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Predictors of obstructive sleep apnea misclassification when using total bed time versus total sleep time
Obstructive sleep apnea (OSA) is a highly prevalent condition worldwide. Untreated, it is associated with multiple medical complications as well as a reduced quality of life. Home sleep apnea tests are increasingly used for its diagnosis and evaluation of severity, but using total bed time rather th...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8169653/ https://www.ncbi.nlm.nih.gov/pubmed/34075091 http://dx.doi.org/10.1038/s41598-021-90818-y |
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author | Lim, Wei Yang See, Kay Choong |
author_facet | Lim, Wei Yang See, Kay Choong |
author_sort | Lim, Wei Yang |
collection | PubMed |
description | Obstructive sleep apnea (OSA) is a highly prevalent condition worldwide. Untreated, it is associated with multiple medical complications as well as a reduced quality of life. Home sleep apnea tests are increasingly used for its diagnosis and evaluation of severity, but using total bed time rather than total sleep time may underestimate OSA severity. We aim to uncover the extent and predictors of OSA misclassification when using total bed time. A retrospective observational study was conducted using data from the sleep laboratory of the National University Hospital, Singapore, a tertiary hospital with 1200 beds. Misclassification of OSA was defined as any OSA severity that was less severe using total bed time versus total sleep time. Logistic regression was used to identify predictors of OSA misclassification. A total of 1621 patients were studied (mean age 45.6 ± 15.9 years; 73.4% male). 300 (18.5%) patients were misclassified. Risk factors for OSA misclassification included age (OR 1.02, 95% CI 1.01–1.03, P = 0.001) and body-mass index (BMI) (OR 0.97, 95% CI 0.95–0.99, P = 0.015). Risk for misclassification was significant in patients aged ≥ 57 years old, with BMI < 32.3 kg/m(2). Using total bed time rather than total sleep time to quantify OSA severity was associated with a significant risk of misclassification, particularly in patients aged ≥ 57 years old, with BMI < 32.3 kg/m(2). |
format | Online Article Text |
id | pubmed-8169653 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-81696532021-06-02 Predictors of obstructive sleep apnea misclassification when using total bed time versus total sleep time Lim, Wei Yang See, Kay Choong Sci Rep Article Obstructive sleep apnea (OSA) is a highly prevalent condition worldwide. Untreated, it is associated with multiple medical complications as well as a reduced quality of life. Home sleep apnea tests are increasingly used for its diagnosis and evaluation of severity, but using total bed time rather than total sleep time may underestimate OSA severity. We aim to uncover the extent and predictors of OSA misclassification when using total bed time. A retrospective observational study was conducted using data from the sleep laboratory of the National University Hospital, Singapore, a tertiary hospital with 1200 beds. Misclassification of OSA was defined as any OSA severity that was less severe using total bed time versus total sleep time. Logistic regression was used to identify predictors of OSA misclassification. A total of 1621 patients were studied (mean age 45.6 ± 15.9 years; 73.4% male). 300 (18.5%) patients were misclassified. Risk factors for OSA misclassification included age (OR 1.02, 95% CI 1.01–1.03, P = 0.001) and body-mass index (BMI) (OR 0.97, 95% CI 0.95–0.99, P = 0.015). Risk for misclassification was significant in patients aged ≥ 57 years old, with BMI < 32.3 kg/m(2). Using total bed time rather than total sleep time to quantify OSA severity was associated with a significant risk of misclassification, particularly in patients aged ≥ 57 years old, with BMI < 32.3 kg/m(2). Nature Publishing Group UK 2021-06-01 /pmc/articles/PMC8169653/ /pubmed/34075091 http://dx.doi.org/10.1038/s41598-021-90818-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Lim, Wei Yang See, Kay Choong Predictors of obstructive sleep apnea misclassification when using total bed time versus total sleep time |
title | Predictors of obstructive sleep apnea misclassification when using total bed time versus total sleep time |
title_full | Predictors of obstructive sleep apnea misclassification when using total bed time versus total sleep time |
title_fullStr | Predictors of obstructive sleep apnea misclassification when using total bed time versus total sleep time |
title_full_unstemmed | Predictors of obstructive sleep apnea misclassification when using total bed time versus total sleep time |
title_short | Predictors of obstructive sleep apnea misclassification when using total bed time versus total sleep time |
title_sort | predictors of obstructive sleep apnea misclassification when using total bed time versus total sleep time |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8169653/ https://www.ncbi.nlm.nih.gov/pubmed/34075091 http://dx.doi.org/10.1038/s41598-021-90818-y |
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