Author:
Lin Shengwu,Wang Qianqian,Zhu Yufeng,Jin Xiaoqing,Han Pei,Lu Zhongsheng
Abstract
AbstractPost-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.
Funder
This work was supported by funds from the scientific research guiding plan project of Qinghai provincial health commission
Publisher
Springer Science and Business Media LLC
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