Association between nocturnal heart rate variability and incident cardiovascular disease events: The HypnoLaus population-based study.
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State: Public
Version: Supplementary document
License: Not specified
Serval ID
serval:BIB_19E47F19C123
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Association between nocturnal heart rate variability and incident cardiovascular disease events: The HypnoLaus population-based study.
Journal
Heart rhythm
ISSN
1556-3871 (Electronic)
ISSN-L
1547-5271
Publication state
Published
Issued date
04/2022
Peer-reviewed
Oui
Volume
19
Number
4
Pages
632-639
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
Publication Status: ppublish
Abstract
Although heart rate variability (HRV) is widely used to assess cardiac autonomic function, few studies have specifically investigated nocturnal HRV.
The purpose of this study was to assess the association between nocturnal HRV and cardiovascular disease (CVD) incidence over 4 years in a population-based sample.
A total of 1784 participants (48.2% men; 58 ± 11 years) from the HypnoLaus population-based cohort free of CVD at baseline were included. Polysomnography-based electrocardiograms were exported to analyze time- and frequency-domain HRV, Poincaré plots indices, detrended fluctuation analysis, acceleration capacity (AC) and deceleration capacity (DC), entropy, heart rate fragmentation (HRF), and heart rate turbulence. Multivariable-adjusted Cox regression analysis was used to assess the association between HRV indices and incident CVD events.
Sixty-seven participants (3.8%) developed CVD over mean follow-up of 4.1 ± 1.1 years. In a fully adjusted model, AC (hazard ratio per 1-SD increase; 95% confidence interval: 1.59; 1.17-2.16; P = .004), DC (0.63; 0.47-0.84; P = .002), and HRF (1.41; 1.11-1.78; P = .005) were the only HRV metrics significantly associated with incident CVD events after controlling for false discovery rate.
Nocturnal novel HRV parameters such as AC, DC, and HRF are better predictors of CVD events than time and frequency traditional HRV parameters. These findings suggest a form of dysautonomia and fragmented rhythms, but further experimental studies are needed to delineate the underlying physiological mechanisms of these novel HRV parameters.
The purpose of this study was to assess the association between nocturnal HRV and cardiovascular disease (CVD) incidence over 4 years in a population-based sample.
A total of 1784 participants (48.2% men; 58 ± 11 years) from the HypnoLaus population-based cohort free of CVD at baseline were included. Polysomnography-based electrocardiograms were exported to analyze time- and frequency-domain HRV, Poincaré plots indices, detrended fluctuation analysis, acceleration capacity (AC) and deceleration capacity (DC), entropy, heart rate fragmentation (HRF), and heart rate turbulence. Multivariable-adjusted Cox regression analysis was used to assess the association between HRV indices and incident CVD events.
Sixty-seven participants (3.8%) developed CVD over mean follow-up of 4.1 ± 1.1 years. In a fully adjusted model, AC (hazard ratio per 1-SD increase; 95% confidence interval: 1.59; 1.17-2.16; P = .004), DC (0.63; 0.47-0.84; P = .002), and HRF (1.41; 1.11-1.78; P = .005) were the only HRV metrics significantly associated with incident CVD events after controlling for false discovery rate.
Nocturnal novel HRV parameters such as AC, DC, and HRF are better predictors of CVD events than time and frequency traditional HRV parameters. These findings suggest a form of dysautonomia and fragmented rhythms, but further experimental studies are needed to delineate the underlying physiological mechanisms of these novel HRV parameters.
Keywords
Autonomic Nervous System, Cardiovascular Diseases/diagnosis, Cardiovascular Diseases/epidemiology, Electrocardiography, Female, Heart, Heart Rate/physiology, Humans, Male, Cardiovascular disease, Electrocardiogram, Heart rate fragmentation, Heart rate variability, Prospective study, Sleep
Pubmed
Web of science
Create date
11/12/2021 12:36
Last modification date
18/07/2024 6:09