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Establishment and assessment of a nomogram model for predicting the risk of fulminant myocarditis: A STROBE compliant cross-sectional study

We aimed to identify potential clinical predictors associated with the risk of fulminant myocarditis, and further to establish and assess a nomogram model based on significant attributes for clinical practicability. This is a retrospective, cross-sectional study, involving 28 patients with fulminant...

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Autores principales: Xu, Guifen, Chen, Feizhen, Zhao, Wenxiang, Zheng, Yong, Zhuang, Wei, Yu, Fuling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8084052/
https://www.ncbi.nlm.nih.gov/pubmed/33907091
http://dx.doi.org/10.1097/MD.0000000000025317
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author Xu, Guifen
Chen, Feizhen
Zhao, Wenxiang
Zheng, Yong
Zhuang, Wei
Yu, Fuling
author_facet Xu, Guifen
Chen, Feizhen
Zhao, Wenxiang
Zheng, Yong
Zhuang, Wei
Yu, Fuling
author_sort Xu, Guifen
collection PubMed
description We aimed to identify potential clinical predictors associated with the risk of fulminant myocarditis, and further to establish and assess a nomogram model based on significant attributes for clinical practicability. This is a retrospective, cross-sectional study, involving 28 patients with fulminant myocarditis and 35 age-, and sex-matched patients with non-fulminant myocarditis. Effect-size estimates are expressed as odds ratio (OR) and 95% confidence interval (CI). Fifteen factors were primarily identified to be associated with the significant risk of fulminant myocarditis after adjusting for confounders. Due to strong correlation, 6 factors were retained, including mean arterial pressure (OR, 95% CI, P: .82, .72–.94, .005), creatinine (2.15, 1.13–4.10, 0.020), blood urea nitrogen (1.45, 1.04–2.02, 0.028), aspartate aminotransferase (2.62, 1.16–5.91, 0.021), troponin I (1.43, 1.07–1.90, 0.015), and ventricular wall motion abnormality (25.81, 2.52–264.69, 0.006). The contribution of the 6 significant factors to predicting fulminant myocarditis risk was significant from multi-angle analyses, and regressing these factors in a nomogram model exhibited good predictive accuracy, as reflected by both C-index (>90%, P < .001). We have identified 6 clinical factors in significant association with fulminant myocarditis, and their prediction capability was more obvious in a nomogram model. Further investigations with larger sample sizes and longer follow-up intervals are warranted.
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spelling pubmed-80840522021-05-01 Establishment and assessment of a nomogram model for predicting the risk of fulminant myocarditis: A STROBE compliant cross-sectional study Xu, Guifen Chen, Feizhen Zhao, Wenxiang Zheng, Yong Zhuang, Wei Yu, Fuling Medicine (Baltimore) 3900 We aimed to identify potential clinical predictors associated with the risk of fulminant myocarditis, and further to establish and assess a nomogram model based on significant attributes for clinical practicability. This is a retrospective, cross-sectional study, involving 28 patients with fulminant myocarditis and 35 age-, and sex-matched patients with non-fulminant myocarditis. Effect-size estimates are expressed as odds ratio (OR) and 95% confidence interval (CI). Fifteen factors were primarily identified to be associated with the significant risk of fulminant myocarditis after adjusting for confounders. Due to strong correlation, 6 factors were retained, including mean arterial pressure (OR, 95% CI, P: .82, .72–.94, .005), creatinine (2.15, 1.13–4.10, 0.020), blood urea nitrogen (1.45, 1.04–2.02, 0.028), aspartate aminotransferase (2.62, 1.16–5.91, 0.021), troponin I (1.43, 1.07–1.90, 0.015), and ventricular wall motion abnormality (25.81, 2.52–264.69, 0.006). The contribution of the 6 significant factors to predicting fulminant myocarditis risk was significant from multi-angle analyses, and regressing these factors in a nomogram model exhibited good predictive accuracy, as reflected by both C-index (>90%, P < .001). We have identified 6 clinical factors in significant association with fulminant myocarditis, and their prediction capability was more obvious in a nomogram model. Further investigations with larger sample sizes and longer follow-up intervals are warranted. Lippincott Williams & Wilkins 2021-04-30 /pmc/articles/PMC8084052/ /pubmed/33907091 http://dx.doi.org/10.1097/MD.0000000000025317 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
spellingShingle 3900
Xu, Guifen
Chen, Feizhen
Zhao, Wenxiang
Zheng, Yong
Zhuang, Wei
Yu, Fuling
Establishment and assessment of a nomogram model for predicting the risk of fulminant myocarditis: A STROBE compliant cross-sectional study
title Establishment and assessment of a nomogram model for predicting the risk of fulminant myocarditis: A STROBE compliant cross-sectional study
title_full Establishment and assessment of a nomogram model for predicting the risk of fulminant myocarditis: A STROBE compliant cross-sectional study
title_fullStr Establishment and assessment of a nomogram model for predicting the risk of fulminant myocarditis: A STROBE compliant cross-sectional study
title_full_unstemmed Establishment and assessment of a nomogram model for predicting the risk of fulminant myocarditis: A STROBE compliant cross-sectional study
title_short Establishment and assessment of a nomogram model for predicting the risk of fulminant myocarditis: A STROBE compliant cross-sectional study
title_sort establishment and assessment of a nomogram model for predicting the risk of fulminant myocarditis: a strobe compliant cross-sectional study
topic 3900
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8084052/
https://www.ncbi.nlm.nih.gov/pubmed/33907091
http://dx.doi.org/10.1097/MD.0000000000025317
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