD group and, although speculative, it is possible that ICD discharge was a potential driver of the increased hospital use.

Not only do ICDs function to prevent arrhythmic death, they also may help to prevent syncope and its associated head trauma during cerebral hypoperfusion from the cardiac arrhythmia. The latter is especially of concern for LVAD patients, who are routinely on therapeutic anticoagulation and aspirin. Reassuringly, there was no difference in the rate of neurological dysfunction and, specifically, hemorrhagic stroke.

Our findings differ from prior studies reporting an associated survival benefit for patients with an ICD and a pulsatile LVAD (7,8,25,26), but are consistent with a previous analysis of bridge to transplant patients supported by CF-LVAD in the UNOS registry (9). This difference is mechanistically plausible, because pulsatile pumps may be more dependent on native cardiac activity than continuous flow pumps. As mentioned, medically treated HF patients often develop cerebral hypoperfusion and hemodynamic compromise during VA. Although cardiac output may be reduced during periods of VA, this reduction may be less likely to cause hemodynamic collapse in the presence of a CF-LVAD; indeed, prolonged VA have been reported (27,28), during which the CF-LVAD maintains systemic perfusion likely through Fontan-like physiology. Data on RV function and peripheral vascular resistance, which would impact Fantan-like physiology, were not available for this study. Although many of these events may resolve spontaneously, this degree of hemodynamic support allows CF-LVAD patients with a VA that does not resolve (with or without ICD) to present for arrhythmia treatment (17). Alternatively, the lack of mortality benefit from an ICD may be an artifact due to confounding by a factor not measured in the INTERMACS registry. Although possible, an association between ICD use and improved survival was missing from both the primary analysis and all sensitivity analyses, suggesting this may be less likely. Last, it is possible that ICD firing to terminate VA that might have terminated spontaneously is detrimental in patients with a CF-LVAD. Discharge of the ICD has been linked to echocardiographic RV dysfunction (29) and, when recurrent, may precipitate RV failure (30). Unfortunately, specific information about ICD discharge was not available in the INTERMACS registry and this factor could not be examined.

It is important to underscore the fact that these data do not support deactivation of ICD therapies after LVAD implantation. Furthermore, for patients who have received appropriate shocks whether before or after LVAD implantation, we believe maintenance of ICD therapy is important to prevent the morbidities associated with prolonged VA (most notably RV failure). As such, we advocate for generator changes in patients with prior VA if required after LVAD implantation. However, we do believe these findings may put into question the need for primary prevention ICDs in patients with a CF-LVAD.

Well-conducted trials in non-LVAD patients have demonstrated that more permissive ICD programming can be beneficial. The 1,902-patient randomized ADVANCE III trial (Avoid Delivering Therapies for Nonsustained Arrhythmias in ICD Patients III) demonstrated that prolonged detection intervals decreased therapies delivered and inappropriate shocks with no difference in mortality or arrhythmic syncope (31). MADIT-RIT (MADIT Randomized Trial to Reduce Inappropriate Therapy) found an increased rate threshold (>200 beats/min, after a 2.5-s monitoring delay) and delayed therapy (60 s with a HR of 170 to 199 beats/min, 12 s with a HR of >200 beats/min) were both associated with reductions in inappropriate therapy and all-cause mortality, while not increasing syncope (32). We propose that these data, in combination with this study, provide an impetus to compare standard ICD therapy to more permissive ICD settings (combination of increased threshold and delayed therapy) among CF-LVAD patients.

Study limitations

As a result of the observational nature, this study is limited in its ability to determine causation. The INTERMACS registry that was used is of high quality, although our analysis was limited to the data collected, which might have omitted confounders. The ICD interrogation data were not available, resulting in probable under-reporting of ICD therapy (antitachycardia pacing) and an unknown frequency of inappropriate shocks. Also absent were individual patient ICD settings limiting our ability to comment on ICD programming. The registry also does not specifically include data on de novo ICD implantation after LVAD, creating the possibility of 1-way patient crossover and an introduction of bias. In this study, none of the patients were reported to be hospitalized for ICD implantation and, in the UNOS Mechanical Circulatory Support registry, fewer than 8% of patients without an ICD at the time of listing went on to receive one (9), suggesting the amount of crossover was unlikely to have been large. The data available also precluded inclusion of RV function and pulmonary vascular resistance in the propensity score, post-implant anti-arrhythmic drug use, and post-LVAD implantation hospitalizations for syncope. Although propensity score matching with a caliper width of 20% of SD of the logit of the propensity score eliminates 99% of the bias due to measured confounding variables (11), this technique is unable to account for unmeasured confounders. Last, in an effort to completely explore this topic, a number of secondary analyses and subgroup analyses were performed. Some of these had significant p values (p < 0.05); however, only a few would persist after adjustment for multiple testing (e.g., Bonferroni correction, Hochberg step-up, or Holm step-down method).

