Alternative algorithms and devices in sleep apnoea diagnosis: what we know and what we expect.


Journal

Current opinion in pulmonary medicine
ISSN: 1531-6971
Titre abrégé: Curr Opin Pulm Med
Pays: United States
ID NLM: 9503765

Informations de publication

Date de publication:
11 2020
Historique:
pubmed: 18 9 2020
medline: 5 5 2021
entrez: 17 9 2020
Statut: ppublish

Résumé

Diagnosis of sleep apnoea was performed in sleep laboratories with polysomnography. This requires a room with supervision and presence of technologists and trained sleep experts. Today, clinical guidelines in most countries recommend home sleep apnoea testing with simple systems using six signals only. If criteria for signal quality, recording conditions, and patient selection are considered, then this is a reliable test with high accuracy. Recently diagnostic tools for sleep apnoea diagnosis become even more simple: smartwatches and wearables with smart apps claim to diagnose sleep apnoea when these devices are tracking sleep and sleep quality as part of new consumer health checking. Alternative and new devices range from excellent diagnostic tools with high accuracy and full validation studies down to very low-quality tools which only result in random diagnostic reports. Due to the high prevalence of sleep apnoea, even a random diagnosis may match a real disorder sometimes. Until now, there are no metrics established how to evaluate these alternative algorithms and simple devices. Proposals for evaluating smartwatches, smartphones, single-use sensors, and new algorithms are presented. New assessments may help to overcome current limitations in sleep apnoea severity metrics. VIDEO ABSTRACT: http://links.lww.com/COPM/A28.

Identifiants

pubmed: 32941350
doi: 10.1097/MCP.0000000000000726
pmc: PMC7575020
pii: 00063198-202011000-00008
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

650-656

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Auteurs

Thomas Penzel (T)

Interdisciplinary Sleep Medicine Center, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Saratov State University, Saratov, Russia.

Ingo Fietze (I)

Interdisciplinary Sleep Medicine Center, Charité - Universitätsmedizin Berlin, Berlin, Germany.

Martin Glos (M)

Interdisciplinary Sleep Medicine Center, Charité - Universitätsmedizin Berlin, Berlin, Germany.

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Classifications MeSH