Contexte
This study was conducted by JL. Pépin, C. Letesson, NN. Le-Dong, A. Dedave, S. Denison, V. Cuthbert, JB. Martinot and D. Gozal.
Given the high prevalence of obstructive sleep apnea (OSA), there is a consensus among experts on the need for simpler and automated diagnostic approaches.
In this extend, the goal is to demonstrate in what way mandibular mouvements measure associated with machine learning anlysis is appropriate for the OSA diagnosis. Sunrise ORDI will be compared to the gold standard PSG ORDI. ORDI stands for Obstructive Respiratory Difficulties Index.
Study Design
The monocentric prospective study was conducted on a group of 376 adults with suspected OSA, in the Centre hospitalier Universitaire de Louvain sleep laboratory (Sainte-Elisabeth site, Namur, Belgium). The patients (55,1% males) were enrolled from July 5, 2017, to October 31, 2018.
Patients underwent overnight in-laboratory sleep test with both polysomnography (PSG) and Sunrise equipments. The PSG was used as the reference method and blindly scored by two independant experts. Then the results were compared with simultaneous MM recordings analysis using the Sunrise system.
Results
The study concludes that the Sunrise system provides an accurate estimation of ORDI obtained during standard PSG in a large cohort of patients with and without OSA. This clinical validation was a real milestone for Sunrise to show the extreme equivalence between the two diagnostic methods, by publishing these results in a peer-reviewed journal.
A few words about the Journal
JAMA Network Open is an international, peer-reviewed, open access, general medical journal published by the American Medical Association. Each article has been peer reviewed and published under an open access license for clinicians, investigators, and policy makers. JAMA Network Open is a member of the JAMA Network, a consortium of peer-reviewed, general medical and specialty publications.
Access to the complete publication right here.
