ArticleSleep & breathing = Schlaf & Atmung2025
A prediction algorithm for severe OSA to facilitate decision for split night study.
Article in Sleep & breathing = Schlaf & Atmung, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
backgroundA split-night sleep study is a specialized diagnostic tool that combines the evaluation and treatment of sleep apnea into a single night. The initial phase involves monitoring physiological parameters to assess the severity of sleep apnea, measured by the Apnea-Hypopnea Index (AHI). Subsequently, Positive Airway Pressure (PAP) therapy is initiated. This study aims to predict full-night AHI and severe obstructive sleep apnea (OSA) based on early-night data.
methodsConsecutive patients referred for full-night polysomnography (PSG) were included. Clinical data (gender, age, blood pressure, Body Mass Index (BMI), snoring, apnea, neck circumference, ESS) and first 2-hour physiological parameters (sleep amounts, efficiency, respiratory event indices, oxygen saturation) were collected. Multivariate regression analyses were used to predict severe OSA (AHI > 30 events/hr). For external validation, 40 cases suspected of OSA were selected from another sleep center.
resultsIn a study of 348 patients, 41% were found to have severe OSA. BMI was the most accurate clinical predictor, with an accuracy of 0.69. The initial 2-hour AHI proved to be the best physiological predictor, achieving an accuracy of 0.79. A multivariate model that combined AHI, mean oxygen saturation, and the hypopnea index showed an accuracy of 0.82 for both internal and external samples.
conclusionsA combined model using various PSG features can accurately identify patients who need split-night PSG. This method could enhance efficiency and lower costs in settings with limited resources.
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