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Consumer sleep technology for the screening of obstructive sleep apnea and snoring: current status and a protocol for a systematic review and meta-analysis of diagnostic test accuracy
Journal article   Open access   Peer reviewed

Consumer sleep technology for the screening of obstructive sleep apnea and snoring: current status and a protocol for a systematic review and meta-analysis of diagnostic test accuracy

Gabriel Natan Pires, Erna Sif Arnardóttir, Anna Sigridur Islind, Timo Leppänen and Walter T. McNicholas
Journal of sleep research, Vol.32(4), pp.1-20
2023
Scopus ID: 2-s2.0-85148467552
Web of Science ID: WOS:000934608300001
PMID: 36807680

Abstract

Digital health Digital medicine Mobile applications Sleep trackers Smartwatches Wearables
There are concerns about the validation and accuracy of currently available con-sumer sleep technology for sleep-disordered breathing. The present report providesa background review of existing consumer sleep technologies and discloses themethods and procedures for a systematic review and meta-analysis of diagnostic testaccuracy of these devices and apps for the detection of obstructive sleep apnea andsnoring in comparison with polysomnography. The search will be performed in fourdatabases (PubMed, Scopus, Web of Science, and the Cochrane Library). Studies willbe selected in two steps, first by an analysis of abstracts followed by full-text analy-sis, and two independent reviewers will perform both phases. Primary outcomesinclude apnea–hypopnea index, respiratory disturbance index, respiratory eventindex, oxygen desaturation index, and snoring duration for both index and referencetests, as well as the number of true positives, false positives, true negatives, and falsenegatives for each threshold, as well as for epoch-by-epoch and event-by-eventresults, which will be considered for the calculation of surrogate measures (includingsensitivity, specificity, and accuracy). Diagnostic test accuracy meta-analyses will beperformed using the Chu and Cole bivariate binomial model. Mean difference meta-analysis will be performed for continuous outcomes using the DerSimonian and Lairdrandom-effects model. Analyses will be performed independently for each outcome.Subgroup and sensitivity analyses will evaluate the effects of the types (wearables,nearables, bed sensors, smartphone applications), technologies (e.g., oximeter, micro-phone, arterial tonometry, accelerometer), the role of manufacturers, and the repre-sentativeness of the samples.
url
https://doi.org/10.1111/jsr.13819View
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