Comparison of the effect of weight change, simulated computational continuous positive airway pressure treatment and positional therapy on severity of sleep apnea. (18th June 2020)

• Record Type: Journal Article
• Authors: Kulkas, Antti; Duce, Brett; Töyräs, Juha; Seppä, Juha; Leppänen, Timo
• Is Part Of: Journal of sleep research. Volume 30:Number 2(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-06-18
• Subjects: AHI -- CPAP treatment -- obstructive sleep apnea -- positional therapy -- simulation -- weight loss; Sleep -- Periodicals; Sleep disorders -- Periodicals; 612.821
• DOI: 10.1111/jsr.13070
• Languages: English
• ISSNs: 0962-1105

Abstract

Abstract: Weight loss, continuous positive airway pressure (CPAP) and positional therapy (PT) are important treatments in obstructive sleep apnea (OSA). Although all of these reduce the apnea–hypopnea index (AHI) effectively, the benefits of these treatments have not been thoroughly investigated in a patient‐specific manner. Therefore, clinicians do not have objective means to choose an optimal treatment for each patient. We aim to provide clinicians the possibility for treatment optimization in a patient‐specific manner by introducing a computational simulation approach. The effect of actual weight change, computationally simulated CPAP treatment and PT and their combinations on the AHI were compared in 54 OSA patients divided into three equally sized groups (weight loss > 7%, weight loss 0%–7%, and weight gain) after a 5‐year follow‐up with lifestyle intervention. Weight loss reduced the AHI by 43.5% ( p < .05) and 18%, simulated CPAP treatment with 3.3‐hr adherence by 42.4% ( p < .05) and 35.5% ( p < .05), and simulated PT by 13.5% ( p < .05) and 30.7% ( p < .05) in > 7% and 0%–7% weight loss groups, respectively. Simulated CPAP treatment and PT were able to compensate for the increase in the AHI caused by weight gain. A developed simulation approach could help clinicians to estimate treatment success in advance in order to prescribe the most optimal patient‐specific treatment to reduce OSA‐related health risks.