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目的:建立能够评估多发伤患者院内早期死亡风险的列线图预测模型。方法:对Dryad开放数据库中一项关于多发伤研究数据进行二次分析，纳入原数据中18～65岁的多发伤患者，剔除入院时血乳酸（Lac）、格拉斯哥昏迷评分（GCS）、损伤严重程度评分（ISS）和72 h内死亡等变量缺失的患者。分析72 h内死亡患者与存活患者性别、年龄及入院时Lac、ISS评分、GCS评分等各指标的差异，通过Logistic回归分析72 h死亡危险因素，并应用R语言软件将危险因素建立列线图预测模型；应用受试者工作特征曲线（ROC）评价该模型的预测能力，并通过自举法（Bootstrap法）重复抽样1 000次进行内部验证。使用决策曲线（DCA）分析预测模型的临床实用价值。结果:共纳入2 315例多发伤患者，Logistic回归分析显示，血Lac、GCS评分和年龄>55岁为多发伤患者72 h内死亡的危险因素〔Lac：优势比（n OR）n ＝1.36，95%可信区间（95%n CI）为1.29～1.42，n P<0.001；GCS评分：n OR＝0.76，95%n CI为0.73～0.79，n P55岁：n OR＝1.92，95%n CI为1.37～2.66，n P<0.001〕，使用上述危险因素建立预测模型并通过列线图展示。ROC曲线分析显示，列线图模型预测多发伤患者72 h内死亡风险的ROC曲线下面积（AUC）为0.858，预测能力显著高于血Lac（AUC＝0.743）、GCS评分（AUC＝0.774）单项危险因素和ISS评分（AUC＝0.699），均n P 55 years old were the risk factors for early death in polytrauma patients [Lac: odds ratio ( n OR) = 1.36, 95% confidence interval (95%n CI) was 1.29-1.42, n P < 0.001; GCS score: n OR = 0.76, 95%n CI was 0.73-0.79, n P 55 years old: n OR = 1.92, 95%n CI was 1.37-2.66, n 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 n 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.n Conclusions:The 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.