Cargando…
Establishment and validation of PTE prediction model in patients with cerebral contusion
Post-traumatic epilepsy (PTE) is an important cause of poor prognosis in patients with cerebral contusions. The primary purpose of this study is to evaluate the high-risk factors of PTE by summarizing and analyzing the baseline data, laboratory examination, and imaging features of patients with a ce...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9708650/ https://www.ncbi.nlm.nih.gov/pubmed/36446999 http://dx.doi.org/10.1038/s41598-022-24824-z |
_version_ | 1784840982912565248 |
---|---|
author | Lin, Shengwu Wang, Qianqian Zhu, Yufeng Jin, Xiaoqing Han, Pei Lu, Zhongsheng |
author_facet | Lin, Shengwu Wang, Qianqian Zhu, Yufeng Jin, Xiaoqing Han, Pei Lu, Zhongsheng |
author_sort | Lin, Shengwu |
collection | PubMed |
description | Post-traumatic epilepsy (PTE) is an important cause of poor prognosis in patients with cerebral contusions. The primary purpose of this study is to evaluate the high-risk factors of PTE by summarizing and analyzing the baseline data, laboratory examination, and imaging features of patients with a cerebral contusion, and then developing a Nomogram prediction model and validating it. This study included 457 patients diagnosed with cerebral contusion who met the inclusion criteria from November 2016 to November 2019 at the Qinghai Provincial People's Hospital. All patients were assessed for seizure activity seven days after injury. Univariate analysis was used to determine the risk factors for PTE. Significant risk factors in univariate analysis were selected for binary logistic regression analysis. P < 0.05 was statistically significant. Based on the binary logistic regression analysis results, the prediction scoring system of PTE is established by Nomogram, and the line chart model is drawn. Finally, external validation was performed on 457 participants to assess its performance. Univariate and binary logistic regression analyses were performed using SPSS software, and the independent predictors significantly associated with PTE were screened as Contusion site, Chronic alcohol use, Contusion volume, Skull fracture, Subdural hematoma (SDH), Glasgow coma scale (GCS) score, and Non late post-traumatic seizure (Non-LPTS). Based on this, a Nomogram model was developed. The prediction accuracy of our scoring system was C-index = 98.29%. The confidence interval of the C-index was 97.28% ~ 99.30%. Internal validation showed that the calibration plot of this model was close to the ideal line. This study developed and verified a highly accurate Nomogram model, which can be used to individualize PTE prediction in patients with a cerebral contusion. It can identify individuals at high risk of PTE and help us pay attention to prevention in advance. The model has a low cost and is easy to be popularized in the clinic. This model still has some limitations and deficiencies, which need to be verified and improved by future large-sample and multicenter prospective studies. |
format | Online Article Text |
id | pubmed-9708650 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-97086502022-12-01 Establishment and validation of PTE prediction model in patients with cerebral contusion Lin, Shengwu Wang, Qianqian Zhu, Yufeng Jin, Xiaoqing Han, Pei Lu, Zhongsheng Sci Rep Article Post-traumatic epilepsy (PTE) is an important cause of poor prognosis in patients with cerebral contusions. The primary purpose of this study is to evaluate the high-risk factors of PTE by summarizing and analyzing the baseline data, laboratory examination, and imaging features of patients with a cerebral contusion, and then developing a Nomogram prediction model and validating it. This study included 457 patients diagnosed with cerebral contusion who met the inclusion criteria from November 2016 to November 2019 at the Qinghai Provincial People's Hospital. All patients were assessed for seizure activity seven days after injury. Univariate analysis was used to determine the risk factors for PTE. Significant risk factors in univariate analysis were selected for binary logistic regression analysis. P < 0.05 was statistically significant. Based on the binary logistic regression analysis results, the prediction scoring system of PTE is established by Nomogram, and the line chart model is drawn. Finally, external validation was performed on 457 participants to assess its performance. Univariate and binary logistic regression analyses were performed using SPSS software, and the independent predictors significantly associated with PTE were screened as Contusion site, Chronic alcohol use, Contusion volume, Skull fracture, Subdural hematoma (SDH), Glasgow coma scale (GCS) score, and Non late post-traumatic seizure (Non-LPTS). Based on this, a Nomogram model was developed. The prediction accuracy of our scoring system was C-index = 98.29%. The confidence interval of the C-index was 97.28% ~ 99.30%. Internal validation showed that the calibration plot of this model was close to the ideal line. This study developed and verified a highly accurate Nomogram model, which can be used to individualize PTE prediction in patients with a cerebral contusion. It can identify individuals at high risk of PTE and help us pay attention to prevention in advance. The model has a low cost and is easy to be popularized in the clinic. This model still has some limitations and deficiencies, which need to be verified and improved by future large-sample and multicenter prospective studies. Nature Publishing Group UK 2022-11-29 /pmc/articles/PMC9708650/ /pubmed/36446999 http://dx.doi.org/10.1038/s41598-022-24824-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Lin, Shengwu Wang, Qianqian Zhu, Yufeng Jin, Xiaoqing Han, Pei Lu, Zhongsheng Establishment and validation of PTE prediction model in patients with cerebral contusion |
title | Establishment and validation of PTE prediction model in patients with cerebral contusion |
title_full | Establishment and validation of PTE prediction model in patients with cerebral contusion |
title_fullStr | Establishment and validation of PTE prediction model in patients with cerebral contusion |
title_full_unstemmed | Establishment and validation of PTE prediction model in patients with cerebral contusion |
title_short | Establishment and validation of PTE prediction model in patients with cerebral contusion |
title_sort | establishment and validation of pte prediction model in patients with cerebral contusion |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9708650/ https://www.ncbi.nlm.nih.gov/pubmed/36446999 http://dx.doi.org/10.1038/s41598-022-24824-z |
work_keys_str_mv | AT linshengwu establishmentandvalidationofptepredictionmodelinpatientswithcerebralcontusion AT wangqianqian establishmentandvalidationofptepredictionmodelinpatientswithcerebralcontusion AT zhuyufeng establishmentandvalidationofptepredictionmodelinpatientswithcerebralcontusion AT jinxiaoqing establishmentandvalidationofptepredictionmodelinpatientswithcerebralcontusion AT hanpei establishmentandvalidationofptepredictionmodelinpatientswithcerebralcontusion AT luzhongsheng establishmentandvalidationofptepredictionmodelinpatientswithcerebralcontusion |