Risk factors and construction of a predictive nomogram model for intraoperative brain bulge in patients with traumatic brain injury

YAN Binbin; ZHENG Bo; YUAN Ping

doi:10.11850/j.issn.1009-122X.2025.11.004

Abstract：Objective To analyze the risk factors for intraoperative brain bulge(IOBB)in patients with traumatic brain injury(TBI)and construct a nomogram predictive model.Methods Clinical data of 360 TBI patients were analyzed retrospectively.The patients were divided into a modeling group(n=288)and a validation group(n=72)in a 4:1 ratio.Based on the clinical data of the modeling group,patients were divided into an IOBB group and a non-IOBB group according to whether IOBB occurred.Univariate and multivariate analyses were performed.A nomogram predictive model was constructed based on the results of the multivariate analysis,and the model's discrimination and clinical utility were validated.Results There were no statistically significant differences in the clinical data between the modeling group and the validation group(all P>0.05).The univariate analysis results showed that there were statistically significant differences between the IOBB group and the non-IOBB group in terms of pupil dilation,contralateral skull fracture,epidural hemorrhage,subdural hemorrhage,age,blood glucose,preoperative intracranial pressure,preoperative GCS score,midline displacement of brain CT,CT value of the lesion side transverse sinus,CT value of the healthy side transverse sinus,and CT value of the superior sagittal sinus(all P<0.05).The multivariate analysis results showed that pupil dilation(OR=7.907,95%CI:1.790-34.934,P=0.006),contralateral skull fractures(OR=7.094,95%CI:2.053-24.511,P=0.002),subdural hemorrhage(OR=6.534,95%CI:1.594-26.787,P=0.009),age(OR=0.888,95%CI:0.817-0.965,P=0.005),and CT values of the affected transverse sinus(OR=1.328,95%CI:1.169-1.510,P<0.001)were all risk factors for IOBB in TBI patients.The area under the curve(AUC)values for the modeling group and the validation group were 0.929(95%CI:0.880-0.978)and 0.964(95%CI:0.914-1.000),respectively.Decision curve analysis(DCA)showed that within the threshold probability range of 0-1.0,patients could potentially obtain a relatively high positive net benefit when interventions were carried out based on this model.Clinical impact curve(CIC)analysis indicated that within the threshold probability range of 0-1.0,this model could accurately predict the risk of IOBB in TBI patients.Conclusions Multiple factors can lead to IOBB in TBI patients.Constructing a nomogram predictive model and conducting a preoperative risk assessment of IOBB are of great significance for preventing IOBB.