Conclusions

The presence of an ICD was not associated with a decrease in mortality among patients with a CF-LVAD.

Perspectives

COMPETENCY IN PATIENT CARE: Nearly 1 in 5 patients who receive a CF-LVAD do not have an ICD. In the INTERMACS registry, ICDs were not found to be associated with a decrease in mortality in patients with a CF-LVAD, despite an increase in treated VA.

TRANSLATIONAL OUTLOOK: Prospective, randomized studies investigating permissive ICD programming (e.g., increased use of antitachycardia pacing, prolonged detection intervals, and higher detection rates) in CF-LVAD patients are needed.

Acknowledgment

The authors would like to thank the INTERMACS investigators, coordinators, and participating institutions for the data they have provided for this registry.

Appendix

Footnotes

  • The data for this study came from the Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS), National Heart Lung and Blood Institute, Contract number HHSN268200548198C, 2010. The content is solely the responsibility of the author(s) and does not necessarily represent the official views of the Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) or the National Institutes of Health. Dr. Clerkin is supported by National Institutes of Health Grant T32 HL007854. Dr. Garan is supported by National Institutes of Health Grant KL2TR001874. Dr. Naka has received consulting fees from Abbott (Thoratec) and St. Jude (Heartware). Dr. Garan has received honoraria from Abiomed. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Abbreviations and Acronyms
CF-LVAD
continuous-flow left ventricular assist device
ESC
European Society of Cardiology
HF
heart failure
ICD
implantable cardioverter-defibrillator
INTERMACS
Interagency Registry for Mechanically Assisted Circulatory Support
LVAD
left ventricular assist device
NYHA
New York Heart Association
RR
rate ratio
RV
right ventricle/ventricular
UNOS
United Network for Organ Sharing
VA
ventricular arrhythmia
  • Received June 25, 2017.
  • Revision received August 16, 2017.
  • Accepted August 18, 2017.

