• Tian Xie, Xiangda Zhang, Bin Cheng, Min Huang, Shikai Wang, and Sihua Ou.
• Department of Hepatobiliary and Pancreatic Surgery, Union Shenzhen Hospital, Huazhong University of Science and Technology, Shenzhen 518000, Guangdong, China.
• Zhonghua Wei Zhong Bing Ji Jiu Yi Xue. 2020 Oct 1; 32 (10): 1208-1212.

ObjectiveTo establish a prognostic Nomogram model for predicting the risk of early death in polytrauma patients.MethodsData extracted from a polytrauma study on Dryad, an open access database, was selected for secondary analysis. Patients from 18 to 65 years old with polytrauma in the original data were included. All patients with missing variables, such as blood lactic acid (Lac), Glasgow coma score (GCS) and injury severity score (ISS) at admission, were excluded. The differences of gender, age, Lac, ISS and GCS scores between the patients who died within 72 hours and those who survived were analyzed. The risk factors for 72-hour death were analyzed by Logistic regression, and the Nomogram prediction model was established using R software. The receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of the model, and the Bootstrap method was used for internal verification by repeating sample for 1 000 times. Decision curve (DCA) was applied to analyze the clinical practical value of the model.ResultsA total of 2 315 polytrauma patients were included. Logistic regression analysis showed that Lac, GCS score and age > 55 years old were the risk factors for early death in polytrauma patients [Lac: odds ratio (OR) = 1.36, 95% confidence interval (95%CI) was 1.29-1.42, P < 0.001; GCS score: OR = 0.76, 95%CI was 0.73-0.79, P < 0.001; age > 55 years old: OR = 1.92, 95%CI was 1.37-2.66, P < 0.001]. The prediction model was established by using the above risk factors and displayed by Nomogram. ROC curve analysis showed that the area under the ROC curve (AUC) of Nomogram model to predict the risk of death within 72 hours was 0.858, and the predictive ability of Nomogram model was significantly higher than that of Lac (AUC = 0.743), GCS score (AUC = 0.774) and ISS score (AUC = 0.699), all P < 0.05. The model calibration chart showed that the predicting probability was consistent with the actual occurrence probability, and the DCA showed that Nomogram model presented excellent clinical value in predicting the 72-hour death risk for polytrauma patients.ConclusionsThe prognostic Nomogram model presents significantly predictive value for the risk of death within 72 hours in polytrauma patients. Prognostic Nomogram model could offer individualized, visualized and graphical prediction pattern, and provide physicians with practical diagnostic tool for triage system and management of polytrauma according to precision medicine.

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