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目的:探讨影响重症监护病房（ICU）脓毒症患者短期预后的危险因素，并评估其联合预测价值。方法:回顾性分析2018年1月至2019年8月江苏省中医院急诊ICU收治的104例脓毒症患者的临床资料。收集患者的性别、年龄、既往史、合并症等一般资料以及入院24 h内的序贯器官衰竭评分（SOFA）、平均动脉压（MAP）、血常规、肝肾功能、凝血指标和降钙素原（PCT）。根据患者28 d转归分为死亡组和存活组。分别采用单因素和多因素Logistic回归模型分析影响脓毒症预后的危险因素；绘制受试者工作特征曲线（ROC），评估相关指标对脓毒症预后的预测价值；选择可能与疾病严重程度有关的参数进行Pearson或Spearman相关分析，评价各参数与SOFA评分的相关性。结果:104例患者均纳入最终分析，其中存活组60例，死亡组44例，28 d病死率为42.3%。①单因素分析结果：死亡组急性肾损伤（AKI）发生率、SOFA评分、血肌酐（SCr）、D-二聚体、活化部分凝血活酶时间（APTT）、国际标准化比值（INR）和PCT显著高于存活组〔AKI发生率：70.5%（31/44）比36.7%（22/60），SOFA评分（分）：11.0（8.0，13.0）比8.0（6.2，10.0），SCr（μmol/L）：108.8（65.5，235.6）比75.1（55.1，109.5），D-二聚体（mg/L）：4.1（1.6，11.6）比2.1（1.2，4.3），APTT（s）：42.6（37.7，55.7）比40.3（35.9，44.7），INR：1.3（1.2，1.5）比1.2（1.1，1.4），PCT（μg/L）：3.1（0.4，39.9）比0.3（0.1，3.4），均n P<0.05〕。②多因素Logistic回归分析结果：考虑到各自变量间的交互影响，将所有单因素分析的指标纳入多因素Logistic回归模型，基于条件向后法进行多次多因素Logistic回归分析，SPSS软件自动筛选出年龄、SOFA评分、MAP、中性粒细胞计数（NEU）、淋巴细胞计数（LYM）和APTT 6个变量建立预测模型，分析结果显示，SOFA评分、NEU和LYM为脓毒症患者短期预后的独立危险因素〔SOFA评分：优势比（n OR）＝1.22，95%可信区间（95%n CI）为1.04～1.44，n P＝0.02；NEU：n OR＝1.14，95%n CI为1.03～1.26，n P＝0.01；LYM：n OR＝0.79，95%n CI为0.66～0.95，n P＝0.01〕。③ ROC曲线分析结果：上述6个变量预测模型具有SPSS软件默认的最佳拟合度，联合年龄〔ROC曲线下面积（AUC）＝0.60〕、SOFA评分（AUC＝0.71）、MAP（AUC＝0.53）、NEU（AUC＝0.59）、LYM（AUC＝0.54）和APTT（AUC＝0.61）进行预测具有较好的敏感度（79.5%）和特异度（65.0%），AUC最大（AUC＝0.75），高于单个变量的AUC值，提示多变量联合预测脓毒症短期结局的准确性更高。④相关性分析结果：NEU、D-二聚体、凝血酶原时间（PT）、APTT、INR和PCT与SOFA评分均呈显著正相关（n r值分别为0.26、0.28、0.21、0.22、0.10、0.38，均n P<0.05）。n 结论:SOFA评分、NEU和LYM是脓毒症患者短期预后的独立危险因素；年龄、SOFA评分、MAP、NEU、LYM和APTT 6个指标联合预测脓毒症短期预后的准确性优于单个变量，诊断价值更高；NEU、D-二聚体、PT、APTT、INR和PCT与SOFA评分有一定的相关性。“,”Objective:To explore the risk factors influencing the short-term mortality of patients with sepsis in intensive care unit (ICU) and the combined value of predicting prognosis.Methods:A retrospective analysis was performed on 104 patients with sepsis admitted to emergency ICU of Jiangsu Provincial Hospital of Traditional Chinese Medicine from January 2018 to August 2019. Multiple general information containing gender, age, past history as well as complications and sequential organ failure assessment (SOFA) score, mean arterial pressure (MAP), blood routine examination, hepatic and renal function, coagulation indicators and procalcitonin (PCT) were collected within 24 hours of admission. Patients were divided into death group and survival group according to the 28-day outcome. Univariate and multivariate Logistic regression analysis were used to find the effective factors influencing the prognosis of sepsis. Receiver operating characteristic (ROC) curve was drawn to evaluate the value of related indexes in predicting the prognosis of sepsis. Correlation between parameters that might be relevant to disease severity