Prospective study on the diagnostic model of obstructive sleep apnea_Chinese Journal of Respiratory and Critical Care Medicine

Authors：

 SUN Kai ¹ , LEI Fei ² , ZHENG Aibo ¹ , ZHOU Liping ¹ , MA Shengjun ¹ , LIU Yong ¹ , PENG Juan ¹

1. Department of Pulmonary and Critical Care Medicine, Zigong Fourth People’s Hospital, Zigong, Sichuan 643000, P.R.China;
2. Sleep Medicine Center, West China Hospital, Sichuan University, Chengdu 610041, P.R. China;

Corresponding?author：

SUN Kai, Email: 26576628@qq.com

Keywords：

Sleep apnea obstructive; diagnostic model; prospective studies; polysomnography

DOI：

10.7507/1671-6205.202412073

Video：

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Objective To prospectively verify the accuracy and reliability of the diagnostic model of obstructive sleep apnea (OSA), including the probability model and disease severity model, and to explore a simple and cost-effective method for screening of OSA. Methods A total of 996 patients who underwent polysomnography in Zigong Fourth People’s Hospital(590 cases) and West China Hospital of Sichuan University(406 cases) were consecutively and prospectively included as the research subjects. Firstly, the OSA diagnostic model was used for the diagnostic test; then polysomnography was performed; Finally, taking polysomnography as the gold standard, the sensitivity, specificity, accuracy, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio and area under the ROC curve of OSA diagnostic model were calculated, and the reliability analysis of the model’s results was carried out. Results The sensitivity, specificity and accuracy of the OSA diagnostic model were 76.38%(595/779), 83.41%(181/217) and 77.91%(776/996) respectively, the positive predictive value is 94.29%, negative predictive value is 45.49%, positive likelihood ratio is 4.604, negative likelihood ratio is 0.283; and the area under the ROC curve was 0.866. The reliability analysis of OSA diagnostic model showed that there was no significant difference in the bias comparison of AHI; the intra-class correlation coefficient(ICC) between AHI in the OSA diagnostic model and AHI in polysomnography was 0.659, with a relatively strong consistency degree; the intra-class correlation coefficient between the lowest SpO₂ in the OSA diagnostic model and the lowest SpO₂ in polysomnography was 0.563, with a moderate consistency degree. Conclusions The OSA diagnostic model can better predict the probability of illness and assess the severity of the disease, which is helpful for the early detection, diagnosis and treatment of OSA. The OSA diagnostic model is suitable for popularization and application in primary hospitals and when polysomnography is not available in time.

Citation： SUN Kai, LEI Fei, ZHENG Aibo, ZHOU Liping, MA Shengjun, LIU Yong, PENG Juan. Prospective study on the diagnostic model of obstructive sleep apnea. Chinese Journal of Respiratory and Critical Care Medicine, 2025, 24(2): 92-96. doi: 10.7507/1671-6205.202412073 Copy

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9.	孫楷, 聶洪玉, 徐東蘭, 等. 鼾癥中OSAHS的預測模型及危險因素分析. 國際呼吸雜志, 2019, 39(14): 1067-1072.
10.	Johns MW. A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep, 1991, 14(6): 540-545.
11.	American Academy of Sleep Medicine. The AASM Manual for the Scoring of Sleep and Associated Events Summary of Updates in Version 2.6. https://aasm.org/clinical-resources/scoring-manual/.
12.	中華醫學會, 中華醫學會雜志社, 中華醫學會全科醫學分會, 等. 成人阻塞性睡眠呼吸暫停基層診療指南(2018年). 中華全科醫師雜志, 2019, 18(1): 21-29.
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16.	Gottlieb DJ, Punjabi NM. Diagnosis and Management of Obstructive Sleep Apnea: A Review. JAMA, 2020, 323(14): 1389-1400.

1. 阻塞性睡眠呼吸暫停低通氣綜合征診治指南(基層版)寫作組. 阻塞性睡眠呼吸暫停低通氣綜合征診治指南(基層版). 中國呼吸與危重監護雜志, 2015, 14(4): 398-405.
2. Akashiba T, Inoue Y, Uchimura N, et al. Sleep Apnea Syndrome (SAS) Clinical Practice Guidelines 2020. Respir Investig, 2022, 60(1): 3-32.
3. Benjafield AV, Ayas NT, Eastwood PR, et al. Estimation of the global prevalence and burden of obstructive sleep apnoea: a literature-based analysis. Lancet Respir Med, 2019, 7(8): 687-698.
4. Zasadzińska-Stempniak K, Zaj?czkiewicz H, Kukwa A. Prevalence of Obstructive Sleep Apnea in the Young Adult Population: A Systematic Review. J Clin Med, 2024, 13(5): 1386.
5. Godoy PH, Nucera APCDS, Colcher AP, et al. Screening for obstructive sleep apnea in elderly: performance of the Berlin and STOP-Bang questionnaires and the Epworth sleepiness scale using polysomnography as gold standard. Sleep Sci, 2022, 15(2): 136-142.
6. Behar JA, Palmius N, Li Q, et al. Feasibility of Single Channel Oximetry for Mass Screening of Obstructive Sleep Apnea. EClinicalMedicine, 2019, 11: 81-88.
7. 張靜, 何珊, 陳潔, 等. 建立基于臨床數據的兒童阻塞性睡眠呼吸暫停綜合征預測模型. 醫學綜述, 2020, 26(11): 2223-2227+2234.
8. 孫楷, 聶洪玉, 徐東蘭, 等. 鼾癥患者中阻塞性睡眠呼吸暫停低通氣綜合征的篩查及危險因素分析. 中國呼吸與危重監護雜志, 2019, 18(1): 26-30.
9. 孫楷, 聶洪玉, 徐東蘭, 等. 鼾癥中OSAHS的預測模型及危險因素分析. 國際呼吸雜志, 2019, 39(14): 1067-1072.
10. Johns MW. A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep, 1991, 14(6): 540-545.
11. American Academy of Sleep Medicine. The AASM Manual for the Scoring of Sleep and Associated Events Summary of Updates in Version 2.6. https://aasm.org/clinical-resources/scoring-manual/.
12. 中華醫學會, 中華醫學會雜志社, 中華醫學會全科醫學分會, 等. 成人阻塞性睡眠呼吸暫停基層診療指南(2018年). 中華全科醫師雜志, 2019, 18(1): 21-29.
13. Iannella G, Maniaci A, Magliulo G, et al. Current challenges in the diagnosis and treatment of obstructive sleep apnea syndrome in the elderly. Pol Arch Intern Med, 2020, 130(7-8): 649-654.
14. 陸林. 中國睡眠醫學中心標準化建設指南[M]. 北京: 人民衛生出版社, 2021, 5-8.
15. de Araujo Dantas AB, Gon?alves FM, Martins AA, et al. Worldwide prevalence and associated risk factors of obstructive sleep apnea: a meta-analysis and meta-regression. Sleep Breath, 2023, 27(6): 2083-2109.
16. Gottlieb DJ, Punjabi NM. Diagnosis and Management of Obstructive Sleep Apnea: A Review. JAMA, 2020, 323(14): 1389-1400.

Chinese Journal of Respiratory and Critical Care Medicine

Prospective study on the diagnostic model of obstructive sleep apnea

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