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Predictors of Excessive Daytime Sleepiness in Medical Students: A Meta-Regression

Excessive daytime sleepiness (EDS) is highly prevalent among medical students and can have serious negative outcomes for both students and their patients. Little is known about the magnitude and predictors of EDS among medical college students. A meta-regression analysis was conducted to achieve the...

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Autores principales: Jahrami, Haitham, Alshomili, Hajar, Almannai, Noora, Althani, Noora, Aloffi, Adel, Algahtani, Haifa, Brown, Cary A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7445829/
https://www.ncbi.nlm.nih.gov/pubmed/33089164
http://dx.doi.org/10.3390/clockssleep1020018
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author Jahrami, Haitham
Alshomili, Hajar
Almannai, Noora
Althani, Noora
Aloffi, Adel
Algahtani, Haifa
Brown, Cary A.
author_facet Jahrami, Haitham
Alshomili, Hajar
Almannai, Noora
Althani, Noora
Aloffi, Adel
Algahtani, Haifa
Brown, Cary A.
author_sort Jahrami, Haitham
collection PubMed
description Excessive daytime sleepiness (EDS) is highly prevalent among medical students and can have serious negative outcomes for both students and their patients. Little is known about the magnitude and predictors of EDS among medical college students. A meta-regression analysis was conducted to achieve these two targets. A systematic search was performed for English-language studies that reported the prevalence of EDS among medical students using the Epworth sleepiness scale (ESS), age, sex, sleep duration and sleep quality as predictive variables. A total of nine observational studies (K = 9, N = 2587) were included in the analyses. Meta-regression analyses were performed using mean age (years), sex (proportion of male subjects), sleep duration (hours/night) and sleep quality index score (continuous scale) as moderators for EDS—with the prevalence of EDS as an outcome variable. An interaction term of sleep duration X sleep quality was created to assess if these two variables simultaneously influenced the outcome variable. Utilizing the ESS, the pooled prevalence of EDS among medical students was 34.6% (95% Confidence Interval (CI) 18.3–50.9%). Meta-regression models of age, sex, sleep duration and sleep quality alone revealed poor predictive capabilities. Meta-regression models of sleep duration–sleep quality interaction revealed results with high statistical significance. The findings from this review contribute supporting evidence for the relationship between sleep duration and sleep quality scores (i.e., sleep duration X sleep quality score) in predicting EDS in medical students.
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spelling pubmed-74458292020-10-20 Predictors of Excessive Daytime Sleepiness in Medical Students: A Meta-Regression Jahrami, Haitham Alshomili, Hajar Almannai, Noora Althani, Noora Aloffi, Adel Algahtani, Haifa Brown, Cary A. Clocks Sleep Review Excessive daytime sleepiness (EDS) is highly prevalent among medical students and can have serious negative outcomes for both students and their patients. Little is known about the magnitude and predictors of EDS among medical college students. A meta-regression analysis was conducted to achieve these two targets. A systematic search was performed for English-language studies that reported the prevalence of EDS among medical students using the Epworth sleepiness scale (ESS), age, sex, sleep duration and sleep quality as predictive variables. A total of nine observational studies (K = 9, N = 2587) were included in the analyses. Meta-regression analyses were performed using mean age (years), sex (proportion of male subjects), sleep duration (hours/night) and sleep quality index score (continuous scale) as moderators for EDS—with the prevalence of EDS as an outcome variable. An interaction term of sleep duration X sleep quality was created to assess if these two variables simultaneously influenced the outcome variable. Utilizing the ESS, the pooled prevalence of EDS among medical students was 34.6% (95% Confidence Interval (CI) 18.3–50.9%). Meta-regression models of age, sex, sleep duration and sleep quality alone revealed poor predictive capabilities. Meta-regression models of sleep duration–sleep quality interaction revealed results with high statistical significance. The findings from this review contribute supporting evidence for the relationship between sleep duration and sleep quality scores (i.e., sleep duration X sleep quality score) in predicting EDS in medical students. MDPI 2019-04-11 /pmc/articles/PMC7445829/ /pubmed/33089164 http://dx.doi.org/10.3390/clockssleep1020018 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Jahrami, Haitham
Alshomili, Hajar
Almannai, Noora
Althani, Noora
Aloffi, Adel
Algahtani, Haifa
Brown, Cary A.
Predictors of Excessive Daytime Sleepiness in Medical Students: A Meta-Regression
title Predictors of Excessive Daytime Sleepiness in Medical Students: A Meta-Regression
title_full Predictors of Excessive Daytime Sleepiness in Medical Students: A Meta-Regression
title_fullStr Predictors of Excessive Daytime Sleepiness in Medical Students: A Meta-Regression
title_full_unstemmed Predictors of Excessive Daytime Sleepiness in Medical Students: A Meta-Regression
title_short Predictors of Excessive Daytime Sleepiness in Medical Students: A Meta-Regression
title_sort predictors of excessive daytime sleepiness in medical students: a meta-regression
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7445829/
https://www.ncbi.nlm.nih.gov/pubmed/33089164
http://dx.doi.org/10.3390/clockssleep1020018
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