关键词: 颅脑外伤, 术后快速康复, 个体化预测, 列线图模型

Abstract: Objective To establish an individualized column chart model for predicting the risk of rapid postoperative recovery in patients with traumatic brain injury(TBI). Methods A retrospective analysis was conducted on the clinical data of 240 TBI patients who underwent surgical treatment in our hospital from October 2023 to November 2025.70% of patients were randomly selected as the training group(n=168),and 30% of patients were selected as the validation group(n=72).Patients in the training group were assigned into a rapid recovery group(n=101) and a poor recovery group(n=67) based on whether they recovered quickly after surgery.The logistic regression model was used to screen high-risk factors that affected the rapid postoperative recovery of TBI patients in the training group,and the column chart prediction model was constructed.The predictive performance of the column chart model was evaluated through ROC curve,calibration curve,and Hosmer-Lemeshow goodness of fit test,and external validation was performed using data in validation group. Results There were statistically great differences in age,preoperative GCS score,BIS,length of hospital stay,midline shift,basal ganglia,lesion side,and bleeding site between the rapid recovery group and the poor recovery group(P＜0.05).Logistic regression analysis showed that age>65 years old(OR=1.545,95% CI=1.108~1.849),decreased GCS score(OR=1.392,95% CI=1.256~1.601),decreased BIS(OR=1.919,95% CI=1.869~1.973),and midline shift>15 mm(OR=1.326,95% CI=1.122~1.869) were independent risk factors for poor postoperative recovery in TBI patients(P＜0.05).The area under the ROC curve of the model in the training group was 0.935(95% CI=0.895~0.975),indicating good discriminability;the calibration curve tended towards the ideal curve,and the actual value was in good agreement with the predicted value.The area under the ROC curve of the model in the validation group was 0.929(95% CI=0.873~0.985),indicating good discriminability;the calibration curve tended towards the ideal curve,and the actual value was in good agreement with the predicted value. Conclusion The column chart model constructed based on the four independent risk factors selected by the logistic regression model has good predictive value for the risk of poor postoperative recovery in TBI patients.

Key words: Traumatic brain injury, Rapid postoperative recovery, Individualized prediction, Column chart model