and SOFA score was evaluated by Pearson or Spearman correlation analysis.Results:104 patients were enrolled for final analysis, of whom 60 patients survived, while the others died with a 28-day mortality of 42.3%. ① Univariate analysis results: the incidence of acute kidney injury (AKI), SOFA score, serum creatinine (SCr), D-dimer, activated partial thromboplastin time (APTT), international normalized ratio (INR) and PCT in the death group were significantly higher than those in the survival group [incidence of AKI: 70.5% (31/44) vs. 36.7% (22/60), SOFA score: 11.0 (8.0, 13.0) vs. 8.0 (6.2, 10.0), SCr (μmol/L): 108.8 (65.5, 235.6) vs. 75.1 (55.1, 109.5), D-dimer (mg/L): 4.1 (1.6, 11.6) vs. 2.1 (1.2, 4.3), APTT (s): 42.6 (37.7, 55.7) vs. 40.3 (35.9, 44.7), INR: 1.3 (1.2, 1.5) vs. 1.2 (1.1, 1.4), PCT (μg/L): 3.1 (0.4, 39.9) vs. 0.3 (0.1, 3.4), alln P < 0.05]. ② Multivariate Logistic regression analysis results: all indicators of univariate analysis were included in the multivariate Logistic regression model considering interaction between each variable. Multivariate Logistic regression analysis was repeated based on conditional backward method. Age, SOFA score, MAP, neutrophil (NEU), lymphocyte (LYM) and APTT were automatically selected by SPSS software to build the predicting model. Analysis results showed that SOFA score, NEU and LYM were independent risk factors for the short-term prognosis of sepsis [SOFA score: odds ratio ( n OR) = 1.22, 95% confidence interval (95%n CI) was 1.04-1.44, n P = 0.02; NEU: n OR = 1.14, 95%n CI was 1.03-1.26, n P = 0.01; LYM: n OR = 0.79, 95%n CI was 0.66-0.95, n P = 0.01]. ③ ROC curve analysis results: the above six-variable prediction model had the optimal fitting degree defaulted by SPSS. ROC curve showed that the combination of age [area under ROC curve (AUC) = 0.60], SOFA score (AUC = 0.71), MAP (AUC = 0.53), NEU (AUC = 0.59), LYM (AUC = 0.54) and APTT (AUC = 0.61) had better sensitivity (79.5%) and specificity (65.0%) as well as the maximal AUC (AUC = 0.75), which suggested that combined prediction had higher diagnostic value in predicting the short-term prognosis of sepsis.④ Correlation analysis showed that NEU, D-dimer, prothrombin time (PT), APTT, INR and PCT were positively correlated with SOFA score (n r values were 0.26, 0.28, 0.21, 0.22, 0.10, 0.38, respectively, all n P < 0.05).n Conclusions:SOFA score, NEU and LYM were independent risk factors for the short-term prognosis of sepsis. The combination of age, SOFA score, MAP, NEU, LYM and APTT were more accurate than any single factor in predicting the short-term prognosis of sepsis and had higher diagnostic value. NEU, D-dimer, PT, APTT, INR and PCT were correlated with SOFA score.