Development of a nomogram model for predicting the risk of post-traumatic chronic disorders of consciousness in patients with severe craniocerebral injury

BAI Yan; TONG Huimin; WU Yuling; LI Hongxia; WANG Minli; ZHANG Haiying

doi:10.16048/j.issn.2095-5561.2025.06.06

Abstract：Objective To construct a nomogram model for predicting the risk of post-traumatic chronic disorders of consciousness(pDoC)in patients with severe craniocerebral injury(SCI).Methods A total of 168 patients with severe craniocerebral injury,including 87 males and 81 females,aged(48.2±3.3)years old,rangingfrom 35 to 60 years old,were admitted to the Second Affiliated Hospital of the Air Force Medical University between June 2020 and June 2023 were enrolled.The occurrence of pDoC was assessed.Logistic regression analysis was used to identify influencing factors for pDoC development in these patients.The predictive performance of these factors was evaluated using receiver operating characteristic(ROC)curve analysis.A nomogram prediction model was constructed based on the identified factors.The predictive accuracy of the nomogram model was validated using ROC curves and calibration curves.Results Among the 168 patients with severe craniocerebral injury,121(72.0%)developed pDoC,while 47(28.0%)had normal postoperative consciousness.Logistic regression analysis identified older age,≥2 injury sites,admission GCS score of 3 to 5,presence of neurological complications,occurrence of electrolyte disturbances,and underlying diseases as independent risk factors for pDoC following severe craniocerebral injury(P<0.05).ROC curve analysis demonstrated that age,number of injury sites,admission GCS score,neurological complications,electrolyte disturbances,and underlying diseases had good predictive value for pDoC occurrence in severe craniocerebral injury patients.The nomogram model underwent bootstrap resampling 1000 times to generate a calibration curve,indicating good model discrimination(C-index=0.929).The nomogram model of ROC curve was drawn to evaluate the occurrence of pDoC in patients with severe craniocerebral injury,and it had a high predictive accuracy for the occurrence of pDoC in patients with severe craniocerebral injury(area under curve=0.929,95%CI:0.883 to 0.975).Conclusion Independent risk factors for post-traumatic chronic disorders of consciousness in severe craniocerebral injury patients are older age,≥2 injury sites,admission GCS score of 3 to 5,presence of neurological complications,occurrence of electrolyte disturbances,and underlying diseases.The constructed nomogram model has high reference value and predictive efficacy.