Abstract
STUDY OBJECTIVES: Oral appliance (OA) therapy usage can be objectively measured through temperature-sensing data chips embedded in the appliance. Initial reports of group data for short-term treatment usage suggest good nightly hours of usage. However, individual variability in treatment usage patterns has not been assessed. We aimed to identify OA treatment usage subtypes in the first 60 days and the earliest predictors of these usage patterns. METHODS: OSA patients were recruited for a study of OA therapy with an embedded compliance chip (DentiTrac, Braebon, Canada). Fifty-eight participants with 60 days of downloadable treatment usage data (5-minute readings) were analyzed. A hierarchical cluster analysis was used to group participants with similar usage patterns. A random forest classification model was used to identify the minimum number of days to predict usage subtype. RESULTS: Three user groups were identified and named: "Consistent Users" (48.3%), "Inconsistent Users," (32.8%) and "Non-Users" (19.0%). The first 20 days provided optimal data to predict the treatment usage group a patient would belong to at 60 days (90% accuracy). The strongest predictors of user group were downloaded usage data, average wear time, and number of days missed. CONCLUSIONS: Granular analysis of OA usage data suggests the existence of treatment user subtypes (Consistent, Inconsistent, and Non-Users). Our data suggest that 60-day usage patterns can be identified in the first 20 days of treatment using downloaded treatment usage data. Understanding initial treatment usage patterns provide an opportunity for early intervention to improve long-term usage and outcomes. CITATION: Sutherland K, Almeida FR, Kim T, et al. Treatment usage patterns of oral appliances for obstructive sleep apnea over the first 60 days: a cluster analysis. J Clin Sleep Med. 2021;17(9):1785-1792.