Dynamic changes in cardiovascular and systemic parameters prior to sudden cardiac death in heart failure with reduced ejection fraction: a PARADIGM-HF analysis.

Abstract

Prognostic models of sudden cardiac death (SCD) typically incorporate data at only a single time-point. We investigated independent predictors of SCD addressing the impact of integrating time-varying covariates to improve prediction assessment. We studied 8399 patients enrolled in the PARADIGM-HF trial and identified independent predictors of SCD (n=561, 36% of total deaths) using time-updated multivariable-adjusted Cox models, classification and regression tree (CART), and logistic regression analysis. Compared with patients who were alive or died from non-sudden cardiovascular deaths, patients who suffered a SCD displayed a distinct temporal profile of New York Heart Association (NYHA) class, heart rate and levels of three biomarkers (albumin, uric acid and total bilirubin), with significant differences observed more than 1year prior to the event (Pinteraction < 0.001). In multivariable models adjusted for baseline covariates, seven time-updated variables independently contributed to SCD risk (incremental likelihood chi-square=46.2). CART analysis identified that baseline variables (implantable cardioverter-defibrillator use and N-terminal prohormone of B-type natriuretic peptide levels) and time-updated covariates (NYHA class, total bilirubin, and total cholesterol) improved risk stratification. CART-defined subgroup of highest risk had nearly an eightfold increment in SCD hazard (hazard ratio 7.7, 95% confidence interval 3.6-16.5; P < 0.001). Finally, changes over time in heart rate, NYHA class, blood urea nitrogen and albumin levels were associated with differential risk of sudden vs. non-sudden cardiovascular deaths (P < 0.05). Beyond single time-point assessments, distinct changes in multiple cardiac-specific and systemic variables improved SCD risk prediction and were helpful in differentiating mode of death in chronic heart failure.