Nocturnal Heart Rate Variability Might Help in Predicting Severe Obstructive Sleep-Disordered Breathing

Author:

Statello Rosario12,Rossi Stefano2ORCID,Pisani Francesco3ORCID,Bonzini Matteo45,Andreoli Roberta26,Martini Agnese7,Puligheddu Monica1ORCID,Cocco Pierluigi8,Miragoli Michele259ORCID

Affiliation:

1. Department of Medical Sciences and Public Health, University of Cagliari, 09124 Cagliari, Italy

2. Department of Medicine and Surgery, University of Parma, 43121 Parma, Italy

3. Child Neuropsychiatric Unit, Department of Human Neuroscience, Sapienza University of Rome, 00185 Rome, Italy

4. Occupational Medicine, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy

5. Department of Clinical Sciences and Community Health, University of Milan, 20122 Milan, Italy

6. CERT, Center of Excellence for Toxicological Research, University of Parma, 43121 Parma, Italy

7. INAIL, The National Institute for Insurance against Accidents at Work, Department of Medicine, Epidemiology, Workplace and Environmental Hygiene, 00144 Rome, Italy

8. Centre for Occupational and Environmental Health, Division of Population Health, Health Services Research & Primary Care, University of Manchester, Manchester M13 9PL, UK

9. Department of Molecular Cardiology, Humanitas Research Hospital, IRCCS, 20089 Rozzano, Italy

Abstract

Obstructive sleep apnea (OSA) can have long-term cardiovascular and metabolic effects. The identification of OSA-related impairments would provide diagnostic and prognostic value. Heart rate variability (HRV) as a measure of cardiac autonomic regulation is a promising candidate marker of OSA and OSA-related conditions. We took advantage of the Physionet Apnea-ECG database for two purposes. First, we performed time- and frequency-domain analysis of nocturnal HRV on each recording of this database to evaluate the cardiac autonomic regulation in patients with nighttime sleep breathing disorders. Second, we conducted a logistic regression analysis (backward stepwise) to identify the HRV indices able to predict the apnea–hypopnea index (AHI) categories (i.e., “Severe OSA”, AHI ≥ 30; “Moderate-Mild OSA”, 5 ≥ AHI < 30; and “Normal”, AHI < 5). Compared to the “Normal”, the “Severe OSA” group showed lower high-frequency power in normalized units (HFnu) and higher low-frequency power in normalized units (LFnu). The standard deviation of normal R–R intervals (SDNN) and the root mean square of successive R–R interval differences (RMSSD) were independently associated with sleep-disordered breathing. Our findings suggest altered cardiac autonomic regulation with a reduced parasympathetic component in OSA patients and suggest a role of nighttime HRV in the characterization and identification of sleep breathing disorders.

Funder

Occupational health and prevention of the obstructive sleep apnoea: a silent epidemic

Publisher

MDPI AG

Subject

General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology

Reference59 articles.

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