ArticlePediatric research2021
Heart rate variability spectrum characteristics in children with sleep apnea.
Article in Pediatric research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.
- Association between Short-Term Exposure to Ozone and Heart Rate Variability: A Systematic Review and Meta-Analysis.International journal of environmental research and public health · 2022Pooled it
- Physiological and Sleep Profiles in Insomnia, OSA and COMISA: A Comparative Study in Portugal and Spain.Journal of sleep research · 2026Article
- Combined explainable deep learning model to predict pediatric sleep apnea from ECG and SpOMeasurement : journal of the International Measurement Confederation · 2026Article
- An explainable deep learning approach for sleep staging in sleep apnea patients across all age subgroups from pulse oximetry signals.Engineering applications of artificial intelligence · 2025Article
- Heart Rate Variability Applications in Medical Specialties: A Narrative Review.Applied psychophysiology and biofeedback · 2025Review
- Heart rate variability analysis in comorbid insomnia and sleep apnea (COMISA).Scientific reports · 2025Observational
- SleepECG-Net: Explainable Deep Learning Approach With ECG for Pediatric Sleep Apnea Diagnosis.IEEE journal of biomedical and health informatics · 2025Article
- RHRVEasy: Heart rate variability made easy.PloS one · 2024Article
- ECG-based convolutional neural network in pediatric obstructive sleep apnea diagnosis.Computers in biology and medicine · 2023Article
- Restless Sleep Disorder (RSD): a New Sleep Disorder in Children. A Rapid Review.Current neurology and neuroscience reports · 2022Review
- Heart rate variability as a potential biomarker of pediatric obstructive sleep apnea resolution.Sleep · 2022Article
- Oximetry Indices in the Management of Sleep Apnea: From Overnight Minimum Saturation to the Novel Hypoxemia Measures.Advances in experimental medicine and biology · 2022Article
- Conventional Machine Learning Methods Applied to the Automatic Diagnosis of Sleep Apnea.Advances in experimental medicine and biology · 2022Article
- Bispectral Analysis of Heart Rate Variability to Characterize and Help Diagnose Pediatric Sleep Apnea.Entropy (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundClassic spectral analysis of heart rate variability (HRV) in pediatric sleep apnea-hypopnea syndrome (SAHS) traditionally evaluates the very low frequency (VLF: 0-0.04 Hz), low frequency (LF: 0.04-0.15 Hz), and high frequency (HF: 0.15-0.40 Hz) bands. However, specific SAHS-related frequency bands have not been explored.
methodsOne thousand seven hundred and thirty-eight HRV overnight recordings from two pediatric databases (0-13 years) were evaluated. The first one (981 children) served as training set to define new HRV pediatric SAHS-related frequency bands. The associated relative power (RP) were computed in the test set, the Childhood Adenotonsillectomy Trial database (CHAT, 757 children). Their relationships with polysomnographic variables and diagnostic ability were assessed.
resultsTwo new specific spectral bands of pediatric SAHS within 0-0.15 Hz were related to duration of apneic events, number of awakenings, and wakefulness after sleep onset (WASO), while an adaptive individual-specific new band from HF was related to oxyhemoglobin desaturations, arousals, and WASO. Furthermore, these new spectral bands showed improved diagnostic ability than classic HRV.
conclusionsNovel spectral bands provide improved characterization of pediatric SAHS. These findings may pioneer a better understanding of the effects of SAHS on cardiac function and potentially serve as detection biomarkers. IMPACT: New specific heart rate variability (HRV) spectral bands are identified and characterized as potential biomarkers in pediatric sleep apnea. Spectral band BW1 (0.001-0.005 Hz) is related to macro sleep disruptions. Spectral band BW2 (0.028-0.074 Hz) is related to the duration of apneic events. An adaptive spectral band within the respiratory range, termed ABW3, is related to oxygen desaturations. The individual and collective diagnostic ability of these novel spectral bands outperforms classic HRV bands.
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