February 10, 2021Open Access
View Full PaperDynamic changes in cardiovascular and systemic parameters prior to sudden cardiac death in heart failure with reduced ejection fraction: a PARADIGM‐HF analysis
Key Result
Time-updated clinical and biomarker covariates improved sudden cardiac death risk prediction in heart failure, identifying a high-risk subgroup (HR 7.7; 95% CI 3.6-16.5; P<0.001).
Study Design
Type
Observational (n=8,399)
Structured PICO
Does integrating time-varying covariates improve the prediction of sudden cardiac death in patients with HFrEF compared to single time-point assessments?
P
Population
8,399 patients with heart failure with reduced ejection fraction enrolled in the PARADIGM-HF trial
I
Intervention
Integration of time-varying covariates (NYHA class, heart rate, albumin, uric acid, total bilirubin, BUN, total cholesterol) into prognostic models
C
Comparator
Single time-point (baseline) assessments
O
Outcome
Sudden cardiac death (SCD)hard clinical
Integrating time-varying clinical and biomarker covariates significantly improves the prediction of sudden cardiac death in patients with HFrEF compared to baseline assessments alone.
Main Result
Effect estimate: HR 7.7 (95% CI 3.6-16.5)
p-value: p=< 0.001
Abstract
Abstract Aims 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. Methods and results 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 1 year prior to the event ( P interaction < 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). Conclusions 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.