The Hourly Apnea-Hypopnea Duration Better Correlates with OSA-Related Nocturnal Hypoxemia and Excessive Daytime Sleepiness Rather Than AHI.

IF 3.4 2区医学 Q2 CLINICAL NEUROLOGY

Nature and Science of Sleep Pub Date : 2025-05-29 eCollection Date: 2025-01-01 DOI:10.2147/NSS.S505702

Yuhan Wang, Wuriliga Yue, Beini Zhou, Jingyi Zhang, Yang He, Mengcan Wang, Ke Hu

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Abstract

Background: The apnea-hypopnea index (AHI) has limitations in assessing nocturnal hypoxemia and excessive daytime sleepiness (EDS) in obstructive sleep apnea (OSA) patients. This study evaluated whether hourly apnea-hypopnea duration (HAD) and mean apnea-hypopnea duration (MAD) could complement or outperform AHI.

Methods: This study included 1069 OSA patients, of whom 754 completed the Epworth Sleepiness Scale (ESS). Multivariable regression models evaluated the associations between AHI, MAD, HAD, and nocturnal hypoxemia, and standardized Z scores were used for comparison. The predictive ability of AHI, MAD, and HAD models for EDS was evaluated using goodness-of-fit indices, and receiver operating characteristic (ROC) curve analysis was performed using bootstrapping techniques.

Results: Nocturnal hypoxemia was observed in 317 participants (29.65%). Patients with nocturnal hypoxemia had significantly higher AHI (43.19 ± 18.41 vs 21.78 ± 14.73 events/hour, P < 0.001) and longer HAD (16.71 ± 7.48 vs 8.24 ± 5.40 minutes, P < 0.001). After adjusting for age, sex, and BMI, AHI and HAD were still significantly associated with nocturnal hypoxemia (P < 0.05). Standardized Z scores analysis revealed that HAD had the strongest association with nocturnal hypoxemia (HAD: OR = 3.69, 95% CI: 3.06-4.46, P < 0.0001; AHI: OR = 3.48, 95% CI: 2.90-4.18, P < 0.0001; MAD: OR = 1.01, 95% CI: 0.88-1.15, P = 0.9314) and mean SpO₂ (HAD: β = -0.91, 95% CI: -1.02--0.79, P < 0.0001; AHI: β = -0.85, 95% CI: -0.97--0.74, P < 0.0001; MAD: β = 0.00, 95% CI: -0.12-0.12, P = 0.9595), outperforming AHI and MAD. The HAD model showed the best fit for predicting EDS, with an area under the curve of 0.61 at a threshold of 5.63.

Conclusion: The HAD better correlates with OSA-related nocturnal hypoxemia and EDS rather than AHI. The duration of respiratory events warrants more investigation in clinical assessment.

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每小时呼吸暂停-低呼吸持续时间与osa相关的夜间低氧血症和日间过度嗜睡的相关性更好，而不是AHI。

背景：呼吸暂停低通气指数（AHI）在评估阻塞性睡眠呼吸暂停（OSA）患者夜间低氧血症和白天过度嗜睡（EDS）方面存在局限性。本研究评估每小时呼吸暂停低通气持续时间（HAD）和平均呼吸暂停低通气持续时间（MAD）是否可以补充或优于AHI。方法：本研究纳入1069例OSA患者，其中754例完成Epworth嗜睡量表（ESS）。多变量回归模型评估AHI、MAD、HAD和夜间低氧血症之间的关系，并使用标准化Z评分进行比较。采用拟合优度指数评估AHI、MAD和HAD模型对EDS的预测能力，采用bootstrapping技术进行受试者工作特征（ROC）曲线分析。结果：夜间低氧血症317例（29.65%）。夜间低氧血症患者AHI较高（43.19±18.41 vs 21.78±14.73事件/小时，P < 0.001）， had较长（16.71±7.48 vs 8.24±5.40分钟，P < 0.001）。在调整年龄、性别和BMI后，AHI和HAD仍与夜间低氧血症显著相关（P < 0.05）。标准化Z评分分析显示HAD与夜间低氧血症的相关性最强(HAD: OR = 3.69, 95% CI: 3.06-4.46, P < 0.0001；Ahi: or = 3.48, 95% ci: 2.90-4.18, p < 0.0001；MAD: OR = 1.01, 95% CI: 0.88-1.15, P = 0.9314)和平均SpO2 (HAD: β = -0.91, 95% CI: -1.02—0.79,P < 0.0001；Ahi: β = -0.85, 95% ci: -0.97—0.74,p < 0.0001；MAD: β = 0.00, 95% CI: -0.12-0.12, P = 0.9595)，优于AHI和MAD。HAD模型对EDS的拟合效果最好，在5.63阈值下曲线下面积为0.61。结论：HAD与osa相关的夜间低氧血症和EDS的相关性优于AHI。呼吸事件的持续时间值得在临床评估中进行更多的调查。

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来源期刊

Nature and Science of Sleep Neuroscience-Behavioral Neuroscience

CiteScore

5.70

自引率

5.90%

发文量

245

审稿时长

16 weeks

期刊介绍： Nature and Science of Sleep is an international, peer-reviewed, open access journal covering all aspects of sleep science and sleep medicine, including the neurophysiology and functions of sleep, the genetics of sleep, sleep and society, biological rhythms, dreaming, sleep disorders and therapy, and strategies to optimize healthy sleep. Specific topics covered in the journal include: The functions of sleep in humans and other animals Physiological and neurophysiological changes with sleep The genetics of sleep and sleep differences The neurotransmitters, receptors and pathways involved in controlling both sleep and wakefulness Behavioral and pharmacological interventions aimed at improving sleep, and improving wakefulness Sleep changes with development and with age Sleep and reproduction (e.g., changes across the menstrual cycle, with pregnancy and menopause) The science and nature of dreams Sleep disorders Impact of sleep and sleep disorders on health, daytime function and quality of life Sleep problems secondary to clinical disorders Interaction of society with sleep (e.g., consequences of shift work, occupational health, public health) The microbiome and sleep Chronotherapy Impact of circadian rhythms on sleep, physiology, cognition and health Mechanisms controlling circadian rhythms, centrally and peripherally Impact of circadian rhythm disruptions (including night shift work, jet lag and social jet lag) on sleep, physiology, cognition and health Behavioral and pharmacological interventions aimed at reducing adverse effects of circadian-related sleep disruption Assessment of technologies and biomarkers for measuring sleep and/or circadian rhythms Epigenetic markers of sleep or circadian disruption.