Determinants of apnea-hypopnea index variability during home sleep testing.
Autor: | Martinot JB; Sleep Laboratory, CHU Université Catholique de Louvain (UCL), Namur Site Sainte-Elisabeth, Namur, Belgium; Institute of Experimental and Clinical Research, UCL Bruxelles Woluwe, Brussels, Belgium. Electronic address: martinot.j@respisom.be., Le-Dong NN; Sunrise, Namur, Belgium., Tamisier R; University Grenoble Alpes, HP2 Laboratory, Inserm U1300, Grenoble, France; EFRC Laboratory, Grenoble Alpes University Hospital, Grenoble, France., Bailly S; University Grenoble Alpes, HP2 Laboratory, Inserm U1300, Grenoble, France; EFRC Laboratory, Grenoble Alpes University Hospital, Grenoble, France., Pépin JL; University Grenoble Alpes, HP2 Laboratory, Inserm U1300, Grenoble, France; EFRC Laboratory, Grenoble Alpes University Hospital, Grenoble, France. |
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Jazyk: | angličtina |
Zdroj: | Sleep medicine [Sleep Med] 2023 Nov; Vol. 111, pp. 86-93. Date of Electronic Publication: 2023 Sep 12. |
DOI: | 10.1016/j.sleep.2023.09.002 |
Abstrakt: | Background: A single-night attended in-laboratory polysomnography or home sleep testing are common approaches for obstructive sleep apnea (OSA) diagnosis. However, internight variability in apnea-hypopnea index value is common, and may result in misclassification of OSA severity and inapropriate treatment decisions. Objective: To investigate factors determining short-term apnea-hypopnea index variability using multi-night automated home sleep testing, and to determine how this variability impacts clinical decisions. Patients/methods: Adults with suspected OSA who successfully performed three home sleep tests using measurements of mandibular jaw movements (Sunrise, Namur, Belgium) combined with automated machine learning analysis were enrolled. Data analysis included principal component analysis, generalized estimating equation regression and qualitative agreement analysis. Results: 160 individuals who performed three sleep tests over a mean of 8.78 ± 8.48 days were included. The apnea-hypopnea index varied by -0.88 events/h (5th-95th percentile range: -14.33 to 9.72 events/h). Based on a single-night recording, rates of overtreatment and undertreatment would have been of 13.5% and 6.0%, respectively. Regression analysis adjusted for age, sex, body mass index, total sleep time, and time between home sleep tests showed that time spent in deep non-rapid eye movement sleep and with head in supine position were independent significant predictors of the apnea-hypopnea index variability. Conclusions: At the individual level, short-term internight variability in the apnea-hypopnea index was significantly associated with time spent in deep non-rapid eye movement sleep and head in supine position. Clinical decisions based on a single-night testing may lead to errors in OSA severity classification and incorrect therapeutic decisions. Competing Interests: Declaration of competing interest Jean-Benoît Martinot is a scientific advisor to Sunrise and has been an investigator in pharmaceutical trials for Jazz Pharmaceuticals and Theranexus. Nhat-Nam Le-Dong is an employee of Sunrise. Jean-Louis Pépin is a scientific advisor to Sunrise, has received grants and/or personal fees from ResMed, Philips, Fisher & Paykel, Sefam, AstraZeneca, AGIR à dom, Elevie, VitalAire, Boehringer Ingelheim, Jazz Pharmaceuticals and Itamar Medical, and has received research support for clinical studies from Mutualia and Air Liquide Foundation. There was no funding or other financial support for this research from Sunrise. Renaud Tamisier and Sébastien Bailly have no financial disclosures. (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.) |
Databáze: | MEDLINE |
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