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Risk factors and risk nomogram model of reoperation for hemorrhages after severe traumatic brain injury craniotomy

OBJECTIVE: This study aimed to explore the risk factors associated with reoperation for postoperative hemorrhages after severe traumatic brain injury (sTBI) craniotomy and establish a risk nomogram model. METHODS: A retrospective case‐control study was performed. Overall, 367 patients who were diagn...

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Autores principales: Yang, Tao, Yu, Jie, Shen, Hao, Yang, Chao‐Zhi, Zhang, Ping, Li, Yi, Wu, Hai‐Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10529335/
https://www.ncbi.nlm.nih.gov/pubmed/37786884
http://dx.doi.org/10.1002/ibra.12032
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author Yang, Tao
Yu, Jie
Shen, Hao
Yang, Chao‐Zhi
Zhang, Ping
Li, Yi
Wu, Hai‐Tao
author_facet Yang, Tao
Yu, Jie
Shen, Hao
Yang, Chao‐Zhi
Zhang, Ping
Li, Yi
Wu, Hai‐Tao
author_sort Yang, Tao
collection PubMed
description OBJECTIVE: This study aimed to explore the risk factors associated with reoperation for postoperative hemorrhages after severe traumatic brain injury (sTBI) craniotomy and establish a risk nomogram model. METHODS: A retrospective case‐control study was performed. Overall, 367 patients who were diagnosed with sTBI and fulfilled the inclusion criteria were enrolled from the Department of Neurosurgery of the Affiliated Hospital of Zunyi Medical University between January 2015 and December 2020. They were divided into a reoperation group and a non‐reoperation group according to whether they underwent reoperation for hemorrhages. Using univariate binary logistic regression analysis, the possible risk factors were screened. Subsequently, the independent risk factors of reoperation for postoperative hemorrhages were screened using the forward step method of multivariate binary logistic regression analysis, and a corresponding nomogram model was constructed. The receiver operative characteristic (ROC) curve was used to evaluate the reliability of the model. Finally, 30% of the data were randomly selected for internal verification of the model. RESULTS: The reoperation rate for hemorrhage after sTBI emergency craniotomy was 14.71% (54/367); multivariate logistic regression analysis showed that multiple hemorrhages (odds ratio [OR] = 4.38, 95% confidence interval [CI]: 1.815–10.587, p = 0.001), day or night surgery (OR = 0.26, 95% CI: 0.119–0.547, p < 0.001), operation duration (OR = 0.74, 95% CI: 0.119–0.547, p < 0.025), and abnormal intraoperative blood pressure fluctuation (OR = 4.15, 95% CI: 2.090–8.245, p < 0.001) were statistically significant. The sensitivity and specificity of the nomogram model were 0.815 and 0.661, respectively, and the area under ROC curve was 0.76 (95% CI: 0.705–0.833). Internal verification showed that the area under the ROC curve was 0.783 (95% CI: 0.683–0.883). CONCLUSIONS: Taken together, the results of our study reveal that multiple preoperative intracranial hemorrhages, day and night operation, operation duration, and abnormal fluctuation of intraoperative blood pressure were independent risk factors for postoperative bleeding and reoperation for sTBI. Through the analysis of the influencing factors, a prediction model for the risk of bleeding and reoperation after craniocerebral trauma was developed. Compared with other relevant studies, this prediction model has good prediction efficiency and can be used to predict the occurrence of bleeding and reoperation after sTBI in patients.
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spelling pubmed-105293352023-10-02 Risk factors and risk nomogram model of reoperation for hemorrhages after severe traumatic brain injury craniotomy Yang, Tao Yu, Jie Shen, Hao Yang, Chao‐Zhi Zhang, Ping Li, Yi Wu, Hai‐Tao Ibrain Original Articles OBJECTIVE: This study aimed to explore the risk factors associated with reoperation for postoperative hemorrhages after severe traumatic brain injury (sTBI) craniotomy and establish a risk nomogram model. METHODS: A retrospective case‐control study was performed. Overall, 367 patients who were diagnosed with sTBI and fulfilled the inclusion criteria were enrolled from the Department of Neurosurgery of the Affiliated Hospital of Zunyi Medical University between January 2015 and December 2020. They were divided into a reoperation group and a non‐reoperation group according to whether they underwent reoperation for hemorrhages. Using univariate binary logistic regression analysis, the possible risk factors were screened. Subsequently, the independent risk factors of reoperation for postoperative hemorrhages were screened using the forward step method of multivariate binary logistic regression analysis, and a corresponding nomogram model was constructed. The receiver operative characteristic (ROC) curve was used to evaluate the reliability of the model. Finally, 30% of the data were randomly selected for internal verification of the model. RESULTS: The reoperation rate for hemorrhage after sTBI emergency craniotomy was 14.71% (54/367); multivariate logistic regression analysis showed that multiple hemorrhages (odds ratio [OR] = 4.38, 95% confidence interval [CI]: 1.815–10.587, p = 0.001), day or night surgery (OR = 0.26, 95% CI: 0.119–0.547, p < 0.001), operation duration (OR = 0.74, 95% CI: 0.119–0.547, p < 0.025), and abnormal intraoperative blood pressure fluctuation (OR = 4.15, 95% CI: 2.090–8.245, p < 0.001) were statistically significant. The sensitivity and specificity of the nomogram model were 0.815 and 0.661, respectively, and the area under ROC curve was 0.76 (95% CI: 0.705–0.833). Internal verification showed that the area under the ROC curve was 0.783 (95% CI: 0.683–0.883). CONCLUSIONS: Taken together, the results of our study reveal that multiple preoperative intracranial hemorrhages, day and night operation, operation duration, and abnormal fluctuation of intraoperative blood pressure were independent risk factors for postoperative bleeding and reoperation for sTBI. Through the analysis of the influencing factors, a prediction model for the risk of bleeding and reoperation after craniocerebral trauma was developed. Compared with other relevant studies, this prediction model has good prediction efficiency and can be used to predict the occurrence of bleeding and reoperation after sTBI in patients. John Wiley and Sons Inc. 2022-04-13 /pmc/articles/PMC10529335/ /pubmed/37786884 http://dx.doi.org/10.1002/ibra.12032 Text en © 2022 The Authors. Ibrain published by Affiliated Hospital of Zunyi Medical University (AHZMU) and Wiley‐VCH GmbH. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Yang, Tao
Yu, Jie
Shen, Hao
Yang, Chao‐Zhi
Zhang, Ping
Li, Yi
Wu, Hai‐Tao
Risk factors and risk nomogram model of reoperation for hemorrhages after severe traumatic brain injury craniotomy
title Risk factors and risk nomogram model of reoperation for hemorrhages after severe traumatic brain injury craniotomy
title_full Risk factors and risk nomogram model of reoperation for hemorrhages after severe traumatic brain injury craniotomy
title_fullStr Risk factors and risk nomogram model of reoperation for hemorrhages after severe traumatic brain injury craniotomy
title_full_unstemmed Risk factors and risk nomogram model of reoperation for hemorrhages after severe traumatic brain injury craniotomy
title_short Risk factors and risk nomogram model of reoperation for hemorrhages after severe traumatic brain injury craniotomy
title_sort risk factors and risk nomogram model of reoperation for hemorrhages after severe traumatic brain injury craniotomy
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10529335/
https://www.ncbi.nlm.nih.gov/pubmed/37786884
http://dx.doi.org/10.1002/ibra.12032
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