Yuhan Wang, Wuriliga Yue, Beini Zhou, Jingyi Zhang, Yang He, Mengcan Wang, Ke Hu
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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.</p><p><strong>Results: </strong>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 <i>Z</i> 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 SpO<sub>2</sub> (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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":"17 ","pages":"1101-1112"},"PeriodicalIF":3.4000,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12130169/pdf/","citationCount":"0","resultStr":"{\"title\":\"The Hourly Apnea-Hypopnea Duration Better Correlates with OSA-Related Nocturnal Hypoxemia and Excessive Daytime Sleepiness Rather Than AHI.\",\"authors\":\"Yuhan Wang, Wuriliga Yue, Beini Zhou, Jingyi Zhang, Yang He, Mengcan Wang, Ke Hu\",\"doi\":\"10.2147/NSS.S505702\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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 <i>Z</i> 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.</p><p><strong>Results: </strong>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 <i>Z</i> 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 SpO<sub>2</sub> (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.</p><p><strong>Conclusion: </strong>The HAD better correlates with OSA-related nocturnal hypoxemia and EDS rather than AHI. 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引用次数: 0
摘要
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。
The Hourly Apnea-Hypopnea Duration Better Correlates with OSA-Related Nocturnal Hypoxemia and Excessive Daytime Sleepiness Rather Than AHI.
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.
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.