Nature and Science of Sleep (Jun 2024)

Using Apnea–Hypopnea Duration per Hour to Predict Hypoxemia Among Patients with Obstructive Sleep Apnea

  • Ma C,
  • Zhang Y,
  • Tian T,
  • Zheng L,
  • Ye J,
  • Liu H,
  • Zhao D

Journal volume & issue
Vol. Volume 16
pp. 847 – 853

Abstract

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Changxiu Ma,1 Ying Zhang,1 Tingchao Tian,2 Ling Zheng,1 Jing Ye,1 Hui Liu,1 Dahai Zhao1 1Department of Respiratory and Critical Care Medicine, Second Affiliated Hospital, Anhui Medical University, Hefei, 230601, People’s Republic of China; 2Department of Respiratory and Critical Care Medicine, Huoqiu First People’s Hospital, Huoqiu, 237400, People’s Republic of ChinaCorrespondence: Dahai Zhao, Second Affiliated Hospital, Anhui Medical University, 678 Furong Road, Hefei, Anhui Province, 230601, People’s Republic of China, Tel +86-13721027959, Email [email protected]: To explore the role of the mean apnea–hypopnea duration (MAD) and apnea–hypopnea duration per hour (HAD) in hypoxemia and evaluate whether they can effectively predict the occurrence of hypoxemia among adults with OSA.Patients and Methods: A total of 144 participants underwent basic information gathering and polysomnography (PSG). Logistic regression models were conducted to evaluate the best index in terms of hypoxemia. To construct the prediction model for hypoxemia, we randomly divided the participants into the training set (70%) and the validation set (30%).Results: The participants with hypoxemia tend to have higher levels of obesity, diabetes, AHI, MAD, and HAD compared with non-hypoxemia. The most relevant indicator of blood oxygen concentration is HAD (r = 0.73) among HAD, MAD, and apnea–hypopnea index (AHI). The fitness of HAD on hypoxemia showed the best. In the stage of establishing the prediction model, the area under the curve (AUC) values of both the training set and the validation set are 0.95. The increased HAD would elevate the risk of hypoxemia [odds ratio (OR): 1.30, 95% confidence interval (CI): 1.13– 1.49].Conclusion: The potential role of HAD in predicting hypoxemia underscores the significance of leveraging comprehensive measures of respiratory disturbances during sleep to enhance the clinical management and prognostication of individuals with sleep-related breathing disorders.Keywords: mean apnea–hypopnea duration, obstructive sleep apnea, apnea–hypopnea duration per hour, polysomnography, apnea–hypopnea index

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