STUDY OBJECTIVES: Mandibular protruding oral appliances represent a potentially important therapy for obstructive sleep apnea (OSA). However, their clinical utility is limited by a less-than-ideal efficacy rate and uncertainty regarding an efficacious mandibular position, pointing to the need for a tool to assist in delivery of the therapy. The current study assesses the ability to prospectively identify therapeutic responders and determine an efficacious mandibular position. METHODS: Individuals (n = 202) with OSA participated in a blinded, 2-part investigation. A system for identifying therapeutic responders was developed in part 1 (n = 149); the predictive accuracy of this system was prospectively evaluated on a new population in part 2 (n = 53). Each participant underwent a 2-night, in-home feedback-controlled mandibular positioner (FCMP) test, followed by treatment with a custom oral appliance and an outcome study with the oral appliance in place. A machine learning classification system was trained to predict therapeutic outcome on data obtained from FCMP studies on part 1 participants. The accuracy of this trained system was then evaluated on part 2 participants by examining the agreement between prospectively predicted outcome and observed outcome. A predicted efficacious mandibular position was derived from each FCMP study. RESULTS: Predictive accuracy was as follows: sensitivity 85%; specificity 93%; positive predictive value 97%; and negative predictive value 72%. Of participants correctly predicted to respond to therapy, the predicted mandibular protrusive position proved efficacious in 86% of cases. CONCLUSIONS: An unattended, in-home FCMP test prospectively identifies individuals with OSA who will respond to oral appliance therapy and provides an efficacious mandibular position. CLINICAL TRIAL REGISTRATION: The trial that this study reports on is registered on www.clinicaltrials.gov, ID NCT03011762, study name: Feasibility and Predictive Accuracy of an In-Home Computer Controlled Mandibular Positioner in Identifying Favourable Candidates for Oral Appliance Therapy.
STUDY OBJECTIVES: Mandibular protruding oral appliances represent a potentially important therapy for obstructive sleep apnea (OSA). However, their clinical utility is limited by a less-than-ideal efficacy rate and uncertainty regarding an efficacious mandibular position, pointing to the need for a tool to assist in delivery of the therapy. The current study assesses the ability to prospectively identify therapeutic responders and determine an efficacious mandibular position. METHODS: Individuals (n = 202) with OSA participated in a blinded, 2-part investigation. A system for identifying therapeutic responders was developed in part 1 (n = 149); the predictive accuracy of this system was prospectively evaluated on a new population in part 2 (n = 53). Each participant underwent a 2-night, in-home feedback-controlled mandibular positioner (FCMP) test, followed by treatment with a custom oral appliance and an outcome study with the oral appliance in place. A machine learning classification system was trained to predict therapeutic outcome on data obtained from FCMP studies on part 1 participants. The accuracy of this trained system was then evaluated on part 2 participants by examining the agreement between prospectively predicted outcome and observed outcome. A predicted efficacious mandibular position was derived from each FCMP study. RESULTS: Predictive accuracy was as follows: sensitivity 85%; specificity 93%; positive predictive value 97%; and negative predictive value 72%. Of participants correctly predicted to respond to therapy, the predicted mandibular protrusive position proved efficacious in 86% of cases. CONCLUSIONS: An unattended, in-home FCMP test prospectively identifies individuals with OSA who will respond to oral appliance therapy and provides an efficacious mandibular position. CLINICAL TRIAL REGISTRATION: The trial that this study reports on is registered on www.clinicaltrials.gov, ID NCT03011762, study name: Feasibility and Predictive Accuracy of an In-Home Computer Controlled Mandibular Positioner in Identifying Favourable Candidates for Oral Appliance Therapy.
Authors: Ching Li Chai-Coetzer; Nick A Antic; L Sharn Rowland; Peter G Catcheside; Adrian Esterman; Richard L Reed; Helena Williams; Sandra Dunn; R Doug McEvoy Journal: Thorax Date: 2011-01-20 Impact factor: 9.139
Authors: F Gagnadoux; B Fleury; B Vielle; B Pételle; N Meslier; X L N'Guyen; W Trzepizur; J L Racineux Journal: Eur Respir J Date: 2009-03-26 Impact factor: 16.671
Authors: Chloé Kastoer; Marijke Dieltjens; Sara Op de Beeck; Marc J Braem; Paul H Van de Heyning; Olivier M Vanderveken Journal: J Clin Sleep Med Date: 2018-08-15 Impact factor: 4.062
Authors: Erin V Mosca; Sabina Bruehlmann; Shaelynn M Zouboules; Alexandra E Chiew; Curtis Westersund; Dillon A Hambrook; Seyed A Zareian Jahromi; Joshua Grosse; Zbigniew L Topor; Shouresh Charkhandeh; John E Remmers Journal: J Clin Sleep Med Date: 2022-03-01 Impact factor: 4.062
Authors: Pien Fenneke Nicole Bosschieter; Julia A M Uniken Venema; Patty E Vonk; Madeline J L Ravesloot; Joost W Vanhommerig; A Hoekema; Joanneke M Plooij; F Lobbezoo; Nico de Vries Journal: Sleep Breath Date: 2022-08-09 Impact factor: 2.655