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Weighted Epworth sleepiness scale predicted the apnea-hypopnea index better
BACKGROUND: The relationship between the Epworth sleepiness scale (ESS) and the apnea-hypopnea index (AHI) is uncertain and even poor. The major problem associated with the ESS might be a lack of consideration of weight in prediction in clinical practice. Would awarding different item-scores to the...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7291446/ https://www.ncbi.nlm.nih.gov/pubmed/32532260 http://dx.doi.org/10.1186/s12931-020-01417-w |
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author | Guo, Qi Song, Wei-dong Li, Wei Zeng, Chao Li, Yan-hong Mo, Jian-ming Lü, Zhong-dong Jiang, Mei |
author_facet | Guo, Qi Song, Wei-dong Li, Wei Zeng, Chao Li, Yan-hong Mo, Jian-ming Lü, Zhong-dong Jiang, Mei |
author_sort | Guo, Qi |
collection | PubMed |
description | BACKGROUND: The relationship between the Epworth sleepiness scale (ESS) and the apnea-hypopnea index (AHI) is uncertain and even poor. The major problem associated with the ESS might be a lack of consideration of weight in prediction in clinical practice. Would awarding different item-scores to the four scales of ESS items to develop a weighted ESS scoring system improve the accuracy of the AHI prediction? It is warranted to explore the intriguing hypotheses. METHODS: Seven hundred fifty-six adult patients with suspicion of obstructive sleep apnoea syndrome (OSAS) were prospectively recruited to a derivation cohort. This was tested against a prospective validation cohort of 810 adult patients with suspected OSAS. Each ESS item’s increased odds ratio for the corresponding AHI was calculated using univariate logistic regression. The receiver operating characteristic curves were created and the areas under the curves (AUCs) were calculated to illustrate and compare the accuracy of the indices. RESULTS: The higher the ESS item-score, the closer the relationship with the corresponding AHI. The odds ratios decreased as a result of the increased AHI. The ESS items were of unequal weight in predicting the corresponding AHI and a weighted ESS was developed. The coincidence rates with the corresponding AHI, body mass indices, and neck circumferences rose as the scores increased, whereas nocturnal nadir oxygen saturations decreased, and the weighted ESS was more strongly associated with these indices, compared with the ESS. The capability in predicting the patients without OSAS or with severe OSAS was strong, especially the latter, and the weighted ESS orchestrated manifest improvement in screening the patients with simple snoring. The patterns of sensitivities, specificities, and Youden’s indices of the four ranks of weighted ESS for predicting the corresponding AHI were better than those of the ESS, and the AUCs of weighted ESS were greater than the corresponding areas of ESS in the two cohorts. CONCLUSIONS: The weighted ESS orchestrated significant improvement in predicting the AHI, indicating that the capability in predicting the patients without OSAS or with severe OSAS was strong, which might have implications for clinical triage decisions to prioritize patients for polysomnography. |
format | Online Article Text |
id | pubmed-7291446 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-72914462020-06-12 Weighted Epworth sleepiness scale predicted the apnea-hypopnea index better Guo, Qi Song, Wei-dong Li, Wei Zeng, Chao Li, Yan-hong Mo, Jian-ming Lü, Zhong-dong Jiang, Mei Respir Res Research BACKGROUND: The relationship between the Epworth sleepiness scale (ESS) and the apnea-hypopnea index (AHI) is uncertain and even poor. The major problem associated with the ESS might be a lack of consideration of weight in prediction in clinical practice. Would awarding different item-scores to the four scales of ESS items to develop a weighted ESS scoring system improve the accuracy of the AHI prediction? It is warranted to explore the intriguing hypotheses. METHODS: Seven hundred fifty-six adult patients with suspicion of obstructive sleep apnoea syndrome (OSAS) were prospectively recruited to a derivation cohort. This was tested against a prospective validation cohort of 810 adult patients with suspected OSAS. Each ESS item’s increased odds ratio for the corresponding AHI was calculated using univariate logistic regression. The receiver operating characteristic curves were created and the areas under the curves (AUCs) were calculated to illustrate and compare the accuracy of the indices. RESULTS: The higher the ESS item-score, the closer the relationship with the corresponding AHI. The odds ratios decreased as a result of the increased AHI. The ESS items were of unequal weight in predicting the corresponding AHI and a weighted ESS was developed. The coincidence rates with the corresponding AHI, body mass indices, and neck circumferences rose as the scores increased, whereas nocturnal nadir oxygen saturations decreased, and the weighted ESS was more strongly associated with these indices, compared with the ESS. The capability in predicting the patients without OSAS or with severe OSAS was strong, especially the latter, and the weighted ESS orchestrated manifest improvement in screening the patients with simple snoring. The patterns of sensitivities, specificities, and Youden’s indices of the four ranks of weighted ESS for predicting the corresponding AHI were better than those of the ESS, and the AUCs of weighted ESS were greater than the corresponding areas of ESS in the two cohorts. CONCLUSIONS: The weighted ESS orchestrated significant improvement in predicting the AHI, indicating that the capability in predicting the patients without OSAS or with severe OSAS was strong, which might have implications for clinical triage decisions to prioritize patients for polysomnography. BioMed Central 2020-06-12 2020 /pmc/articles/PMC7291446/ /pubmed/32532260 http://dx.doi.org/10.1186/s12931-020-01417-w Text en © The Author(s) 2020 Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Guo, Qi Song, Wei-dong Li, Wei Zeng, Chao Li, Yan-hong Mo, Jian-ming Lü, Zhong-dong Jiang, Mei Weighted Epworth sleepiness scale predicted the apnea-hypopnea index better |
title | Weighted Epworth sleepiness scale predicted the apnea-hypopnea index better |
title_full | Weighted Epworth sleepiness scale predicted the apnea-hypopnea index better |
title_fullStr | Weighted Epworth sleepiness scale predicted the apnea-hypopnea index better |
title_full_unstemmed | Weighted Epworth sleepiness scale predicted the apnea-hypopnea index better |
title_short | Weighted Epworth sleepiness scale predicted the apnea-hypopnea index better |
title_sort | weighted epworth sleepiness scale predicted the apnea-hypopnea index better |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7291446/ https://www.ncbi.nlm.nih.gov/pubmed/32532260 http://dx.doi.org/10.1186/s12931-020-01417-w |
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