Abstract TP188: Predicting Ischemic Stroke And All-cause Mortality Risk In Patients With Heart Failure With Reduced Ejection Fraction And Sinus Rhythm: A Secondary Analysis Of The Warcef Trial

Abstract

Introduction: There is a known risk of ischemic stroke (IS) and mortality among patients with heart failure with reduced ejection fraction (HFrEF) and sinus rhythm. We identify predictors of IS and all-cause death in patients with left ventricular ejection fraction (LVEF) < 35% and sinus rhythm by a machine-learning approach. Methods: We performed a post-hoc analysis of the WARCEF trial which randomized patients with LVEF < 35% and sinus rhythm to either aspirin or warfarin. We built two Random Forest for Survival, Longitudinal, and Multivariate (RF-SLAM) algorithms to model the outcomes of IS and all-cause death separately using all baseline variables with missingness < 10%. The training data set was comprised of 70% of observations and the testing set of the remaining 30%. To assess variable importance in outcome prediction, Mean Decrease Accuracy was computed for each variable over all out-of-bag cross-validated predictions. Results: In 2,298 participants (median age 61.5 years [IQR 54.3-69.6], 20% female) during a mean follow-up of 3.5 years (SD 1.8 years), 84 (3.7%) patients had an ischemic stroke and 547 (23.8%) died. Patient-specific characteristics contributing most to ischemic stroke prediction with variable Mean Decrease Accuracies ≥ 2.5 were prior transient ischemic attack, CHA 2 DS 2 -VASc score, age, prior stroke, glucose, and blood urea nitrogen (model accuracy 0.95; 95% C.I. 0.93-0.97). Age, hemoglobin, glucose, INR, platelet count, BUN, and systolic blood pressure were the most important patient-specific predictors of all-cause death with variable Mean Decrease Accuracies ≥ 2.5 (model accuracy 0.76; 95% C.I. 0.72-0.79). Conclusions: Clinical and serologic characteristics identified by the RF-SLAM algorithm predict IS and all-cause death risks in patients with HFrEF and sinus rhythm. Future studies are needed to assess the impact of these factors on treatment effects in heart failure trials evaluating outcomes which include stroke.