Back to Search Start Over

Cardiovascular and non-cardiovascular death distinction

Authors :
Wouter Ouwerkerk
John G.F. Cleland
Stefan D. Anker
Leong L. Ng
Dirk J. van Veldhuisen
Adriaan A. Voors
Marco Metra
Jasper Tromp
Gerasimos Filippatos
João Pedro Ferreira
Kenneth Dickstein
Faiez Zannad
Epidemiology and Data Science
Dermatology
Cardiovascular Centre (CVC)
Source :
European journal of heart failure, 22(1), 81-89. Wiley-Blackwell, European Journal of Heart Failure, 22(1), 81-89. Wiley
Publication Year :
2020
Publisher :
Wiley, 2020.

Abstract

AIMS: Heart failure (HF) patients are at high-risk of cardiovascular (CV) events, including CV death. Nonetheless, a substantial proportion of these patients die from non-CV causes. Identifying patients at higher risk for each individual event may help selecting patients for clinical trials and tailoring cardiovascular therapies. The aims of the present study are to: (i) characterize patients according to CV vs. non-CV death; (ii) develop models for the prediction of the respective events; (iii) assess the models' performance to differentiate CV from non-CV death. METHODS AND RESULTS: This study included 2309 patients with HF from the BIOSTAT-CHF (a systems BIOlogy Study to TAilored Treatment in Chronic Heart Failure) study. Competing-risk models were used to assess the best combination of variables associated with each cause-specific death. Results were validated in an independent cohort of 1738 HF patients. The best model to predict CV death included low blood pressure, estimated glomerular filtration rate ≤ 60 mL/min, peripheral oedema, previous HF hospitalization, ischaemic HF, chronic obstructive pulmonary disease, elevated N-terminal pro-B-type natriuretic peptide (NT-proBNP), and troponin (c-index = 0.73). The non-CV death model incorporated age > 75 years, anaemia and elevated NT-proBNP (c-index = 0.71). Both CV and non-CV death rose by quintiles of the risk scores; yet these models allowed the identification of patients in whom absolute CV death rates clearly outweigh non-CV death ones. These findings were externally replicated, but performed worse in a less severely diseased population. CONCLUSIONS: Risk models for predicting CV and non-CV death allowed the identification of patients at higher absolute risk of dying from CV causes (vs. non-CV ones). Troponin helped in predicting CV death only, whereas NT-proBNP helped in the prediction of both CV and non-CV death. These findings can be useful both for tailoring therapies and for patient selection in HF trials in order to attain CV event enrichment.

Details

Language :
English
ISSN :
18790844 and 13889842
Volume :
22
Issue :
1
Database :
OpenAIRE
Journal :
European Journal of Heart Failure
Accession number :
edsair.doi.dedup.....5f14c8ad8cce6a5494894865cbbe1223