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Establishment and validation of a model for brain injury state evaluation and prognosis prediction

PURPOSE: Traumatic brain injury (TBI) is one of the leading causes of disability and death in modern times, whose evaluation and prognosis prediction have been one of the most critical issues in TBI management. However, the existed models for the abovementioned purposes were defective to varying deg...

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Autores principales: Li, Xia, Lü, Chao, Wang, Jun, Wan, Yi, Dai, Shu-Hui, Zhang, Lei, Hu, Xue-An, Jiang, Xiao-Fan, Fei, Zhou
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7567905/
https://www.ncbi.nlm.nih.gov/pubmed/32928607
http://dx.doi.org/10.1016/j.cjtee.2020.08.006
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author Li, Xia
Lü, Chao
Wang, Jun
Wan, Yi
Dai, Shu-Hui
Zhang, Lei
Hu, Xue-An
Jiang, Xiao-Fan
Fei, Zhou
author_facet Li, Xia
Lü, Chao
Wang, Jun
Wan, Yi
Dai, Shu-Hui
Zhang, Lei
Hu, Xue-An
Jiang, Xiao-Fan
Fei, Zhou
author_sort Li, Xia
collection PubMed
description PURPOSE: Traumatic brain injury (TBI) is one of the leading causes of disability and death in modern times, whose evaluation and prognosis prediction have been one of the most critical issues in TBI management. However, the existed models for the abovementioned purposes were defective to varying degrees. This study aims to establish an ideal brain injury state clinical prediction model (BISCPM). METHODS: This study was a retrospective design. The six-month outcomes of patients were selected as the end point event. BISCPM was established by using the split-sample technology, and externally validated via different tests of comparison between the observed and predicted six-month mortality in validating group. TBI patients admitted from July 2006 to June 2012 were recruited and randomly divided into establishing model group and validating model group. Twenty-one scoring indicators were included in BISCPM and divided into three parts, A, B, and C. Part A included movement, pupillary reflex and diameter, CT parameters, and secondary brain insult factors, etc. Part B was age and part C was medical history of the patients. The total score of part A, B and C was final score of BISCPM. RESULTS: Altogether 1156 TBI patients were included with 578 cases in each group. The score of BISCPM from validating group ranged from 2.75 to 31.94, averaging 13.64 ± 5.59. There was not statistical difference between observed and predicted mortality for validating group. The discrimination validation showed that the BISCPM is superior to international mission for prognosis and analysis of clinical trials (IMPACT) lab model. CONCLUSION: BISCPM is an effective model for state evaluation and prognosis prediction of TBI patients. The use of BISCPM could be of great significance for decision-making in management of TBI.
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spelling pubmed-75679052020-10-20 Establishment and validation of a model for brain injury state evaluation and prognosis prediction Li, Xia Lü, Chao Wang, Jun Wan, Yi Dai, Shu-Hui Zhang, Lei Hu, Xue-An Jiang, Xiao-Fan Fei, Zhou Chin J Traumatol Original Article PURPOSE: Traumatic brain injury (TBI) is one of the leading causes of disability and death in modern times, whose evaluation and prognosis prediction have been one of the most critical issues in TBI management. However, the existed models for the abovementioned purposes were defective to varying degrees. This study aims to establish an ideal brain injury state clinical prediction model (BISCPM). METHODS: This study was a retrospective design. The six-month outcomes of patients were selected as the end point event. BISCPM was established by using the split-sample technology, and externally validated via different tests of comparison between the observed and predicted six-month mortality in validating group. TBI patients admitted from July 2006 to June 2012 were recruited and randomly divided into establishing model group and validating model group. Twenty-one scoring indicators were included in BISCPM and divided into three parts, A, B, and C. Part A included movement, pupillary reflex and diameter, CT parameters, and secondary brain insult factors, etc. Part B was age and part C was medical history of the patients. The total score of part A, B and C was final score of BISCPM. RESULTS: Altogether 1156 TBI patients were included with 578 cases in each group. The score of BISCPM from validating group ranged from 2.75 to 31.94, averaging 13.64 ± 5.59. There was not statistical difference between observed and predicted mortality for validating group. The discrimination validation showed that the BISCPM is superior to international mission for prognosis and analysis of clinical trials (IMPACT) lab model. CONCLUSION: BISCPM is an effective model for state evaluation and prognosis prediction of TBI patients. The use of BISCPM could be of great significance for decision-making in management of TBI. Elsevier 2020-10 2020-08-20 /pmc/articles/PMC7567905/ /pubmed/32928607 http://dx.doi.org/10.1016/j.cjtee.2020.08.006 Text en © 2020 Production and hosting by Elsevier B.V. on behalf of Chinese Medical Association. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Article
Li, Xia
Lü, Chao
Wang, Jun
Wan, Yi
Dai, Shu-Hui
Zhang, Lei
Hu, Xue-An
Jiang, Xiao-Fan
Fei, Zhou
Establishment and validation of a model for brain injury state evaluation and prognosis prediction
title Establishment and validation of a model for brain injury state evaluation and prognosis prediction
title_full Establishment and validation of a model for brain injury state evaluation and prognosis prediction
title_fullStr Establishment and validation of a model for brain injury state evaluation and prognosis prediction
title_full_unstemmed Establishment and validation of a model for brain injury state evaluation and prognosis prediction
title_short Establishment and validation of a model for brain injury state evaluation and prognosis prediction
title_sort establishment and validation of a model for brain injury state evaluation and prognosis prediction
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7567905/
https://www.ncbi.nlm.nih.gov/pubmed/32928607
http://dx.doi.org/10.1016/j.cjtee.2020.08.006
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