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 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.

Establishment and validation of a prediction model for intraparenchymal hematoma expansion in patients with cerebral contusion: A reliable Nomogram.

BACKGROUND AND OBJECTIVE: Cerebral Contusion (CC) is one of the most serious injury types in patients with traumatic brain injury (TBI). Traumatic intraparenchymal hematoma (TICH) expansion severely affects the patient's prognosis. In this study, the baseline data, imaging features, and laboratory examinations of patients with CC were summarized and analyzed to develop and validate a nomogram predictive model assessing the risk factors for TICH expansion. METHODS: Totally 258 patients were included and retrospectively analyzed herein, who met the CC inclusion criteria, from July 2018 to July 2021. TICH expansion was defined as increased hematoma volume ≥ 30% relative to primary volume or an absolute hematoma increase ≥ 5 ml at CT review. RESULTS: Univariate and binary logistic regression analyses were performed to screen out the independent predictors significantly correlated with TICH expansion: Age, subdural hematoma (SDH), contusion site, multihematoma fuzzy sign (MFS), contusion volume, and traumatic coagulation abnormalities (TCA). Based on these, the nomogram model was established. The differences between the contusion volume and glasgow outcome scale (GOS) were analyzed by the nonparametric tests. Larger contusion volume was associated with poor prognosis. CONCLUSION: This study established a Nomogram model to predict TICH expansion in patients with CC. Meanwhile, the study found that the risk of bleeding tended to decrease when the hematoma volume was > 15 ml, but the larger initial hematoma volume would indicate worse prognosis. We advocate the use of predictive models for TICH expansion risk assessment in hospitalized CC patients, which is low-cost and easy-to-apply, especially in acute settings.

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 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.