# Heart Rate Variability as a Predictor of Mortality in Heart Failure: A Systematic Review and Meta-Analysis

## TL;DR

Heart rate variability (HRV) is a strong predictor of mortality in heart failure patients, with SDNN being the most reliable measure.

## Contribution

This study provides a comprehensive meta-analysis showing HRV's robust predictive value for mortality in heart failure.

## Key findings

- HRV is significantly associated with mortality in heart failure patients (ES = 1.99, p < 0.001).
- Time-domain HRV measures like SDNN show the strongest predictive power for mortality.
- HRV improves risk stratification beyond ejection fraction and NYHA class, especially for sudden death.

## Abstract

Heart rate variability (HRV), a marker of autonomic function, has been proposed as a prognostic tool in heart failure (HF), but evidence remains fragmented. This meta-analysis synthesizes data on HRV’s predictive value for mortality in HF. Following PRISMA guidelines, PubMed, Embase, Cochrane, and other databases (2000-2024) were systematically searched for studies assessing HRV and mortality in HF. Ten studies (n = 10,544) were included, and random-effects meta-analyses were conducted. The pooled effect size (ES) for the HRV-mortality association was significant (ES = 1.99, 95% CI: 1.36-2.61, p < 0.001), with time-domain measures (standard deviation of NN intervals (SDNN)) showing the strongest prediction (ES = 1.75, I² = 71.49%). Subgroup analyses revealed consistent effects in heart failure with reduced ejection fraction (HFrEF) (ES = 1.74) and mixed populations (ES = 1.99), though heterogeneity was high (I² = 97.67%). HRV improved risk stratification beyond ejection fraction and New York Heart Association (NYHA) class, particularly for sudden death (hazard ratio (HR): 2.1-3.2). Impaired HRV is a robust mortality predictor in HF, with SDNN being the most reliable parameter. Standardization and HRV-guided therapy trials are needed to enhance clinical utility.