Heart rate variability in the prediction of mortality: A systematic review and meta-analysis of healthy and patient populations

Measures of heart rate variability (HRV) as a predictor of risk of disease and mortality have been investigated from various perspectives for more than six decades. The aim of the present comprehensive meta-analysis is to examine eight different HRV parameters to determine their association with all-cause and cardiac mortality. A total of 32 studies and two individual participant datasets (IPD) with 37 samples and 38,008 participants were included. Lower HRV parameter values were significant predictors of higher mortality across different ages, sex, continents, populations and recording lengths. Most of the examined parameters showed comparable hazard ratios (HR). IPD sub-analysis for heart rate corrected HRV parameters confirmed the strong association between HRV and all-cause mortality. Meta-regressions revealed no effect modifier for HRs extracted from covariate-adjusted studies. Sub-analyses of studies comparing the lowest quartile of 5-min root mean square of succes-sive differences (RMSSD) vs. the other quartiles yielded a combined HR of 1.56 (95% CI: 1.32-1.85). The applicability of HRV measurement in preventive settings is discussed.

Automated summary

This comprehensive meta-analysis examines the association between measures of heart rate variability (HRV) and the risk of disease and mortality. The results show that lower HRV parameter values are significant predictors of higher mortality across different populations and recording lengths. The analysis confirms a strong association between HRV and all-cause mortality. Additionally, a sub-analysis highlights that individuals with the lowest quartile of 5-minute root mean square of successive differences (RMSSD) have a higher risk of mortality.