To construct a nomogram model for predicting the risk of new bleeding for traumatic brain injury (TBI) after decompressive craniectomy.

A total of 187 TBI patients who underwent decompressive craniotomy at Second Department of Surgery of Chongqing Kaizhou Hospital of Traditional Chinese Medicine from January 2020 to December 2022 were selected, the occurrence of postoperative new blood emission was recorded. Patients were divided into newly generated blood group and non-newly generated blood group based on whether they experienced new bleeding after surgery, and binary Logistic regression analysis was used to screen for risk factors for new blood emission. The risk prediction model of new blood flow after TBI was constructed by risk factors. Internal validation was performed using bootstrap resampled 1000 times (validation set of 63 cases). Hosmer-Lemeshow was used to evaluate the fit degree of the model, receiver operating characteristic (ROC) curve was used to analyze the value of the model, calibration curve was used to verify the accuracy of the model, and decision curve was used to evaluate the clinical benefits of the model.

Among the 187 patients, there were 23 cases (12.3%) in the newly generated blood group and 164 cases (87.7%) in the non- newly generated blood group. There were differences in the combined skull fracture, preoperative hematoma volume, preoperative Rotterdam CT score, preoperative subdural hematoma, cerebral hernia, postoperative hypotension, surgery time, injury to surgery time, and thrombin time between the two groups of patients (P<0.05). Binary Logistic regression analysis confirmed that combined skull fractures, preoperative hematoma volume≥20 cm³, Rotterdam CT score (4-6 points), postoperative hypotension, and surgery time were independent risk factors for new postoperative bleeding. Constructing a predictive model for risk factors using R language, Hosmer Lemeshow test showed good calibration of the training set (χ²=1.944, P=0.963). ROC analysis showed that the AUC of the training set and validation set were 0.905 (95%CI: 0.849-0.960) and 0.925 (95%CI: 0.839-1.000), respectively. The calibration curve fits well with the ideal curve, indicating high accuracy of the prediction model; The decision curve analysis shows that the model predicts a relatively large net benefit range for new bleeding after decompressive craniectomy.

Combined with skull fracture, preoperative hematoma ≥20 cm³, Rotterdam CT score (4-6 points), postoperative hypotension, and long operation time are the influencing factors for postoperative new blood emission. The risk prediction model based on this construction can provide an auxiliary reference for clinical assessment of the risk of postoperative new blood emission.