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A nomogram for predicting severe adenovirus pneumonia in children

Adenoviral pneumonia in children was an epidemic that greatly impacted children's health in China in 2019. Currently, no simple or systematic scale has been introduced for the early identification and diagnosis of adenoviral pneumonia. The early recognition scale of pediatric severe adenovirus...

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Autores principales: Zhang, Jiamin, Xu, Changdi, Yan, Shasha, Zhang, Xuefang, Zhao, Deyu, Liu, Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10014818/
https://www.ncbi.nlm.nih.gov/pubmed/36937948
http://dx.doi.org/10.3389/fped.2023.1122589
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author Zhang, Jiamin
Xu, Changdi
Yan, Shasha
Zhang, Xuefang
Zhao, Deyu
Liu, Feng
author_facet Zhang, Jiamin
Xu, Changdi
Yan, Shasha
Zhang, Xuefang
Zhao, Deyu
Liu, Feng
author_sort Zhang, Jiamin
collection PubMed
description Adenoviral pneumonia in children was an epidemic that greatly impacted children's health in China in 2019. Currently, no simple or systematic scale has been introduced for the early identification and diagnosis of adenoviral pneumonia. The early recognition scale of pediatric severe adenovirus pneumonia was established based on an analysis of the children's community-acquired pneumonia clinical cohort. This study analyzed the clinical data of 132 children with adenoviral pneumonia who were admitted to the Children's Hospital of Nanjing Medical University. The clinical parameters and imaging features were analyzed using univariate and multivariate logistic regression analyses. A nomogram was constructed to predict the risk of developing severe adenovirus pneumonia in children. There were statistically significant differences in age, respiratory rate, fever duration before admission, percentage of neutrophils and lymphocytes, CRP, ALT, and LDH between the two groups. Logistic regression analysis was conducted using the R language, and respiratory rate, percentage of neutrophils, percentage of lymphocytes, and LDH were used as scale indicators. Using the ROC curve, the sensitivity and specificity of the scale were 93.3% and 92.1%. This scale has good sensitivity and specificity through internal verification, which proves that screening for early recognition of severe adenovirus pneumonia can be realized by scales. This predictive scale helps determine whether a child will develop severe adenovirus pneumonia early in the disease course.
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spelling pubmed-100148182023-03-16 A nomogram for predicting severe adenovirus pneumonia in children Zhang, Jiamin Xu, Changdi Yan, Shasha Zhang, Xuefang Zhao, Deyu Liu, Feng Front Pediatr Pediatrics Adenoviral pneumonia in children was an epidemic that greatly impacted children's health in China in 2019. Currently, no simple or systematic scale has been introduced for the early identification and diagnosis of adenoviral pneumonia. The early recognition scale of pediatric severe adenovirus pneumonia was established based on an analysis of the children's community-acquired pneumonia clinical cohort. This study analyzed the clinical data of 132 children with adenoviral pneumonia who were admitted to the Children's Hospital of Nanjing Medical University. The clinical parameters and imaging features were analyzed using univariate and multivariate logistic regression analyses. A nomogram was constructed to predict the risk of developing severe adenovirus pneumonia in children. There were statistically significant differences in age, respiratory rate, fever duration before admission, percentage of neutrophils and lymphocytes, CRP, ALT, and LDH between the two groups. Logistic regression analysis was conducted using the R language, and respiratory rate, percentage of neutrophils, percentage of lymphocytes, and LDH were used as scale indicators. Using the ROC curve, the sensitivity and specificity of the scale were 93.3% and 92.1%. This scale has good sensitivity and specificity through internal verification, which proves that screening for early recognition of severe adenovirus pneumonia can be realized by scales. This predictive scale helps determine whether a child will develop severe adenovirus pneumonia early in the disease course. Frontiers Media S.A. 2023-03-01 /pmc/articles/PMC10014818/ /pubmed/36937948 http://dx.doi.org/10.3389/fped.2023.1122589 Text en © 2023 Zhang, Xu, Yan, Zhang, Zhao and Liu. 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) (https://creativecommons.org/licenses/by/4.0/) . 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 Pediatrics
Zhang, Jiamin
Xu, Changdi
Yan, Shasha
Zhang, Xuefang
Zhao, Deyu
Liu, Feng
A nomogram for predicting severe adenovirus pneumonia in children
title A nomogram for predicting severe adenovirus pneumonia in children
title_full A nomogram for predicting severe adenovirus pneumonia in children
title_fullStr A nomogram for predicting severe adenovirus pneumonia in children
title_full_unstemmed A nomogram for predicting severe adenovirus pneumonia in children
title_short A nomogram for predicting severe adenovirus pneumonia in children
title_sort nomogram for predicting severe adenovirus pneumonia in children
topic Pediatrics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10014818/
https://www.ncbi.nlm.nih.gov/pubmed/36937948
http://dx.doi.org/10.3389/fped.2023.1122589
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