P085 OSA-Onset: An algorithm for predicting the age of OSA onset

Abstract

Abstract Objectives There is currently no way to estimate the period of time a person has had obstructive sleep apnoea (OSA). Such information is important in both clinical and research settings as it would allow identification of people who have experienced OSA for an extended period. People who are therefore, at greater risk of a range of other medical disorders; and enable consideration of the length of disease in the study of OSA pathogenesis or treatments. Method The ‘age of OSA Onset’ algorithm’ (OSA-Onset) was developed in participants of the Wisconsin Sleep Cohort (WSC) who had ≥2 sleep studies and were not using continuous positive airway pressure (n=696). The algorithm was tested in subsets of participants from the WSC (n=154) and the Sleep Heart Health Study (SHHS; n=705) who had an initial sleep study showing no OSA (apnea-hypopnea index (AHI) <15 events/hr) and a later sleep study showing presence of OSA (AHI≥15 events/hr). Results Regression analyses were performed to identify variables that significantly predicted change in AHI over time (BMI, sex, and AHI) and beta weights and intercept used in the subsequent algorithm. In the WSC and SHHS subsamples, OSA-onset was able to estimate disease onset with a mean absolute error of 7.8 and 5.5 years, respectively. Conclusions 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 therapy.