OSA-Onset: An algorithm for predicting the age of OSA onset

Study objectives: There is currently no way to estimate the period of time a person has had obstructive sleep apnoea (OSA). Such information would allow identification of people who have had an extended exposure period and are therefore at greater risk of other medical disorders; and enable consideration of disease chronicity in the study of OSA pathogenesis/treatment. Method: The 'age of OSA Onset' algorithm was developed in the Wisconsin Sleep Cohort (WSC), in participants who had >= 2 sleep studies and not using continuous positive airway pressure (n = 696). The algorithm was tested in a participant subset from the WSC (n = 154) and the Sleep Heart Health Study (SHHS; n = 705), those with an initial sleep study showing no significant OSA (apnea-hypopnea index (AHI) < 15 events/hr) and later sleep study showing moderate to severe OSA (AHI >= 15 events/hr). Results: Regression analyses were performed to identify variables that predicted change in AHI over time (BMI, sex, and AHI; beta weights and intercept used in the algorithm). In the WSC and SHHS subsamples, the observed years with OSA was 3.6 +/- 2.6 and 2.7 +/- 0.6 years, the algorithm estimated years with OSA was 10.6 +/- 8.2 and 9.0 +/- 6.2 years. Conclusions: The OSA-Onset algorithm estimated years of exposure to OSA with an accuracy of between 6.6 and 7.8 years (mean absolute error). Future studies are needed to determine whether the years of exposure derived from the OSA-Onset algorithm is related to worse prognosis, poorer cognitive outcomes, and/or poorer response to treatment. Crown Copyright (c) 2023 Published by Elsevier B.V. All rights reserved.