Predictive Accuracy of MATRx Plus in Identifying Favorable Candidates for Oral Appliance Therapy

Obstructive sleep apnea (OSA) is a common disease that is largely un-diagnosed and untreated. Standard treatment for obstructive sleep apnea, nasal continuous positive airway pressure (CPAP), entails use of a nose mask to deliver positive pressure which dilates the pharynx and eliminates obstruction. This therapy is highly efficacious and benign but is associated with low adherence, particularly in non-sleepy apneics with disease of mild and moderate severity. The principal alternative to CPAP therapy is oral appliance (OA) therapy in which a custom made mandibular advancement splint (MAS) is used to protrude the mandible during sleep, thereby opening the pharyngeal airway. OA therapy, while preferred and well accepted by most participants, is not uniformly efficacious. Additionally, uncertainty regarding the patient's response to OAT and the effective target mandibular position can lead to a significant time span between diagnosis and initiation of effective treatment. Furthermore, knowledge of the effective target mandibular position supports the use of new OA design and manufacturing processes that can further reduce the time and cost in delivering the therapy. Zephyr Sleep Technologies (the Sponsor) has developed a method of identifying OAT responsive participants and their efficacious mandibular protrusion. Recently, Zephyr Sleep Technologies developed a portable device that avoids this requirement and can be used in a multi-night test in the home. Using a feedback controlled mandibular positioner (FCMP), the device measures and analyzes respiratory airflow and oxygen saturation and makes decisions in real-time about moving the mandible. The FCMP device was tested in a blinded, bi-phase clinical study in which participants with mild-to-severe sleep apnea (n=202) underwent two full-night studies in the home. Data from phase 1 were used to develop a predictive method, and data from phase 2 were used to prospectively test the accuracy of the predictive method. An