Impact of a Chronic Total Coronary Occlusion on the Incidence of Appropriate Implantable Cardioverter-Defibrillator Shocks and Mortality: A Substudy of the Dutch Outcome in ICD Therapy (DO-IT)) Registry.

BACKGROUND: Chronic total coronary occlusions (CTO) substantially increase the risk for sudden cardiac death. Among patients with chronic ischemic heart disease at risk for sudden cardiac death, an implantable cardioverter defibrillator (ICD) is the favored therapy for primary prevention of sudden cardiac death. This study sought to investigate the impact of CTOs on the risk for appropriate ICD shocks and mortality within a nationwide prospective cohort. METHODS AND RESULTS: This is a subanalysis of the nationwide Dutch-Outcome in ICD Therapy (DO-IT) registry of primary prevention ICD recipients in The Netherlands between September 2014 and June 2016 (n=1442). We identified patients with chronic ischemic heart disease (n=663) and assessed available coronary angiograms for CTO presence (n=415). Patients with revascularized CTOs were excluded (n=79). The primary end point was the composite of all-cause mortality and appropriate ICD shocks. Clinical follow-up was conducted for at least 2 years. A total of 336 patients were included, with an average age of 67±9 years, and 20.5% was female (n=69). An unrevascularized CTO was identified in 110 patients (32.7%). During a median follow-up period of 27 months (interquartile range, 24-32), the primary end point occurred in 21.1% of patients with CTO (n=23) compared with 11.9% in patients without CTO (n=27; P=0.034). Corrected for baseline characteristics including left ventricular ejection fraction, and the presence of a CTO was an independent predictor for the primary end point (hazard ratio, 1.82 [95% CI, 1.03-3.22]; P=0.038). CONCLUSIONS: Within this nationwide prospective registry of primary prevention ICD recipients, the presence of an unrevascularized CTO was an independent predictor for the composite outcome of all-cause mortality and appropriate ICD shocks.

Dutch Outcome in Implantable Cardioverter-Defibrillator Therapy: Implantable Cardioverter-Defibrillator-Related Complications in a Contemporary Primary Prevention Cohort.

Background One third of primary prevention implantable cardioverter-defibrillator patients receive appropriate therapy, but all remain at risk of defibrillator complications. Information on these complications in contemporary cohorts is limited. This study assessed complications and their risk factors after defibrillator implantation in a Dutch nationwide prospective registry cohort and forecasts the potential reduction in complications under distinct scenarios of updated indication criteria. Methods and Results Complications in a prospective multicenter registry cohort of 1442 primary implantable cardioverter-defibrillator implant patients were classified as major or minor. The potential for reducing complications was derived from a newly developed prediction model of appropriate therapy to identify patients with a low probability of benefitting from the implantable cardioverter-defibrillator. During a follow-up of 2.2 years (interquartile range, 2.0-2.6 years), 228 complications occurred in 195 patients (13.6%), with 113 patients (7.8%) experiencing at least one major complication. Most common ones were lead related (n=93) and infection (n=18). Minor complications occurred in 6.8% of patients, with lead-related (n=47) and pocket-related (n=40) complications as the most prevailing ones. A surgical reintervention or additional hospitalization was required in 53% or 61% of complications, respectively. Complications were strongly associated with device type. Application of stricter implant indication results in a comparable proportional reduction of (major) complications. Conclusions One in 13 patients experiences at least one major implantable cardioverter-defibrillator-related complication, and many patients undergo a surgical reintervention. Complications are related to defibrillator implantations, and these should be discussed with the patient. Stricter implant indication criteria and careful selection of device type implanted may have significant clinical and financial benefits.

Development and external validation of prediction models to predict implantable cardioverter-defibrillator efficacy in primary prevention of sudden cardiac death.

AIMS: This study was performed to develop and externally validate prediction models for appropriate implantable cardioverter-defibrillator (ICD) shock and mortality to identify subgroups with insufficient benefit from ICD implantation. METHODS AND RESULTS: We recruited patients scheduled for primary prevention ICD implantation and reduced left ventricular function. Bootstrapping-based Cox proportional hazards and Fine and Gray competing risk models with likely candidate predictors were developed for all-cause mortality and appropriate ICD shock, respectively. Between 2014 and 2018, we included 1441 consecutive patients in the development and 1450 patients in the validation cohort. During a median follow-up of 2.4 (IQR 2.1-2.8) years, 109 (7.6%) patients received appropriate ICD shock and 193 (13.4%) died in the development cohort. During a median follow-up of 2.7 (IQR 2.0-3.4) years, 105 (7.2%) received appropriate ICD shock and 223 (15.4%) died in the validation cohort. Selected predictors of appropriate ICD shock were gender, NSVT, ACE/ARB use, atrial fibrillation history, Aldosterone-antagonist use, Digoxin use, eGFR, (N)OAC use, and peripheral vascular disease. Selected predictors of all-cause mortality were age, diuretic use, sodium, NT-pro-BNP, and ACE/ARB use. C-statistic was 0.61 and 0.60 at respectively internal and external validation for appropriate ICD shock and 0.74 at both internal and external validation for mortality. CONCLUSION: Although this cohort study was specifically designed to develop prediction models, risk stratification still remains challenging and no large group with insufficient benefit of ICD implantation was found. However, the prediction models have some clinical utility as we present several scenarios where ICD implantation might be postponed.

Handling missing predictor values when validating and applying a prediction model to new patients.

Missing data present challenges for development and real-world application of clinical prediction models. While these challenges have received considerable attention in the development setting, there is only sparse research on the handling of missing data in applied settings. The main unique feature of handling missing data in these settings is that missing data methods have to be performed for a single new individual, precluding direct application of mainstay methods used during model development. Correspondingly, we propose that it is desirable to perform model validation using missing data methods that transfer to practice in single new patients. This article compares existing and new methods to account for missing data for a new individual in the context of prediction. These methods are based on (i) submodels based on observed data only, (ii) marginalization over the missing variables, or (iii) imputation based on fully conditional specification (also known as chained equations). They were compared in an internal validation setting to highlight the use of missing data methods that transfer to practice while validating a model. As a reference, they were compared to the use of multiple imputation by chained equations in a set of test patients, because this has been used in validation studies in the past. The methods were evaluated in a simulation study where performance was measured by means of optimism corrected C-statistic and mean squared prediction error. Furthermore, they were applied in data from a large Dutch cohort of prophylactic implantable cardioverter defibrillator patients.