ArticleNature and science of sleep2024
Using Apnea-Hypopnea Duration per Hour to Predict Hypoxemia Among Patients with Obstructive Sleep Apnea.
Article in Nature and science of sleep, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Predictive value of the STOP-Bang Questionnaire for respiratory depression risk in patients undergoing painless gastrointestinal endoscopy.Perioperative medicine (London, England) · 2025Article
- Exploring the Dose-Response Relationship between Mandibular Protrusion and Respiratory Effort Burden in Oral Appliance Therapy for Obstructive Sleep Apnea.Annals of the American Thoracic Society · 2025Article
- The Hourly Apnea-Hypopnea Duration Better Correlates with OSA-Related Nocturnal Hypoxemia and Excessive Daytime Sleepiness Rather Than AHI.Nature and science of sleep · 2025Article
- The dose-effect and clinical prediction of the longest apnea duration driving the decrease of blood oxygen: a large sample OSA study with 34-second and 52-second cut-off values was established.Frontiers in physiology · 2025Article
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Authors and funding
7 authors.
Funding
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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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