References

  1. ↵
    1. Mancini D.,
    2. Colombo P.C.
    (2015) Left ventricular assist devices: a rapidly evolving alternative to transplant. J Am Coll Cardiol 65:2542–2555.
    OpenUrlFREE Full Text
  2. ↵
    1. Kirklin J.K.,
    2. Naftel D.C.,
    3. Pagani F.D.,
    4. et al.
    (2015) Seventh INTERMACS annual report: 15,000 patients and counting. J Heart Lung Transplant 34:1495–1504.
    OpenUrlCrossRefPubMed
  3. ↵
    1. Santangeli P.,
    2. Rame J.E.,
    3. Birati E.Y.,
    4. Marchlinski F.E.
    (2017) Management of ventricular arrhythmias in patients with advanced heart failure. J Am Coll Cardiol 69:1842–1860.
    OpenUrlFREE Full Text
  4. ↵
    1. Epstein A.E.,
    2. DiMarco J.P.,
    3. Ellenbogen K.A.,
    4. et al.
    (2008) ACC/AHA/HRS 2008 guidelines for device-based therapy of cardiac rhythm abnormalities: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Writing Committee to Revise the ACC/AHA/NASPE 2002 Guideline Update for Implantation of Cardiac Pacemakers and Antiarrhythmia Devices) developed in collaboration with the American Association for Thoracic Surgery and Society of Thoracic Surgeons. J Am Coll Cardiol 51:e1–e62.
    OpenUrlFREE Full Text
  5. ↵
    1. Priori S.G.,
    2. Blomstrom-Lundqvist C.,
    3. Mazzanti A.,
    4. et al.
    (2015) 2015 ESC guidelines for the management of patients with ventricular arrhythmias and the prevention of sudden cardiac death: the Task Force for the Management of Patients with Ventricular Arrhythmias and the Prevention of Sudden Cardiac Death of the European Society of Cardiology (ESC). Endorsed by: Association for European Paediatric and Congenital Cardiology (AEPC). Eur Heart J 36:2793–2867.
    OpenUrlCrossRefPubMed
  6. ↵
    1. Feldman D.,
    2. Pamboukian S.V.,
    3. Teuteberg J.J.,
    4. et al.
    (2013) The 2013 International Society for Heart and Lung Transplantation Guidelines for mechanical circulatory support: executive summary. J Heart Lung Transplant 32:157–187.
    OpenUrlCrossRefPubMed
  7. ↵
    1. Vakil K.,
    2. Duval S.,
    3. Cogswell R.,
    4. et al.
    (2017) Impact of implantable cardioverter-defibrillators on waitlist mortality among patients awaiting heart transplantation. J Am Coll Cardiol EP 3:33.
    OpenUrl
  8. ↵
    1. Vakil K.,
    2. Kazmirczak F.,
    3. Sathnur N.,
    4. et al.
    (2016) Implantable cardioverter-defibrillator use in patients with left ventricular assist devices. J Am Coll Cardiol HF 4:772.
    OpenUrl
  9. ↵
    1. Clerkin K.J.,
    2. Topkara V.K.,
    3. Mancini D.M.,
    4. et al.
    (2017) The role of implantable cardioverter defibrillators in patients bridged to transplantation with a continuous-flow left ventricular assist device: a propensity score matched analysis. J Heart Lung Transplant 36:633–639.
    OpenUrl
  10. ↵
    1. Kirklin J.K.,
    2. Naftel D.C.,
    3. Stevenson L.W.,
    4. et al.
    (2008) INTERMACS database for durable devices for circulatory support: first annual report. J Heart Lung Transplant 27:1065–1072.
    OpenUrlCrossRefPubMed
  11. ↵
    1. Austin P.C.
    (2011) Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies. Pharm Stat 10:150–161.
    OpenUrlCrossRefPubMed
  12. ↵
    1. Austin P.C.
    (2009) Using the standardized difference to compare the prevalence of a binary variable between two groups in observational research. Communications in Statistics - Simulation and Computation 38:1228–1234.
    OpenUrlCrossRef
  13. ↵
    1. Rosenbaum P.R.,
    2. Rubin D.B.
    (1984) Reducing bias in observational studies using subclassification on the propensity score. J Am Stat Assoc 79:516–524.
    OpenUrlCrossRef
  14. ↵
    1. Elze M.C.,
    2. Gregson J.,
    3. Baber U.,
    4. et al.
    (2017) Comparison of propensity score methods and covariate adjustment. Evaluation in 4 cardiovascular studies. J Am Coll Cardiol 69:345–357.
    OpenUrlFREE Full Text
  15. ↵
    1. D’Agostino R.B.
    (2007) Propensity scores in cardiovascular research. Circulation 115:2340–2343.
    OpenUrlFREE Full Text
  16. ↵
    1. Rogers J.G.,
    2. Aaronson K.D.,
    3. Boyle A.J.,
    4. et al.
    (2010) Continuous flow left ventricular assist device improves functional capacity and quality of life of advanced heart failure patients. J Am Coll Cardiol 55:1826–1834.
    OpenUrlFREE Full Text
  17. ↵
    1. Garan A.R.,
    2. Yuzefpolskaya M.,
    3. Colombo P.C.,
    4. et al.
