Joint Shock/Death Risk Prediction Model for Patients Considering Implantable Cardioverter-Defibrillators.

Pubmed ID: 31412732

Pubmed Central ID: PMC6697057

Journal: Circulation. Cardiovascular quality and outcomes

Publication Date: Aug. 1, 2019

Affiliation: Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA (C.S., A.E.B., D.B.K.).

MeSH Terms: Humans, Male, Female, Aged, Risk Factors, Middle Aged, Randomized Controlled Trials as Topic, Risk Assessment, Heart Failure, Treatment Outcome, Cause of Death, Time Factors, Patient Selection, Decision Support Techniques, Death, Sudden, Cardiac, Defibrillators, Implantable, Electric Countershock, Clinical Decision-Making, Electric Injuries, Health Services Research, Prosthesis Failure

Grants: R01 HS024520, T32 LM012411, U01 HL055297

Authors: Shen C, Buxton AE, Reeder HT, Haneuse SJ, Kramer DB

Cite As: Reeder HT, Shen C, Buxton AE, Haneuse SJ, Kramer DB. Joint Shock/Death Risk Prediction Model for Patients Considering Implantable Cardioverter-Defibrillators. Circ Cardiovasc Qual Outcomes 2019 Aug;12(8):e005675. Epub 2019 Aug 15.

Studies:

Abstract

BACKGROUND: The risk of death or appropriate therapy varies widely among recipients of implantable cardioverter-defibrillators (ICDs). The goals of this study were to develop a risk prediction tool that jointly considers future outcome probabilities of ICD shock and death. METHODS AND RESULTS: We performed a secondary analysis of patients receiving ICDs as part of the SCD-HeFT trial (Sudden Cardiac Death in Heart Failure Trial). We applied an illness-death regression model to jointly model both ICD shocks and death under the semi-competing risks framework, which predicts for each patient their probability of having received ICD shocks, dying, or both at any given point in time. Among 803 ICD recipients (mean age, 60 years; 23% women) followed for a median of 41.1 months, 430 (53.5%) patients completed the study without dying or receiving an ICD shock, 206 (25.7%) received at least 1 shock but survived, 113 (14.1%) died before experiencing a shock, and 54 (6.7%) received at least 1 shock and subsequently died. Predicted outcome probabilities based on baseline demographic and clinical variables reveal substantial heterogeneity in joint shock and death risks, both between patients at each time point and for each single patient across time. Overall, predictive performance for ICD shock and death individually was adequate, based on area under the curve at 5 years of 0.65 for shocks and of 0.79 for death. CONCLUSIONS: Our analysis of outcomes after ICD implantation provides an alternative predictive model for individual risk of death or ICD shocks. If validated, this may provide a useful tool for individualized counseling regarding likely outcomes after device implantation, while also informing the design of further studies to focus the clinical effectiveness and cost-effectiveness of ICD therapy. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT00000609.