Predictors of obstructive sleep apnea misclassification when using total bed time versus total sleep time

Abstract 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...

Full description

Bibliographic Details
Main Authors: Wei Yang Lim, Kay Choong See
Format: Article
Language:English
Published: Nature Publishing Group 2021-06-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-90818-y
id doaj-4d3127cce71a4157bd5d226a812c5260
record_format Article
spelling doaj-4d3127cce71a4157bd5d226a812c52602021-06-06T11:35:00ZengNature Publishing GroupScientific Reports2045-23222021-06-011111710.1038/s41598-021-90818-yPredictors of obstructive sleep apnea misclassification when using total bed time versus total sleep timeWei Yang Lim0Kay Choong See1Division of Respiratory & Critical Care Medicine, Department of Medicine, National University HospitalDivision of Respiratory & Critical Care Medicine, Department of Medicine, National University HospitalAbstract 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/m2. 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/m2.https://doi.org/10.1038/s41598-021-90818-y
collection DOAJ
language English
format Article
sources DOAJ
author Wei Yang Lim
Kay Choong See
spellingShingle Wei Yang Lim
Kay Choong See
Predictors of obstructive sleep apnea misclassification when using total bed time versus total sleep time
Scientific Reports
author_facet Wei Yang Lim
Kay Choong See
author_sort Wei Yang Lim
title 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_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_sort predictors of obstructive sleep apnea misclassification when using total bed time versus total sleep time
publisher Nature Publishing Group
series Scientific Reports
issn 2045-2322
publishDate 2021-06-01
description Abstract 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/m2. 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/m2.
url https://doi.org/10.1038/s41598-021-90818-y
work_keys_str_mv AT weiyanglim predictorsofobstructivesleepapneamisclassificationwhenusingtotalbedtimeversustotalsleeptime
AT kaychoongsee predictorsofobstructivesleepapneamisclassificationwhenusingtotalbedtimeversustotalsleeptime
_version_ 1721393832983003136