A Prediction Nomogram Combining Epworth Sleepiness Scale and Other Clinical Parameters to Predict Obstructive Sleep Apnea in Patients with Hypertension

Background. Obstructive sleep apnea (OSA) is common in patients with hypertension. Nonetheless, OSA is underdiagnosed despite considerable evidence of the association between OSA and adverse health outcomes. This study developed and validated a clinical nomogram to predict OSA in patients with hyper...

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Main Authors: Lin Wang, Dongsheng Sun, Jianhong Xie, Li Zhang, Dibo Lao, Shaokun Xu
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:International Journal of Hypertension
Online Access:http://dx.doi.org/10.1155/2022/3861905
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author Lin Wang
Dongsheng Sun
Jianhong Xie
Li Zhang
Dibo Lao
Shaokun Xu
author_facet Lin Wang
Dongsheng Sun
Jianhong Xie
Li Zhang
Dibo Lao
Shaokun Xu
author_sort Lin Wang
collection DOAJ
description Background. Obstructive sleep apnea (OSA) is common in patients with hypertension. Nonetheless, OSA is underdiagnosed despite considerable evidence of the association between OSA and adverse health outcomes. This study developed and validated a clinical nomogram to predict OSA in patients with hypertension based on the Epworth Sleepiness Scale (ESS) score and OSA-related parameters. Methods. A total of 347 hypertensive patients with suspected OSA were retrospectively enrolled and randomly assigned to a training set and a validation set at 70 : 30 (N = 242/N = 105) ratio. OSA was diagnosed through sleep monitoring and was defined as an apnea-hypopnea index ≥5 events/h. Using the least absolute shrinkage and selection operator regression model, we identified potential predictors of OSA and constructed a nomogram model in the training set. The predictive performance of the nomogram was assessed and validated by discrimination and calibration. The nomogram was also compared with ESS scores according to decision curve analysis (DCA), integrated discrimination index (IDI), and net reclassification index (NRI). Results. ESS scores, body mass index, neck circumference, snoring, and observed apnea predicted OSA are considered. The nomogram showed similar discrimination between the training set (AUC: 0.799, 95% CI: 0.743–0.847) and validation set (AUC: 0.766, 95% CI: 0.673–0.843) and good calibration in the training (P=0.925>0.05) and validation (P=0.906>0.05) sets. Compared with the predictive value of the ESS, the nomogram was clinically useful and significantly improved reclassification accuracy (NRI: 0.552, 95% CI: 0.282–0.822, P<0.001; IDI: 0.088, 95% CI: 0.045–0.133, P<0.001) at a probability threshold of >42%. Conclusions. We developed a novel OSA prediction nomogram based on ESS scores and OSA-related parameters. This nomogram may help improve clinical decision-making, especially in communities and primary clinics, where polysomnography is unavailable.
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spelling doaj-art-054133bee520423e8aa62cf89fcefbbf2025-08-20T02:02:59ZengWileyInternational Journal of Hypertension2090-03922022-01-01202210.1155/2022/3861905A Prediction Nomogram Combining Epworth Sleepiness Scale and Other Clinical Parameters to Predict Obstructive Sleep Apnea in Patients with HypertensionLin Wang0Dongsheng Sun1Jianhong Xie2Li Zhang3Dibo Lao4Shaokun Xu5Geriatric Medicine CenterGeriatric Medicine CenterGeriatric Medicine CenterGeriatric Medicine CenterGeriatric Medicine CenterGeriatric Medicine CenterBackground. Obstructive sleep apnea (OSA) is common in patients with hypertension. Nonetheless, OSA is underdiagnosed despite considerable evidence of the association between OSA and adverse health outcomes. This study developed and validated a clinical nomogram to predict OSA in patients with hypertension based on the Epworth Sleepiness Scale (ESS) score and OSA-related parameters. Methods. A total of 347 hypertensive patients with suspected OSA were retrospectively enrolled and randomly assigned to a training set and a validation set at 70 : 30 (N = 242/N = 105) ratio. OSA was diagnosed through sleep monitoring and was defined as an apnea-hypopnea index ≥5 events/h. Using the least absolute shrinkage and selection operator regression model, we identified potential predictors of OSA and constructed a nomogram model in the training set. The predictive performance of the nomogram was assessed and validated by discrimination and calibration. The nomogram was also compared with ESS scores according to decision curve analysis (DCA), integrated discrimination index (IDI), and net reclassification index (NRI). Results. ESS scores, body mass index, neck circumference, snoring, and observed apnea predicted OSA are considered. The nomogram showed similar discrimination between the training set (AUC: 0.799, 95% CI: 0.743–0.847) and validation set (AUC: 0.766, 95% CI: 0.673–0.843) and good calibration in the training (P=0.925>0.05) and validation (P=0.906>0.05) sets. Compared with the predictive value of the ESS, the nomogram was clinically useful and significantly improved reclassification accuracy (NRI: 0.552, 95% CI: 0.282–0.822, P<0.001; IDI: 0.088, 95% CI: 0.045–0.133, P<0.001) at a probability threshold of >42%. Conclusions. We developed a novel OSA prediction nomogram based on ESS scores and OSA-related parameters. This nomogram may help improve clinical decision-making, especially in communities and primary clinics, where polysomnography is unavailable.http://dx.doi.org/10.1155/2022/3861905
spellingShingle Lin Wang
Dongsheng Sun
Jianhong Xie
Li Zhang
Dibo Lao
Shaokun Xu
A Prediction Nomogram Combining Epworth Sleepiness Scale and Other Clinical Parameters to Predict Obstructive Sleep Apnea in Patients with Hypertension
International Journal of Hypertension
title A Prediction Nomogram Combining Epworth Sleepiness Scale and Other Clinical Parameters to Predict Obstructive Sleep Apnea in Patients with Hypertension
title_full A Prediction Nomogram Combining Epworth Sleepiness Scale and Other Clinical Parameters to Predict Obstructive Sleep Apnea in Patients with Hypertension
title_fullStr A Prediction Nomogram Combining Epworth Sleepiness Scale and Other Clinical Parameters to Predict Obstructive Sleep Apnea in Patients with Hypertension
title_full_unstemmed A Prediction Nomogram Combining Epworth Sleepiness Scale and Other Clinical Parameters to Predict Obstructive Sleep Apnea in Patients with Hypertension
title_short A Prediction Nomogram Combining Epworth Sleepiness Scale and Other Clinical Parameters to Predict Obstructive Sleep Apnea in Patients with Hypertension
title_sort prediction nomogram combining epworth sleepiness scale and other clinical parameters to predict obstructive sleep apnea in patients with hypertension
url http://dx.doi.org/10.1155/2022/3861905
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