期刊
EUROPEAN JOURNAL OF HEART FAILURE
卷 23, 期 8, 页码 1346-1356出版社
WILEY
DOI: 10.1002/ejhf.2120
关键词
Heart failure; Sudden cardiac death; Clinical predictors
资金
- Novartis
- National Council for Scientific and Technological Development (CNPq, Brazil) [30833/2017-1]
- Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES)
This study found that integrating time-varying covariates significantly improved the prediction assessment of sudden cardiac death. Models combining baseline variables with time-updated variables independently predicted SCD risk, helping improve risk stratification and differentiate modes of death in chronic heart failure.
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.
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