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

利用每小时呼吸暂停低通气持续时间预测阻塞性睡眠呼吸暂停患者的低氧血症

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Abstract

PURPOSE: 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.

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