脓毒症心肌病发病率及相关危险因素分析

目的研究脓毒症心肌病（SCM）的发病率及其相关危险因素。 方法回顾性分析2019年1月至2021年4月期间入住陕西省人民医院ICU的228例脓毒症及脓毒性休克患者，根据是否出现SCM分为SCM组（42例）与非SCM组（186例）。对两组患者的临床资料进行比较，采用多因素Logistic回归模型分析SCM发病的相关危险因素。同时，绘制受试者工作特征（ROC）曲线评价各指标对SCM发生的预测价值。 结果SCM在脓毒症及脓毒性休克患者中的发病率为18.4%（42/228）；与非SCM组患者比较，SCM组患者的年龄更高（t = 5.309，P<0.001），冠状动脉粥样硬化性心脏病（CHD）、心房颤动、心力衰竭、慢性肾衰竭占比更高（χ² = 5.090，P = 0.024；χ² = 6.399，P = 0.011；χ² = 31.848，P<0.001；χ² = 3.979，P = 0.046），白细胞（WBC）、乳酸、肌酸激酶同工酶、高敏心肌肌钙蛋白T（hs-cTnT）及急性病生理学和长期健康评价（APACHE）Ⅱ评分均更高（t = 4.560，P <0.001；Z = 3.855，P<0.001；Z = 2.075，P = 0.038；Z = 5.513，P <0.001；Z = 5.913，P <0.001）。多因素Logistic回归分析显示，年龄比值比（OR）= 1.071，95%置信区间（CI）（1.006，1.139），P = 0.030]、CHDOR = 3.185，95%CI（1.201，8.447），P = 0.020]、心力衰竭OR = 3.028，95%CI（1.041，8.810），P = 0.042]、WBC OR = 1.095，95%CI（1.003，1.196），P = 0.042]、乳酸OR = 1.095，95%CI（1.014，1.183），P = 0.021]、hs-cTnTOR = 1.629，95%CI（1.098，2.418），P = 0.015]、APACHEⅡ评分OR = 1.092，95%CI（1.003，1.188），P = 0.043]为影响SCM发病的独立危险因素。ROC曲线分析显示，年龄曲线下面积（AUC）= 0.767，95%CI（0.694，0.840），P<0.001]、WBCAUC = 0.757，95%CI（0.689，0.824），P<0.001]、乳酸AUC = 0.690，95%CI（0.603，0.778），P<0.001]、hs-cTnTAUC = 0.772，95%CI（0.071，0.843），P< 0.001]及APACHEⅡ评分AUC = 0.792，95%CI（0.727，0.856），P<0.001]均对SCM的发生有一定预测价值。 结论SCM在脓毒症或脓毒性休克患者中发病率较高，年龄、CHD、心力衰竭、WBC、乳酸、hs-cTnT、APACHEⅡ评分均为脓毒症或脓毒性休克患者SCM发病的独立危险因素。

Analysis of incidence and related risk factors of septic cardiomyopathy

ObjectiveTo investigate the incidence and related risk factors of septic cardiomyopathy (SCM). MethodsA total of 228 patients with sepsis or septic shock admitted to ICU of Shaanxi Provincial People's Hospital from January 2019 to April 2021 were retrospectively analyzed in this study. All patients were divided into the SCM group (42 cases) and the non-SCM group (186 cases) according to the occurrence of SCM. The clinical indicators were recorded and compared between the two groups. The multivariate Logistic regression analysis was used to analyze the risk factors associated with the development of SCM. Meanwhile, the receiver operating characteristic (ROC) curve was drawn to evaluate the predictive value of each indicator on SCM occurrence. ResultsThe incidence of SCM in patients with sepsis or septic shock was 18.4% (42/228). In the SCM group, the patients were older (t = 5.309, P<0.001), the incidences of coronary atherosclerotic heart disease (CHD), atrial fibrillation, heart failure and chronic kidney failure were higher (χ² = 5.090, P = 0.024; χ² = 6.399, P = 0.011; χ² = 31.848, P< 0.001; χ² = 3.979, P = 0.046), and the levels of white blood cell (WBC), lactate, creatine kinase isoenzymes-MB, high-sensitivity cardiac troponin T (hs-cTnT) and acute physiology and chronic health evaluation (APACHE) Ⅱ score (t = 4.560, P<0.001; Z = 3.855, P<0.001; Z = 2.075, P = 0.038; Z = 5.513, P<0.001; Z = 5.913, P<0.001) were all much higher than those in the non-SCM group. The multivariate Logistic regression analysis showed that the age odds ratio (OR) = 1.071, 95% confidence interval (CI) (1.006, 1.139), P = 0.030], CHD OR = 3.185, 95%CI (1.201, 8.447), P = 0.020], heart failure OR = 3.028, 95%CI (1.041, 8.810), P = 0.042], WBC OR = 1.095, 95%CI (1.003, 1.196), P = 0.042], lactate OR = 1.095, 95%CI (1.014, 1.183), P = 0.021], hs-cTnT OR = 1.629, 95%CI (1.098, 2.418), P = 0.015], APACHEⅡ score OR = 1.092, 95%CI (1.003, 1.188), P = 0.043] were independent risk factors for the incidence of SCM. The ROC curve analysis showed that the age area under the curve (AUC) = 0.767, 95%CI (0.694, 0.840), P<0.001], WBC AUC = 0.757, 95%CI (0.689, 0.824), P<0.001], lactate AUC = 0.690, 95%CI (0.603, 0.778), P<0.001], hs-cTnT AUC = 0.772, 95%CI (0.071, 0.843), P<0.001] and APACHEⅡ score AUC = 0.792, 95%CI (0.727, 0.856), P<0.001] all had certain predictive values for SCM occurrence. ConclusionsThe incidence of SCM of patients with sepsis or septic shock is relatively high. Age, CHD, heart failure, WBC, lactate, hs-cTnT and APACHEⅡ score are independent risk factors of SCM occurrence.