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Establishment and validation of prognosis model for patients with cerebral contusion

BACKGROUND AND OBJECTIVE: Cerebral Contusion (CC) is one of the most serious injury types in patients with traumatic brain injury (TBI). In this study, the baseline data, imaging features and laboratory examinations of patients with CC were summarized and analyzed to develop and validate a predictio...

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Autores principales: Zhu, Yufeng, Jin, Xiaoqing, Xu, Lulu, Han, Pei, Lin, Shengwu, Lu, Zhongsheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628400/
https://www.ncbi.nlm.nih.gov/pubmed/34844563
http://dx.doi.org/10.1186/s12883-021-02482-4
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author Zhu, Yufeng
Jin, Xiaoqing
Xu, Lulu
Han, Pei
Lin, Shengwu
Lu, Zhongsheng
author_facet Zhu, Yufeng
Jin, Xiaoqing
Xu, Lulu
Han, Pei
Lin, Shengwu
Lu, Zhongsheng
author_sort Zhu, Yufeng
collection PubMed
description BACKGROUND AND OBJECTIVE: Cerebral Contusion (CC) is one of the most serious injury types in patients with traumatic brain injury (TBI). In this study, the baseline data, imaging features and laboratory examinations of patients with CC were summarized and analyzed to develop and validate a prediction model of nomogram to evaluate the clinical outcomes of patients. METHODS: A total of 426 patients with cerebral contusion (CC) admitted to the People’s Hospital of Qinghai Province and Affiliated Hospital of Qingdao University from January 2018 to January 2021 were included in this study, We randomly divided the cohort into a training cohort (n = 284) and a validation cohort (n = 142) with a ratio of 2:1.At Least absolute shrinkage and selection operator (Lasso) regression were used for screening high-risk factors affecting patient prognosis and development of the predictive model. The identification ability and clinical application value of the prediction model were analyzed through the analysis of receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA). RESULTS: Twelve independent prognostic factors, including age, Glasgow Coma Score (GCS), Basal cistern status, Midline shift (MLS), Third ventricle status, intracranial pressure (ICP) and CT grade of cerebral edema,etc., were selected by Lasso regression analysis and included in the nomogram. The model showed good predictive performance, with a C index of (0.87, 95% CI, 0.026–0.952) in the training cohort and (0.93, 95% CI, 0.032–0.965) in the validation cohort. Clinical decision curve analysis (DCA) also showed that the model brought high clinical benefits to patients. CONCLUSION: This study established a high accuracy of nomogram model to predict the prognosis of patients with CC, its low cost, easy to promote, is especially applicable in the acute environment, at the same time, CSF-glucose/lactate ratio(C-G/L), volume of contusion, and mean CT values of edema zone, which were included for the first time in this study, were independent predictors of poor prognosis in patients with CC. However, this model still has some limitations and deficiencies, which require large sample and multi-center prospective studies to verify and improve our results. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12883-021-02482-4.
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spelling pubmed-86284002021-12-01 Establishment and validation of prognosis model for patients with cerebral contusion Zhu, Yufeng Jin, Xiaoqing Xu, Lulu Han, Pei Lin, Shengwu Lu, Zhongsheng BMC Neurol Research BACKGROUND AND OBJECTIVE: Cerebral Contusion (CC) is one of the most serious injury types in patients with traumatic brain injury (TBI). In this study, the baseline data, imaging features and laboratory examinations of patients with CC were summarized and analyzed to develop and validate a prediction model of nomogram to evaluate the clinical outcomes of patients. METHODS: A total of 426 patients with cerebral contusion (CC) admitted to the People’s Hospital of Qinghai Province and Affiliated Hospital of Qingdao University from January 2018 to January 2021 were included in this study, We randomly divided the cohort into a training cohort (n = 284) and a validation cohort (n = 142) with a ratio of 2:1.At Least absolute shrinkage and selection operator (Lasso) regression were used for screening high-risk factors affecting patient prognosis and development of the predictive model. The identification ability and clinical application value of the prediction model were analyzed through the analysis of receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA). RESULTS: Twelve independent prognostic factors, including age, Glasgow Coma Score (GCS), Basal cistern status, Midline shift (MLS), Third ventricle status, intracranial pressure (ICP) and CT grade of cerebral edema,etc., were selected by Lasso regression analysis and included in the nomogram. The model showed good predictive performance, with a C index of (0.87, 95% CI, 0.026–0.952) in the training cohort and (0.93, 95% CI, 0.032–0.965) in the validation cohort. Clinical decision curve analysis (DCA) also showed that the model brought high clinical benefits to patients. CONCLUSION: This study established a high accuracy of nomogram model to predict the prognosis of patients with CC, its low cost, easy to promote, is especially applicable in the acute environment, at the same time, CSF-glucose/lactate ratio(C-G/L), volume of contusion, and mean CT values of edema zone, which were included for the first time in this study, were independent predictors of poor prognosis in patients with CC. However, this model still has some limitations and deficiencies, which require large sample and multi-center prospective studies to verify and improve our results. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12883-021-02482-4. BioMed Central 2021-11-29 /pmc/articles/PMC8628400/ /pubmed/34844563 http://dx.doi.org/10.1186/s12883-021-02482-4 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Zhu, Yufeng
Jin, Xiaoqing
Xu, Lulu
Han, Pei
Lin, Shengwu
Lu, Zhongsheng
Establishment and validation of prognosis model for patients with cerebral contusion
title Establishment and validation of prognosis model for patients with cerebral contusion
title_full Establishment and validation of prognosis model for patients with cerebral contusion
title_fullStr Establishment and validation of prognosis model for patients with cerebral contusion
title_full_unstemmed Establishment and validation of prognosis model for patients with cerebral contusion
title_short Establishment and validation of prognosis model for patients with cerebral contusion
title_sort establishment and validation of prognosis model for patients with cerebral contusion
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628400/
https://www.ncbi.nlm.nih.gov/pubmed/34844563
http://dx.doi.org/10.1186/s12883-021-02482-4
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