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The Sleep Revolution project: the concept and objectives
Author(s) -
Arnardottir Erna S.,
Islind Anna Sigridur,
Óskarsdóttir María,
Ólafsdóttir Kristín A.,
August Elias,
Jónasdóttir Lára,
HrubosStrøm Harald,
Saavedra Jose M.,
Grote Ludger,
Hedner Jan,
Höskuldsson Sveinbjörn,
Ágústsson Jón Skírnir,
Jóhannsdóttir Kamilla Rún,
McNicholas Walter T.,
Pevernagie Dirk,
Sund Reijo,
Töyräs Juha,
Leppänen Timo
Publication year - 2022
Publication title -
journal of sleep research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.297
H-Index - 117
eISSN - 1365-2869
pISSN - 0962-1105
DOI - 10.1111/jsr.13630
Subject(s) - obstructive sleep apnea , medicine , sleep (system call) , sleep apnea , sleep medicine , hypopnea , intensive care medicine , physical therapy , apnea , polysomnography , sleep disorder , psychiatry , cognition , computer science , operating system
Summary Obstructive sleep apnea is linked to severe health consequences such as hypertension, daytime sleepiness, and cardiovascular disease. Nearly a billion people are estimated to have obstructive sleep apnea with a substantial economic burden. However, the current diagnostic parameter of obstructive sleep apnea, the apnea–hypopnea index, correlates poorly with related comorbidities and symptoms. Obstructive sleep apnea severity is measured by counting respiratory events, while other physiologically relevant consequences are ignored. Furthermore, as the clinical methods for analysing polysomnographic signals are outdated, laborious, and expensive, most patients with obstructive sleep apnea remain undiagnosed. Therefore, more personalised diagnostic approaches are urgently needed. The Sleep Revolution, funded by the European Union's Horizon 2020 Research and Innovation Programme, aims to tackle these shortcomings by developing machine learning tools to better estimate obstructive sleep apnea severity and phenotypes. This allows for improved personalised treatment options, including increased patient participation. Also, implementing these tools will alleviate the costs and increase the availability of sleep studies by decreasing manual scoring labour. Finally, the project aims to design a digital platform that functions as a bridge between researchers, patients, and clinicians, with an electronic sleep diary, objective cognitive tests, and questionnaires in a mobile application. These ambitious goals will be achieved through extensive collaboration between 39 centres, including expertise from sleep medicine, computer science, and industry and by utilising tens of thousands of retrospectively and prospectively collected sleep recordings. With the commitment of the European Sleep Research Society and Assembly of National Sleep Societies, the Sleep Revolution has the unique possibility to create new standardised guidelines for sleep medicine.