Metrics of sleep apnea severity: beyond the apnea-hypopnea index
- PMID: 33693939
- PMCID: PMC8271129
- DOI: 10.1093/sleep/zsab030
Metrics of sleep apnea severity: beyond the apnea-hypopnea index
Abstract
Obstructive sleep apnea (OSA) is thought to affect almost 1 billion people worldwide. OSA has well established cardiovascular and neurocognitive sequelae, although the optimal metric to assess its severity and/or potential response to therapy remains unclear. The apnea-hypopnea index (AHI) is well established; thus, we review its history and predictive value in various different clinical contexts. Although the AHI is often criticized for its limitations, it remains the best studied metric of OSA severity, albeit imperfect. We further review the potential value of alternative metrics including hypoxic burden, arousal intensity, odds ratio product, and cardiopulmonary coupling. We conclude with possible future directions to capture clinically meaningful OSA endophenotypes including the use of genetics, blood biomarkers, machine/deep learning and wearable technologies. Further research in OSA should be directed towards providing diagnostic and prognostic information to make the OSA diagnosis more accessible and to improving prognostic information regarding OSA consequences, in order to guide patient care and to help in the design of future clinical trials.
Keywords: apnea; cardiovascular; hypopnea; hypoxia; lung; sleep.
© Sleep Research Society 2021. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.
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Comment in
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The AHI is useful but limited: how can we do better?Sleep. 2021 Sep 13;44(9):zsab150. doi: 10.1093/sleep/zsab150. Sleep. 2021. PMID: 34181025 Free PMC article. No abstract available.
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Beyond the apnea-hypopnea index: alternative diagnostic parameters and machine learning solutions for estimation of sleep apnea severity.Sleep. 2021 Sep 13;44(9):zsab134. doi: 10.1093/sleep/zsab134. Sleep. 2021. PMID: 34515318 Free PMC article. No abstract available.
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