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Alternative algorithms and devices in sleep apnoea diagnosis: what we know and what we expect
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 on...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7575020/ https://www.ncbi.nlm.nih.gov/pubmed/32941350 http://dx.doi.org/10.1097/MCP.0000000000000726 |
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author | Penzel, Thomas Fietze, Ingo Glos, Martin |
author_facet | Penzel, Thomas Fietze, Ingo Glos, Martin |
author_sort | Penzel, Thomas |
collection | PubMed |
description | 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. RECENT FINDINGS: 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. SUMMARY: 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: . |
format | Online Article Text |
id | pubmed-7575020 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-75750202020-10-29 Alternative algorithms and devices in sleep apnoea diagnosis: what we know and what we expect Penzel, Thomas Fietze, Ingo Glos, Martin Curr Opin Pulm Med SLEEP AND RESPIRATORY NEUROBIOLOGY: Edited by Lee Brown and Winfried Johannes Randerath 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. RECENT FINDINGS: 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. SUMMARY: 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: . Lippincott Williams & Wilkins 2020-11 2020-09-15 /pmc/articles/PMC7575020/ /pubmed/32941350 http://dx.doi.org/10.1097/MCP.0000000000000726 Text en Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc-nd/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0 |
spellingShingle | SLEEP AND RESPIRATORY NEUROBIOLOGY: Edited by Lee Brown and Winfried Johannes Randerath Penzel, Thomas Fietze, Ingo Glos, Martin Alternative algorithms and devices in sleep apnoea diagnosis: what we know and what we expect |
title | Alternative algorithms and devices in sleep apnoea diagnosis: what we know and what we expect |
title_full | Alternative algorithms and devices in sleep apnoea diagnosis: what we know and what we expect |
title_fullStr | Alternative algorithms and devices in sleep apnoea diagnosis: what we know and what we expect |
title_full_unstemmed | Alternative algorithms and devices in sleep apnoea diagnosis: what we know and what we expect |
title_short | Alternative algorithms and devices in sleep apnoea diagnosis: what we know and what we expect |
title_sort | alternative algorithms and devices in sleep apnoea diagnosis: what we know and what we expect |
topic | SLEEP AND RESPIRATORY NEUROBIOLOGY: Edited by Lee Brown and Winfried Johannes Randerath |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7575020/ https://www.ncbi.nlm.nih.gov/pubmed/32941350 http://dx.doi.org/10.1097/MCP.0000000000000726 |
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