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目的:识别短期预后差的脓毒症患者，尽早进行干预，减少病死率。方法:收集2013年6月1日至2021年3月30日东阳市人民医院收治的900例脓毒血症（入院后诊断为脓毒症）患者的资料。收集患者的年龄、性别，及脓毒症患者入院后24 h内第一次的降钙素原、B型脑钠肽前体等指标，及入院当时平均动脉压、心率等指标。Logistic回归分析出与脓毒症患者30 d（短期预后）内死亡相关的独立危险因素，并予逐步回归分析进行变量的二次筛选，最后将有意义的变量建立诺模图，用试者工作特征（receiver operating characteristic，ROC）曲线下面积（AUC）评估模型的判别能力，用GiViTI校准图评估模型的校准度，用递减曲线分析（decline curve analysis，DCA）判断评估预测模型的临床有效性。并应用bootstrap法进行验证。结果:逐步回归分析显示：B型脑钠肽前体、乳酸、白蛋白、氧合指数、平均动脉压、红细胞压积、入院时心率对结果有统计学意义（ P<0.05），建模后AUC为0.846，校准图的 P值为0.886，Brier scaled：0.092，calibration slope：1.000，R2：0.385，DCA曲线在两条极端曲线之上。bootstrap法验证的AUC为0.854，校准图的 P值为0.944，Brier scaled：0.090，calibration slope：1.000，R2：0.389，DCA曲线在两条极端曲线之上。 结论:B型脑钠肽前体、乳酸、白蛋白、氧合指数、平均动脉压、红细胞压积、入院时心率为脓毒症患者30 d死亡的独立危险因素，由上述指标建立的模型在评估脓毒症患者短期预后方面有较好的意义。

Objective:To predict the sepsis patients with bad outcomes in short term and help clinical physicians to take intervention measures to reduce the mortality.Methods:A total of 900 patients with sepsis who were hospitalized in the Dongyang Peoples’ Hospital between 1st Jan 2013 and 30th Mar 2021 had been involved in this study. Information including gender, age and examination results of first time within 24 hours following hospitalization were collected. Independent risk factors of death in 30 days were screened by logistic regression analysis and further confirmed by stepwise regression analysis. Based on the screened variables, nomogram prediction model was established. Finally, the prediction model was evaluated for its prediction power by the area under the curve of receiver operating characteristic (AUC), calibration accuracy by GiViTI calibration curve and clinical effectiveness by decline curve analysis (DCA). The established prediction model was validated by using bootstrap assay.Results:Stepwise regression analysis results showed that B-type natriuretic peptide, lactic acid, albumin, oxygenation index, mean artery pressure, hematocrit and heart rate within 24 hours after hospitalization were significantly associated with death in 30 days among patients with sepsis. The AUC of prediction model was 0.846, with P of 0.886 in calibration curve, calibration slope of 1.0, R2 of 0.385, brier scaled value of 0.092 and DCA curve above the two extreme curves. In validation using bootstrap, the prediction model owned an AUC of 0.854, a P of 0.994 in calibration curve, a brier scaled value of 0.090, a calibration slope of 1.0 and a R2 of 0.389. Also, its DCA curve was above the two extreme curves. Conclusions:B-type natriuretic peptide, Lactic acid, albumin, oxygenation index, mean artery pressure, hematocrit and heart rate within 24 hours after hospitalization were independent risk factors of death in 30 days among patients with sepsis. The established prediction model in this study owned good prediction power of sepsis patients who owned high risk of death in 30 days.