E. Finnsson, Eydís Arnardóttir, Wan-Ju Cheng, Raichel M. Alex, Þ. Sigmarsdóttir, Snorri Helgason, L. Hang, J. Ágústsson, A. Wellman, S. Sands
{"title":"睡眠呼吸暂停内窥镜:从生理实验室到可扩展的多导睡眠图测量","authors":"E. Finnsson, Eydís Arnardóttir, Wan-Ju Cheng, Raichel M. Alex, Þ. Sigmarsdóttir, Snorri Helgason, L. Hang, J. Ágústsson, A. Wellman, S. Sands","doi":"10.3389/frsle.2023.1188052","DOIUrl":null,"url":null,"abstract":"Obstructive sleep apnea (OSA) is a common disorder characterized by recurrent upper airway obstruction during sleep. Despite the availability of continuous positive airway pressure (CPAP) as the gold standard treatment, it is not well tolerated by all patients. Accordingly, research has increasingly focused on developing methods for OSA endotyping, which aims to identify underlying pathophysiological mechanisms of the disorder to help guide treatment for CPAP-intolerant individuals. Four key endotypic traits have been identified, namely: collapsibility, upper airway muscle compensation, arousal threshold and loop gain. However, most methods for extracting these traits require specialized training and equipment not available in a standard sleep clinic, which has hampered the ability to assess the full impact of these traits on OSA outcomes. This paper aims to provide an overview of current methods for OSA endotyping, focusing on the Endo-Phenotyping Using Polysomnography (PUP) method and its cloud-based extension, PUPpy, which offer scalable and accessible ways to estimate endotypic traits from standard polysomnography. We discuss the potential for these methods to facilitate precision medicine for OSA patients and the challenges that need to be addressed for their translation into clinical practice.","PeriodicalId":73106,"journal":{"name":"Frontiers in sleep","volume":"81A 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Sleep apnea endotypes: from the physiological laboratory to scalable polysomnographic measures\",\"authors\":\"E. Finnsson, Eydís Arnardóttir, Wan-Ju Cheng, Raichel M. Alex, Þ. Sigmarsdóttir, Snorri Helgason, L. Hang, J. Ágústsson, A. Wellman, S. Sands\",\"doi\":\"10.3389/frsle.2023.1188052\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Obstructive sleep apnea (OSA) is a common disorder characterized by recurrent upper airway obstruction during sleep. Despite the availability of continuous positive airway pressure (CPAP) as the gold standard treatment, it is not well tolerated by all patients. Accordingly, research has increasingly focused on developing methods for OSA endotyping, which aims to identify underlying pathophysiological mechanisms of the disorder to help guide treatment for CPAP-intolerant individuals. Four key endotypic traits have been identified, namely: collapsibility, upper airway muscle compensation, arousal threshold and loop gain. However, most methods for extracting these traits require specialized training and equipment not available in a standard sleep clinic, which has hampered the ability to assess the full impact of these traits on OSA outcomes. This paper aims to provide an overview of current methods for OSA endotyping, focusing on the Endo-Phenotyping Using Polysomnography (PUP) method and its cloud-based extension, PUPpy, which offer scalable and accessible ways to estimate endotypic traits from standard polysomnography. We discuss the potential for these methods to facilitate precision medicine for OSA patients and the challenges that need to be addressed for their translation into clinical practice.\",\"PeriodicalId\":73106,\"journal\":{\"name\":\"Frontiers in sleep\",\"volume\":\"81A 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in sleep\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3389/frsle.2023.1188052\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in sleep","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/frsle.2023.1188052","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sleep apnea endotypes: from the physiological laboratory to scalable polysomnographic measures
Obstructive sleep apnea (OSA) is a common disorder characterized by recurrent upper airway obstruction during sleep. Despite the availability of continuous positive airway pressure (CPAP) as the gold standard treatment, it is not well tolerated by all patients. Accordingly, research has increasingly focused on developing methods for OSA endotyping, which aims to identify underlying pathophysiological mechanisms of the disorder to help guide treatment for CPAP-intolerant individuals. Four key endotypic traits have been identified, namely: collapsibility, upper airway muscle compensation, arousal threshold and loop gain. However, most methods for extracting these traits require specialized training and equipment not available in a standard sleep clinic, which has hampered the ability to assess the full impact of these traits on OSA outcomes. This paper aims to provide an overview of current methods for OSA endotyping, focusing on the Endo-Phenotyping Using Polysomnography (PUP) method and its cloud-based extension, PUPpy, which offer scalable and accessible ways to estimate endotypic traits from standard polysomnography. We discuss the potential for these methods to facilitate precision medicine for OSA patients and the challenges that need to be addressed for their translation into clinical practice.