Abstract
Heart failure with preserved ejection fraction (HFpEF) presents a challenge in clinical practice due to its complexity and impact on morbidity and mortality. The aim of this systematic review and meta-analysis (SR/MA) was to evaluate the value of B-Type Natriuretic Peptide (BNP) and NT-proBNP in predicting overall adverse outcomes, cardiovascular events, and mortality, in patients with HFpEF. This SR/MA included observational studies and randomized controlled trials (RCTs) that reported the use of BNP and NT-proBNP as prognostic biomarkers for adverse outcomes in HFpEF patients. A comprehensive literature search was conducted using PubMed, EMBASE, and Google, without language restrictions, from inception until June 2024. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. The quality and risk of bias of the included studies were assessed using the Newcastle-Ottawa Scale (NOS). Twenty-two studies involving 10,158 HFpEF patients were included. The analysis showed that BNP is a significant predictor of overall adverse events in HFpEF patients, with an overall HR of 1.34 (95% CI: 1.20-1.52). Similarly, BNP was a significant predictor of cardiovascular events and mortality in HFpEF patients with a HR of 1.36 (95% CI 1.12-1.64) and HR of 1.44 (95% CI: 1.04-1.84), respectively. When analyzing data for NT-proBNP predictive potential, 3 studies confirmed that NT-proBNP is a significant independent prognostic indicator for adverse events, with an overall HR of 1.80 (95% CI: 1.38-2.35). Comparable results were seen for mortality, with higher NT-proBNP levels associated with increased mortality risk and the MA showing a HR of 1.65 (95% CI: 1.55-1.76). This systematic review highlights the valuable prognostic role of BNP and NT-proBNP in predicting overall adverse outcome, cardiovascular events, and mortality in HFpEF patients. Our findings underscore the importance of further research to establish standardized thresholds and investigate BNP and NT-proBNP's potential in predicting morbidity and mortality.
Published Version
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