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

Author:

Pires Gabriel Natan12ORCID,Arnardóttir Erna Sif34ORCID,Islind Anna Sigridur35,Leppänen Timo678ORCID,McNicholas Walter T.9ORCID

Affiliation:

1. Departamento de Psicobiologia Universidade Federal de São Paulo São Paulo Brazil

2. European Sleep Research Society (ESRS) Regensburg Germany

3. Reykjavik University Sleep Institute Reykjavik University Reykjavik Iceland

4. Landspitali—The National University Hospital of Iceland Reykjavik Iceland

5. Department of Computer Science Reykjavik University Reykjavik Iceland

6. Department of Technical Physics University of Eastern Finland Kuopio Finland

7. Diagnostic Imaging Center Kuopio University Hospital Kuopio Finland

8. School of Information Technology and Electrical Engineering The University of Queensland Brisbane Australia

9. Department of Respiratory and Sleep Medicine St Vincent's Hospital Group, School of Medicine, University College Dublin Dublin Ireland

Abstract

SummaryThere are concerns about the validation and accuracy of currently available consumer sleep technology for sleep‐disordered breathing. The present report provides a background review of existing consumer sleep technologies and discloses the methods and procedures for a systematic review and meta‐analysis of diagnostic test accuracy of these devices and apps for the detection of obstructive sleep apnea and snoring in comparison with polysomnography. The search will be performed in four databases (PubMed, Scopus, Web of Science, and the Cochrane Library). Studies will be selected in two steps, first by an analysis of abstracts followed by full‐text analysis, and two independent reviewers will perform both phases. Primary outcomes include apnea–hypopnea index, respiratory disturbance index, respiratory event index, oxygen desaturation index, and snoring duration for both index and reference tests, as well as the number of true positives, false positives, true negatives, and false negatives for each threshold, as well as for epoch‐by‐epoch and event‐by‐event results, which will be considered for the calculation of surrogate measures (including sensitivity, specificity, and accuracy). Diagnostic test accuracy meta‐analyses will be performed using the Chu and Cole bivariate binomial model. Mean difference meta‐analysis will be performed for continuous outcomes using the DerSimonian and Laird random‐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, microphone, arterial tonometry, accelerometer), the role of manufacturers, and the representativeness of the samples.

Funder

Academy of Finland

NordForsk

Publisher

Wiley

Subject

Behavioral Neuroscience,Cognitive Neuroscience,General Medicine

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