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目的:探讨脓毒症心肌病患者的危险因素并基于左心室整体纵轴应变（LV GLS）建立其预测模型。方法:将2019年9月至2021年1月苏北人民医院重症医学科收治的脓毒症且排除既往心功能障碍患者纳入研究。共纳入124例患者，其中男86例，女38例，年龄（66.3±12.8）岁。患者在72 h内行LV GLS测量，将患者分为脓毒症心肌病组（LV GLS>-17%，n n=51）和心功能正常组（LV GLS≤-17%，n n=73）。收集两组患者临床资料，进行单因素分析。单因素分析有差异变量，绘制受试者工作特征（ROC）曲线，分析单个因素预测价值和寻找预测脓毒症心肌病最佳截断值，并根据最佳截断值将连续性变量转换为二分类变量后进行脓毒症心肌病的多因素logistic回归分析筛选危险因素，建立脓毒症心肌病预测模型。通过ROC曲线和Bootstrap自抽样法评估模型预测价值，并绘制列线图。n 结果:脓毒症心肌病组超敏肌钙蛋白I（Hs-TnI）、降钙素原（PCT）、氨基末端脑钠肽前体（NT-proBNP）、血乳酸（Lac）、血管活性药物强度（VDI）、序贯器官衰竭评分（SOFA）高于心功能正常组（均n P<0.05）。多因素logistic回归分析显示：Hs-TnI≥0.131 μg/L（n OR=6.71，95%n CI：2.67~16.88，n P-17%) and a normal cardiac function group (LV GLS≤-17%). Clinical data from two groups of patients were collected for univariate analysis. The receiver operating characteristic (ROC) curves of the factors that were statistically different were drawn for exploring the diagnostic and cut-off values. The continuous variable was converted to a dichotomous variable according to the cut-off value. Multivariate logistic regression analysis of sepsis cardiomyopathy was performed to screen the risk factors and create a predictive model. The predictive model was evaluated by ROC curve analysis and the Bootstrap method and shown as a nomograph.Results:Patients in the sepsis cardiomyopathy group had higher levels of high sensitive troponin I (Hs-TnI), procalcitonin (PCT), lactate (Lac), N-terminal pro-brain atriuretic peptide (NT-proBNP), vasopressor dosing intensity (VDI) and sequential organ failure assessment (SOFA) when compared to those in the normal cardiac function group (all n P<0.05). The multivariate logistic regression analysis showed that Hs-TnI≥0.131 μg/L (n OR=6.71, 95%n CI:2.67-16.88, n P<0.001), PCT≥40 μg/L (n OR=3.08, 95%n CI:1.10-8.59, n P=0.032), Lac≥4.2 mmol/L (n OR=2.80, 95%n CI:1.02-7.69, n P=0.045), NT-proBNP≥3 270 ng/L (n OR=2.67, 95%n CI:1.06-6.74, n P=0.038) were independent risk factors for septic myocardiopathy. The area under the ROC curve of the predictive model based on the four indexes up-mentioned was 0.838 (95%n CI:0.766-0.910), and the C-index was 0.822 (95%n CI:0.750-0.894) which indicated the utility of the nomogram. The model had a good predictive ability, accuracy and discrimination.n Conclusions:Hs-TnI≥0.131 μg/L, PCT≥40 μg/L, Lac≥4.2 mmol/L and NT-proBNP≥3 270 ng/L are independent risk factors for septic myocardiopathy, and the septic cardiomyopathy predictive model constructed based on these factors has a good diagnostic performance.