    (2013) Ventricular arrhythmias and implantable cardioverter-defibrillator therapy in patients with continuous-flow left ventricular assist devices need for primary prevention? J Am Coll Cardiol 61:2542–2550.
    OpenUrlFREE Full Text
  18. ↵
    1. Schulze P.C.,
    2. Kitada S.,
    3. Clerkin K.,
    4. Jin Z.,
    5. Mancini D.M.
    (2014) Regional differences in recipient waitlist time and pre- and post-transplant mortality after the 2006 United Network for Organ Sharing policy changes in the donor heart allocation algorithm. J Am Coll Cardiol HF 2:166–177.
    OpenUrl
  19. ↵
    1. Moss A.J.,
    2. Hall W.J.,
    3. Cannom D.S.,
    4. et al.
    (1996) Improved survival with an implanted defibrillator in patients with coronary disease at high risk for ventricular arrhythmia. N Engl J Med 335:1933–1940.
    OpenUrlCrossRefPubMed
  20. ↵
    1. Moss A.J.,
    2. Zareba W.,
    3. Hall W.J.,
    4. et al.
    (2002) Prophylactic implantation of a defibrillator in patients with myocardial infarction and reduced ejection fraction. N Engl J Med 346:877–883.
    OpenUrlCrossRefPubMed
  21. ↵
    1. Bardy G.H.,
    2. Lee K.L.,
    3. Mark D.B.,
    4. et al.
    (2005) Amiodarone or an implantable cardioverter–defibrillator for congestive heart failure. N Engl J Med 352:225–237.
    OpenUrlCrossRefPubMed
  22. ↵
    1. Hohnloser S.H.,
    2. Kuck K.H.,
    3. Dorian P.,
    4. et al.
    (2004) Prophylactic use of an implantable cardioverter–defibrillator after acute myocardial infarction. N Engl J Med 351:2481–2488.
    OpenUrlCrossRefPubMed
  23. ↵
    1. Buxton A.E.,
    2. Lee K.L.,
    3. DiCarlo L.,
    4. et al.
    (2000) Electrophysiologic testing to identify patients with coronary artery disease who are at risk for sudden death. N Engl J Med 342:1937–1945.
    OpenUrlCrossRefPubMed
  24. ↵
    1. Kadish A.,
    2. Dyer A.,
    3. Daubert J.P.,
    4. et al.
    (2004) Prophylactic defibrillator implantation in patients with nonischemic dilated cardiomyopathy. N Engl J Med 350:2151–2158.
    OpenUrlCrossRefPubMed
  25. ↵
    1. Refaat M.M.,
    2. Tanaka T.,
    3. Kormos R.L.,
    4. et al.
    (2012) Survival benefit of implantable cardioverter-defibrillators in left ventricular assist device-supported heart failure patients. J Cardiac Failure 18:140–145.
    OpenUrlCrossRefPubMed
  26. ↵
    1. Cantillon D.J.,
    2. Tarakji K.G.,
    3. Kumbhani D.J.,
    4. Smedira N.G.,
    5. Starling R.C.,
    6. Wilkoff B.L.
    (2010) Improved survival among ventricular assist device recipients with a concomitant implantable cardioverter-defibrillator. Heart Rhythm 7:466–471.
    OpenUrlCrossRefPubMed
  27. ↵
    1. Oz M.C.,
    2. Rose E.A.,
    3. Slater J.,
    4. Kuiper J.J.,
    5. Catanese K.A.,
    6. Levin H.R.
    (1994) Malignant ventricular arrhythmias are well tolerated in patients receiving long-term left ventricular assist devices. J Am Coll Cardiol 24:1688–1691.
    OpenUrlFREE Full Text
  28. ↵
    1. Sims D.B.,
    2. Rosner G.,
    3. Uriel N.I.R.,
    4. González-Costello J.,
    5. Ehlert F.A.,
    6. Jorde U.P.
    (2012) Twelve hours of sustained ventricular fibrillation supported by a continuous-flow left ventricular assist device. Pacing Clin Electrophysiol 35:e144–e148.
    OpenUrlCrossRefPubMed
  29. ↵
    1. Malasana G.,
    2. Daccarett M.,
    3. Kuppahally S.,
    4. Wasmund S.L.,
    5. Litwin S.E.,
    6. Hamdan M.H.
    (2011) High prevalence of right ventricular dysfunction in ICD patients with shocks: a potential new predictor in risk stratification. J Interv Cardiac Electrophysiol 31:165–169.
    OpenUrlPubMed
  30. ↵
    1. Garan A.R.,
    2. Levin A.P.,
    3. Topkara V.,
    4. et al.
    (2015) Early post-operative ventricular arrhythmias in patients with continuous-flow left ventricular assist devices. J Heart Lung Transplant 34:1611–1616.
    OpenUrl
  31. ↵
    1. Gasparini M.,
    2. Proclemer A.,
    3. Klersy C.,
    4. et al.
    (2013) Effect of long-detection interval vs standard-detection interval for implantable cardioverter-defibrillators on antitachycardia pacing and shock delivery: the ADVANCE III randomized clinical trial. JAMA 309:1903–1911.
    OpenUrlCrossRefPubMed
  32. ↵
    1. Moss A.J.,
    2. Schuger C.,
    3. Beck C.A.,
    4. et al.
    (2012) Reduction in inappropriate therapy and mortality through ICD programming. N Engl J Med 367:2275–2283.
    OpenUrlCrossRefPubMed
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