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Development and validation of the hypertensive intracerebral hemorrhage prognosis models
To develop and validate the prognosis model of hypertensive intracerebral hemorrhage based on admission characteristics, which would be applied to predict the 3-month outcome. For developing the prognosis models, we studied data from 325 patients with retrospectively consecutive hypertensive intrace...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6181527/ https://www.ncbi.nlm.nih.gov/pubmed/30278523 http://dx.doi.org/10.1097/MD.0000000000012446 |
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author | Ding, Wu Gu, Zhiwei Song, Dagang Liu, Jiansheng Zheng, Gang Tu, Chuanjian |
author_facet | Ding, Wu Gu, Zhiwei Song, Dagang Liu, Jiansheng Zheng, Gang Tu, Chuanjian |
author_sort | Ding, Wu |
collection | PubMed |
description | To develop and validate the prognosis model of hypertensive intracerebral hemorrhage based on admission characteristics, which would be applied to predict the 3-month outcome. For developing the prognosis models, we studied data from 325 patients with retrospectively consecutive hypertensive intracerebral hemorrhage admitted between 2012 and 2016. The predictive value of admission characteristics was tested in logistic regression models, presenting 3-month outcome as the primary outcome. The performance of the models was tested by discrimination and calibration. After development, internal and external validations were used to test the function. The multivariate analysis of logistic regression indicated that age, Glasgow coma scale score, pupillary light reflex, hypoxemia, intracerebral hemorrhage volume, blood glucose, and D-dimer level were independent factors of the hypertensive intracerebral hemorrhage prognosis model. The prognosis model based on those admission risk factors worked well. The receiver operating characteristic curve was used to analyze the discriminant ability of model A, model A + B, and model A + B + C. Specifically, the area under the receiver operating characteristic curve increased from 0.816 (model A; 95% CI, 0.760–0.872) to 0.913 (model A + B + C; 95% CI, 0.881–0.946), and the models were not overoptimistic and were applicably confirmed by internal and external validations respectively. This prognosis model could be used to predict the prognosis of patients with hypertensive intracerebral hemorrhage early, simply and accurately, contributing to the clinical treatment eventually. |
format | Online Article Text |
id | pubmed-6181527 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-61815272018-10-15 Development and validation of the hypertensive intracerebral hemorrhage prognosis models Ding, Wu Gu, Zhiwei Song, Dagang Liu, Jiansheng Zheng, Gang Tu, Chuanjian Medicine (Baltimore) Research Article To develop and validate the prognosis model of hypertensive intracerebral hemorrhage based on admission characteristics, which would be applied to predict the 3-month outcome. For developing the prognosis models, we studied data from 325 patients with retrospectively consecutive hypertensive intracerebral hemorrhage admitted between 2012 and 2016. The predictive value of admission characteristics was tested in logistic regression models, presenting 3-month outcome as the primary outcome. The performance of the models was tested by discrimination and calibration. After development, internal and external validations were used to test the function. The multivariate analysis of logistic regression indicated that age, Glasgow coma scale score, pupillary light reflex, hypoxemia, intracerebral hemorrhage volume, blood glucose, and D-dimer level were independent factors of the hypertensive intracerebral hemorrhage prognosis model. The prognosis model based on those admission risk factors worked well. The receiver operating characteristic curve was used to analyze the discriminant ability of model A, model A + B, and model A + B + C. Specifically, the area under the receiver operating characteristic curve increased from 0.816 (model A; 95% CI, 0.760–0.872) to 0.913 (model A + B + C; 95% CI, 0.881–0.946), and the models were not overoptimistic and were applicably confirmed by internal and external validations respectively. This prognosis model could be used to predict the prognosis of patients with hypertensive intracerebral hemorrhage early, simply and accurately, contributing to the clinical treatment eventually. Wolters Kluwer Health 2018-09-28 /pmc/articles/PMC6181527/ /pubmed/30278523 http://dx.doi.org/10.1097/MD.0000000000012446 Text en Copyright © 2018 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc-nd/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0 |
spellingShingle | Research Article Ding, Wu Gu, Zhiwei Song, Dagang Liu, Jiansheng Zheng, Gang Tu, Chuanjian Development and validation of the hypertensive intracerebral hemorrhage prognosis models |
title | Development and validation of the hypertensive intracerebral hemorrhage prognosis models |
title_full | Development and validation of the hypertensive intracerebral hemorrhage prognosis models |
title_fullStr | Development and validation of the hypertensive intracerebral hemorrhage prognosis models |
title_full_unstemmed | Development and validation of the hypertensive intracerebral hemorrhage prognosis models |
title_short | Development and validation of the hypertensive intracerebral hemorrhage prognosis models |
title_sort | development and validation of the hypertensive intracerebral hemorrhage prognosis models |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6181527/ https://www.ncbi.nlm.nih.gov/pubmed/30278523 http://dx.doi.org/10.1097/MD.0000000000012446 |
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