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Development and Validation of a Nomogram-Based Prognostic Model to Predict High Blood Pressure in Children and Adolescents—Findings From 342,736 Individuals in China

OBJECTIVES: Predicting the potential risk factors of high blood pressure (HBP) among children and adolescents is still a knowledge gap. Our study aimed to establish and validate a nomogram-based model for identifying youths at risk of developing HBP. METHODS: HBP was defined as systolic blood pressu...

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Autores principales: Liang, Jing-Hong, Zhao, Yu, Chen, Yi-Can, Huang, Shan, Zhang, Shu-Xin, Jiang, Nan, Kakaer, Aerziguli, Chen, Ya-Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9260112/
https://www.ncbi.nlm.nih.gov/pubmed/35811689
http://dx.doi.org/10.3389/fcvm.2022.884508
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author Liang, Jing-Hong
Zhao, Yu
Chen, Yi-Can
Huang, Shan
Zhang, Shu-Xin
Jiang, Nan
Kakaer, Aerziguli
Chen, Ya-Jun
author_facet Liang, Jing-Hong
Zhao, Yu
Chen, Yi-Can
Huang, Shan
Zhang, Shu-Xin
Jiang, Nan
Kakaer, Aerziguli
Chen, Ya-Jun
author_sort Liang, Jing-Hong
collection PubMed
description OBJECTIVES: Predicting the potential risk factors of high blood pressure (HBP) among children and adolescents is still a knowledge gap. Our study aimed to establish and validate a nomogram-based model for identifying youths at risk of developing HBP. METHODS: HBP was defined as systolic blood pressure or diastolic blood pressure above the 95th percentile, using age, gender, and height-specific cut-off points. Penalized regression with Lasso was used to identify the strongest predictors of HBP. Internal validation was conducted by a 5-fold cross-validation and bootstrapping approach. The predictive variables and the advanced nomogram plot were identified by conducting univariate and multivariate logistic regression analyses. A nomogram was constructed by a training group comprised of 239,546 (69.9%) participants and subsequently validated by an external group with 103,190 (30.1%) participants. RESULTS: Of 342,736 children and adolescents, 55,480 (16.2%) youths were identified with HBP with mean age 11.51 ± 1.45 years and 183,487 were boys (53.5%). Nine significant relevant predictors were identified including: age, gender, weight status, birth weight, breastfeeding, gestational hypertension, family history of obesity and hypertension, and physical activity. Acceptable discrimination [area under the receiver operating characteristic curve (AUC): 0.742 (development group), 0.740 (validation group)] and good calibration (Hosmer and Lemeshow statistics, P > 0.05) were observed in our models. An available web-based nomogram was built online on https://hbpnomogram.shinyapps.io/Dyn_Nomo_HBP/. CONCLUSIONS: This model composed of age, gender, early life factors, family history of the disease, and lifestyle factors may predict the risk of HBP among youths, which has developed a promising nomogram that may aid in more accurately identifying HBP among youths in primary care.
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spelling pubmed-92601122022-07-08 Development and Validation of a Nomogram-Based Prognostic Model to Predict High Blood Pressure in Children and Adolescents—Findings From 342,736 Individuals in China Liang, Jing-Hong Zhao, Yu Chen, Yi-Can Huang, Shan Zhang, Shu-Xin Jiang, Nan Kakaer, Aerziguli Chen, Ya-Jun Front Cardiovasc Med Cardiovascular Medicine OBJECTIVES: Predicting the potential risk factors of high blood pressure (HBP) among children and adolescents is still a knowledge gap. Our study aimed to establish and validate a nomogram-based model for identifying youths at risk of developing HBP. METHODS: HBP was defined as systolic blood pressure or diastolic blood pressure above the 95th percentile, using age, gender, and height-specific cut-off points. Penalized regression with Lasso was used to identify the strongest predictors of HBP. Internal validation was conducted by a 5-fold cross-validation and bootstrapping approach. The predictive variables and the advanced nomogram plot were identified by conducting univariate and multivariate logistic regression analyses. A nomogram was constructed by a training group comprised of 239,546 (69.9%) participants and subsequently validated by an external group with 103,190 (30.1%) participants. RESULTS: Of 342,736 children and adolescents, 55,480 (16.2%) youths were identified with HBP with mean age 11.51 ± 1.45 years and 183,487 were boys (53.5%). Nine significant relevant predictors were identified including: age, gender, weight status, birth weight, breastfeeding, gestational hypertension, family history of obesity and hypertension, and physical activity. Acceptable discrimination [area under the receiver operating characteristic curve (AUC): 0.742 (development group), 0.740 (validation group)] and good calibration (Hosmer and Lemeshow statistics, P > 0.05) were observed in our models. An available web-based nomogram was built online on https://hbpnomogram.shinyapps.io/Dyn_Nomo_HBP/. CONCLUSIONS: This model composed of age, gender, early life factors, family history of the disease, and lifestyle factors may predict the risk of HBP among youths, which has developed a promising nomogram that may aid in more accurately identifying HBP among youths in primary care. Frontiers Media S.A. 2022-06-23 /pmc/articles/PMC9260112/ /pubmed/35811689 http://dx.doi.org/10.3389/fcvm.2022.884508 Text en Copyright © 2022 Liang, Zhao, Chen, Huang, Zhang, Jiang, Kakaer and Chen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cardiovascular Medicine
Liang, Jing-Hong
Zhao, Yu
Chen, Yi-Can
Huang, Shan
Zhang, Shu-Xin
Jiang, Nan
Kakaer, Aerziguli
Chen, Ya-Jun
Development and Validation of a Nomogram-Based Prognostic Model to Predict High Blood Pressure in Children and Adolescents—Findings From 342,736 Individuals in China
title Development and Validation of a Nomogram-Based Prognostic Model to Predict High Blood Pressure in Children and Adolescents—Findings From 342,736 Individuals in China
title_full Development and Validation of a Nomogram-Based Prognostic Model to Predict High Blood Pressure in Children and Adolescents—Findings From 342,736 Individuals in China
title_fullStr Development and Validation of a Nomogram-Based Prognostic Model to Predict High Blood Pressure in Children and Adolescents—Findings From 342,736 Individuals in China
title_full_unstemmed Development and Validation of a Nomogram-Based Prognostic Model to Predict High Blood Pressure in Children and Adolescents—Findings From 342,736 Individuals in China
title_short Development and Validation of a Nomogram-Based Prognostic Model to Predict High Blood Pressure in Children and Adolescents—Findings From 342,736 Individuals in China
title_sort development and validation of a nomogram-based prognostic model to predict high blood pressure in children and adolescents—findings from 342,736 individuals in china
topic Cardiovascular Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9260112/
https://www.ncbi.nlm.nih.gov/pubmed/35811689
http://dx.doi.org/10.3389/fcvm.2022.884508
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