基于超声心动图参数联合血清MFG-E8构建脓毒性心肌病病人预后模型

李雅琳; 李东风; 李昊; 付玉茹; 王园园

基于超声心动图参数联合血清MFG-E8构建脓毒性心肌病病人预后模型

Construction of the prognosis model of patients with septic cardiomyopathy based on echocardiographic parameters combined with serum MFG-E8

摘要

摘要:
目的： 基于超声心动图参数联合血清乳脂肪球表皮生长因子８（MFG–E8）构建脓毒性心肌病病人预后的预测模型。
方法： 回顾性分析109例脓毒性心肌病病人的临床资料，根据病人28 d存活情况分为死亡组（n = 52）和存活组（n = 57）。2组病人入院时均进行超声心动图检查，对比2组临床资料、超声心动图参数及血清MFG–E8水平，分析脓毒性心肌病病人死亡的影响因素，构建并验证脓毒性心肌病病人发生死亡的列线图预测模型。
结果： 死亡组急性生理学与慢性健康状况Ⅱ评分、N末端脑钠肽前体、血乳酸、肌酸激酶同工酶、序贯器官衰竭评分、使用血管活性药物比例均高于存活组（P ＜ 0.05），左心室射血分数（LVEF）、右心室收缩期三尖瓣环运动速度（RV–Sm）、二尖瓣环舒张早期运动速度（e′）、血清MFG–E8水平均低于存活组（P ＜ 0.05）；logistic回归分析显示，LVEF、RV–Sm、e′、血清MFG–E8均为脓毒性心肌病病人发生死亡的保护因素（P ＜ 0.05）。列线图模型预测脓毒性心肌病病人发生死亡的灵敏度为90.38%，特异度为94.74%，AUC为0.911。
结论： LVEF、RV–Sm、e′、血清MFG–E8与脓毒性心肌病病人死亡风险关系密切，基于LVEF、RV–Sm、e′与血清MFG–E8构建的列线图预测模型有助于早期甄别脓毒性心肌病病人发生死亡的风险。

Abstract:
Objective To construct a predictive model for the prognosis of patients with septic cardiomyopathy based on echocardiographic parameters combined with serum milk fat globule epidermal growth factor 8 (MFG-E8).
Methods The clinical data of 109 patients with septic cardiomyopathy were retrospectively analyzed. According to the 28-day survival status of the patients, they were divided into the death group (n = 52) and survival group (n = 57). Echocardiography was performed on two groups on admission. The clinical data, echocardiographic parameters and serum MFG-E8 levels between two groups were compared to analyze the influencing factors of death in patients with septic cardiomyopathy, and a nomogram prediction model for death in patients with septic cardiomyopathy was constructed and verified.
Results The scores of Acute Physiology and Chronic Health Status II, N-terminal pro-brain natriuretic peptide, blood lactic acid, creatine kinase isoenzyme, sequential organ failure score and proportion of vasoactive drug use in the death group were all higher than those in survival group (P ＜ 0.05). The left ventricular ejection fraction (LVEF), right ventricular systolic tricuspid annulus velocity (RV-Sm), early diastolic mitral annulus velocit (e′) and serum MFG-E8 level in the death group were all lower than those in survival group (P ＜ 0.05). The results of logistic regression analysis showed that the LVEF, RV-Sm, e′ and serum MFG-E8 were the protective factors of death in patients with septic cardiomyopathy (P ＜ 0.05). The sensitivity of the nomogram model in predicting death in patients with septic cardiomyopathy was 90.38%, the specificity was 94.74%, and the AUC was 0.911.
Conclusions LVEF, RV-Sm, e′ and serum MFG-E8 are closely related to the risk of death in patients with septic cardiomyopathy. The nomogram prediction model constructed based on LVEF, RV-Sm, e′ and serum MFG-E8 is helpful for early identification of the risk of death in patients with septic cardiomyopathy.
Conclusions The LVEF、RV-Sm, e′ and serum MFG-E8 are closely related to the risk of death in patients with septic cardiomyopathy. The nomogram prediction model constructed based on LVEF, RV-Sm, e′ and serum MFG-E8 is helpful for early identification of the risk of death in patients with septic cardiomyopathy.

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