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The predictive value of resting heart rate in identifying undiagnosed diabetes in Korean adults: Korea National Health and Nutrition Examination Survey

OBJECTIVES: The purpose of this study was (1) to examine whether the addition of resting heart rate (RHR) to the existing undiagnosed diabetes mellitus (UnDM) prediction model would improve predictability, and (2) to develop and validate UnDM prediction models by using only easily assessable variabl...

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Autores principales: Park, Dong-Hyuk, Cho, Wonhee, Lee, Yong-Ho, Jee, Sun Ha, Jeon, Justin Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Epidemiology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9117096/
https://www.ncbi.nlm.nih.gov/pubmed/34990528
http://dx.doi.org/10.4178/epih.e2022009
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author Park, Dong-Hyuk
Cho, Wonhee
Lee, Yong-Ho
Jee, Sun Ha
Jeon, Justin Y.
author_facet Park, Dong-Hyuk
Cho, Wonhee
Lee, Yong-Ho
Jee, Sun Ha
Jeon, Justin Y.
author_sort Park, Dong-Hyuk
collection PubMed
description OBJECTIVES: The purpose of this study was (1) to examine whether the addition of resting heart rate (RHR) to the existing undiagnosed diabetes mellitus (UnDM) prediction model would improve predictability, and (2) to develop and validate UnDM prediction models by using only easily assessable variables such as gender, RHR, age, and waist circumference (WC). METHODS: Korea National Health and Nutrition Examination Survey (KNHANES) 2010, 2012, 2014, 2016 data were used to develop the model (model building set, n=19,675), while the data from 2011, 2013, 2015, 2017 were used to validate the model (validation set, n=19,917). UnDM was defined as a fasting glucose level ≥126 mg/dL or glycated hemoglobin ≥6.5%; however, doctors have not diagnosed it. Statistical package for the social sciences logistic regression analysis was used to determine the predictors of UnDM. RESULTS: RHR, age, and WC were associated with UnDM. When RHR was added to the existing model, sensitivity was reduced (86 vs. 73%), specificity was increased (49 vs. 65%), and a higher Youden index (35 vs. 38) was expressed. When only gender, RHR, age, and WC were used in the model, a sensitivity, specificity, and Youden index of 70%, 67%, and 37, respectively, were observed. CONCLUSIONS: Adding RHR to the existing UnDM prediction model improved specificity and the Youden index. Furthermore, when the prediction model only used gender, RHR, age, and WC, the outcomes were not inferior to those of the existing prediction model.
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spelling pubmed-91170962022-05-25 The predictive value of resting heart rate in identifying undiagnosed diabetes in Korean adults: Korea National Health and Nutrition Examination Survey Park, Dong-Hyuk Cho, Wonhee Lee, Yong-Ho Jee, Sun Ha Jeon, Justin Y. Epidemiol Health Original Article OBJECTIVES: The purpose of this study was (1) to examine whether the addition of resting heart rate (RHR) to the existing undiagnosed diabetes mellitus (UnDM) prediction model would improve predictability, and (2) to develop and validate UnDM prediction models by using only easily assessable variables such as gender, RHR, age, and waist circumference (WC). METHODS: Korea National Health and Nutrition Examination Survey (KNHANES) 2010, 2012, 2014, 2016 data were used to develop the model (model building set, n=19,675), while the data from 2011, 2013, 2015, 2017 were used to validate the model (validation set, n=19,917). UnDM was defined as a fasting glucose level ≥126 mg/dL or glycated hemoglobin ≥6.5%; however, doctors have not diagnosed it. Statistical package for the social sciences logistic regression analysis was used to determine the predictors of UnDM. RESULTS: RHR, age, and WC were associated with UnDM. When RHR was added to the existing model, sensitivity was reduced (86 vs. 73%), specificity was increased (49 vs. 65%), and a higher Youden index (35 vs. 38) was expressed. When only gender, RHR, age, and WC were used in the model, a sensitivity, specificity, and Youden index of 70%, 67%, and 37, respectively, were observed. CONCLUSIONS: Adding RHR to the existing UnDM prediction model improved specificity and the Youden index. Furthermore, when the prediction model only used gender, RHR, age, and WC, the outcomes were not inferior to those of the existing prediction model. Korean Society of Epidemiology 2022-01-03 /pmc/articles/PMC9117096/ /pubmed/34990528 http://dx.doi.org/10.4178/epih.e2022009 Text en ©2022, Korean Society of Epidemiology https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Park, Dong-Hyuk
Cho, Wonhee
Lee, Yong-Ho
Jee, Sun Ha
Jeon, Justin Y.
The predictive value of resting heart rate in identifying undiagnosed diabetes in Korean adults: Korea National Health and Nutrition Examination Survey
title The predictive value of resting heart rate in identifying undiagnosed diabetes in Korean adults: Korea National Health and Nutrition Examination Survey
title_full The predictive value of resting heart rate in identifying undiagnosed diabetes in Korean adults: Korea National Health and Nutrition Examination Survey
title_fullStr The predictive value of resting heart rate in identifying undiagnosed diabetes in Korean adults: Korea National Health and Nutrition Examination Survey
title_full_unstemmed The predictive value of resting heart rate in identifying undiagnosed diabetes in Korean adults: Korea National Health and Nutrition Examination Survey
title_short The predictive value of resting heart rate in identifying undiagnosed diabetes in Korean adults: Korea National Health and Nutrition Examination Survey
title_sort predictive value of resting heart rate in identifying undiagnosed diabetes in korean adults: korea national health and nutrition examination survey
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9117096/
https://www.ncbi.nlm.nih.gov/pubmed/34990528
http://dx.doi.org/10.4178/epih.e2022009
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