Heart rate variability in the prediction of mortality: a systematic review and meta-analysis of healthy and patient populations
Open accessAbstract
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 successive 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.
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Low HRV is a marker of autonomic dysfunction associated with poor cardiovascular outcomes.
“with low HRV being a marker of autonomic dysfunction associated with poor cardiovascular outcomes”
From Exercise benefits in cardiovascular diseases: From mechanisms to clinical implementation (2023) · cites this paper as [187]
Regular PA/exercise increases heart rate variability (HRV) in both healthy individuals and in patients with CVD.
“Regular PA/exercise increases heart rate variability (HRV) -a measure of efferent PNS (vagal nerve) activity to the heart, with low HRV being a marker of autonomic dysfunction associated with poor cardiovascular outcomes-in both healthy individuals and in patients with CVD.186,187”
From Exercise benefits in cardiovascular diseases: From mechanisms to clinical implementation (2023) · cites this paper as [187]
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- Authors
- Jarczok, M. N., Weimer, K., Braun, C., Williams, D. P., Thayer, J. F., Gündel, H. O., & Balint, E. M.
- Affiliations
- Universität Ulm (DE)
- University of California, Irvine (US)
- Corresponding author
- Jarczok, Marc N.
- ORCID
- Venue
- Neuroscience & Biobehavioral Reviews
- Publisher
- Elsevier BV
- Published
- 2022-12
- Volume
- 143
- Pages
- 104907
- ISSN
- 0149-7634 (ISSN-L)
- OpenAlex
- W4304943826
- Cited by
- 246
- References
- 114
- Citations by year
- 2026: 74 · 2025: 71 · 2024: 76 · 2023: 23 · 2022: 1
- FWCI
- 8.70
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (am, 521 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Neuroscience & Biobehavioral Reviews (acceptedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (R01AG013196, R01HL36310)
- U.S. Department of Health and Human Services
- National Institute on Aging (5-PO1-AG20166-04)
- Medical Research Council (G0902037, MR/K013351/1)
- British Heart Foundation (RG/13/2/30098)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiac Health and Mental Health
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiac electrophysiology and arrhythmias
- Keywords
- heart rate variability, mortality prediction, all-cause mortality, cardiac mortality, RMSSD, heart rate correction, risk prediction, healthy population, individual patient data
- MeSH terms
- Heart, Heart Rate, Humans, Proportional Hazards Models
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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