Nature and Science of Sleep (Mar 2023)
New Metrics from Polysomnography: Precision Medicine for OSA Interventions
Abstract
Junwei Guo, Yi Xiao Department of Respiratory and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of ChinaCorrespondence: Yi Xiao, Department of Respiratory and Critical Care Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, No. 1 Shuaifuyuan Street, Dongcheng District, Beijing, 100730, People’s Republic of China, Tel +86 010 69155037, Email [email protected]: Obstructive sleep apnea (OSA) is a highly preventable disease accompanied by multiple comorbid conditions. Despite the well-established cardiovascular and neurocognitive sequelae with OSA, the optimal metric for assessing the OSA severity and response to therapy remains controversial. Although overnight polysomnography (PSG) is the golden standard for OSA diagnosis, the abundant information is not fully exploited. With the development of deep learning and the era of big data, new metrics derived from PSG have been validated in some OSA consequences and personalized treatment. In this review, these metrics are introduced based on the pathophysiological mechanisms of OSA and new technologies. Emphasis is laid on the advantages and the prognostic value against apnea-hypopnea index. New classification criteria should be established based on these metrics and other clinical characters for precision medicine.Keywords: obstructive sleep apnea, precision medicine, polysomnography, metrics
