0689 Use Of An Automated Scanning System To Select A Patient Interface

Abstract Introduction There is no universal process for selecting mask style, size, and fit, and there is considerable variance in clinician and patient mask preference and patient anatomy. Poor mask fit may negatively affect adherence. A three-dimensional (3D) facial scanner and proprietary analytical software were developed to bring efficiencies to mask selection. This study explored the impact of that system on initial mask success compared to standard practice. Methods This was an open-label, randomized-controlled study. Participants provided written informed consent. 3D Scanner Arm (3DA): Participants answered questions about sleeping habits then had 3D facial images taken. Proprietary software recommended a hierarchy of up to four Philips Respironics masks and sizes. Traditional Fitting Arm (TFA): A designated clinician selected and fit masks using their standard methods. Mask selection was assessed by applying therapy and soliciting patient and clinician feedback. Mask refits and adherence were tracked through 90 days. Five sleep centers recruited 115 participants into the 3DA (61 males, 51.1±13.4 years, BMI 35.2±7.0, diagnostic AHI 26.2±21.9) and 123 into the TFA (79 males, 51.1±11.9 years, BMI 35±7.9, diagnostic AHI 26.9±22.6). Results A significantly higher percentage of 3DA patients required only one mask fitting (with no refits) compared to TFA during the initial setup (89.6% vs. 54.5%, p