ArticleSleep medicine2020
Sleep heart rate variability assists the automatic prediction of long-term cardiovascular outcomes.
Article in Sleep medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed, 73 citations in OpenAlex.
- Delta-9-Tetrahydrocannabinol (THC) Before Bedtime: Feasibility and Mechanistic Pilot Study on Sleep and Cardiac Autonomic Activity.Journal of sleep research · 2026Article
- Association of Severe Obesity, Hypertension, and Physical Activity with 24 h Heart Rate Variability in Adults.Journal of cardiovascular development and disease · 2026Article
- Impact of Nonlinear Heart Rate Variability in Postoperative Complex Congenital Heart Disease: Insights From Repaired Tetralogy of Fallot and Fontan Palliation.Pediatric cardiology · 2026Article
- SleepJEPA: Learning the latent world of sleep with at-home sleep data to estimate disease risk.medRxiv : the preprint server for health sciences · 2026Article
- Sleep apnoea and its consequences: from animal models to precision medicine.Sleep medicine · 2026Review
- Predicting All-Cause Mortality in Patients With Obstructive Sleep Apnea Using Sleep-Related Features: A Machine-Learning Approach.Journal of clinical neurology (Seoul, Korea) · 2025Article
- Orthostatic testing for heart rate and heart rate variability monitoring in exercise science and practice.European journal of applied physiology · 2024Review
- Deriving Accurate Nocturnal Heart Rate, rMSSD and Frequency HRV from the Oura Ring.Sensors (Basel, Switzerland) · 2024Article
- Evaluating the impact of automatic positive airway pressure therapy on cardiovascular risk index and vascular behavior in patients with obstructive sleep apnea: a study on heterogeneity in the therapeutic response.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2024Article
- A foundational transformer leveraging full night, multichannel sleep study data accurately classifies sleep stages.medRxiv : the preprint server for health sciences · 2024Article
- Heart Rate Fragmentation, Ambulatory Blood Pressure, and Coronary Artery Calcification: A Population-Based Study.JACC. Asia · 2024Article
- Assessing Risk of Health Outcomes From Brain Activity in Sleep: A Retrospective Cohort Study.Neurology. Clinical practice · 2024Article
- Heart Rate and Heart Rate Variability in Healthy Preterm-Born Young Adults and Association with Vitamin D: A Wearable Device Assessment.Journal of clinical medicine · 2023Article
- Impact of CPAP Therapy on the Autonomic Nervous System.Biomedicines · 2023Article
- Article
- An Obstructive Sleep Apnea - A Novel Public Health Threat.Physiological research · 2023Review
- Impaired Cardiovascular Parameters in Resistance Training Practitioners Who Take Ergogenic Aids.Journal of cardiovascular development and disease · 2023Article
- Coupling analysis of heart rate variability and cortical arousal using a deep learning algorithm.PloS one · 2023Article
- Heart rate variability in different sleep stages is associated with metabolic function and glycemic control in type 2 diabetes mellitus.Frontiers in physiology · 2023Article
- Wearable Devices for Remote Monitoring of Heart Rate and Heart Rate Variability-What We Know and What Is Coming.Sensors (Basel, Switzerland) · 2022Review
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
Abstract
objectiveWe aimed to investigate the association between sleep HRV and long-term cardiovascular disease (CVD) outcomes, and further explore whether HRV features can assist the automatic CVD prediction.
methodsWe retrospectively analyzed polysomnography (PSG) data obtained from 2111 participants in the Sleep Heart Health Study, who were followed up for a median of 11.8 years after PSG acquisition. During follow-up, 1252 participants suffered CVD events (CVD group) and 859 participants remained CVD-free (non-CVD group). HRV measures, derived from time-domain and frequency-domain, were calculated. Regression models were created to determine the independent predictor for long-term CVD outcomes, and to explore the association between HRV and CVD latency. Furthermore, based on HRV and other clinical features, a model was trained to automatically predict CVD outcomes using the eXtreme Gradient Boosting algorithm.
resultsCompared with the non-CVD group, decreased HRV during sleep was found in the CVD group. HRV, particularly its component of high frequency (HF), was demonstrated to be independent predictor of CVD outcomes. Moreover, normalized HF was positively correlated with CVD latency. The proposed prediction model achieved a total accuracy of 75.3%, in which sleep HRV features served as a supplement to the well-recognized CVD risk factors, such as aging, adiposity and sleep disorders.
conclusionsAssociation between sleep HRV and long-term CVD outcomes was demonstrated here, suggesting that altered HRV during sleep might occur many years prior to the onset of CVD. Machine learning models, combining sleep HRV and other clinical characteristics, should be promising in the early prediction of CVD outcomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.