Objective: To investigate the correlation between left ventricular ejection fraction (LVEF) and age with changes in anterior descending CT coronary flow reserve fraction (CT-FFR) before and after transcatheter aortic valve implantation (TAVI), based on references and data summaries. Methods: Seventy-eight patients with severe aortic stenosis diagnosed and treated in the Department of Cardiovascular Medicine of the Affiliated Hospital of Qingdao University from March 2019 to October 2022 were selected to detect the CT coronary flow reserve fraction of the anterior descending branches of the patients before and after transcatheter aortic replacement, and according to the pre- and post-surgery CT coronary flow reserve fractions, patients were divided into the variable group (Group I), the large group (Group II), and unchanged group (Group III), to explore the effects of left ventricular ejection fraction and age on each group. Results: Compared to Group III, in Group I, LVEF mainly influenced CT-FFR to become smaller after TAVI and played a positive role;compared to Group III, age mainly influenced CT-FFR to become larger after TAVI and played a negative role. Conclusion: LVEF and age predict changes in anterior descending CT coronary flow reserve fraction after transcatheter aortic implantation.
目的探讨基于临床及影像特征多元Logistic回归模型在肺部新冠病毒Omicron变异株合并细菌感染诊断中的应用价值。方法回顾性收集新冠病毒Omicron变异株合并细菌感染者74例,为A组。同时段新冠病毒Omicron变异株感染者90例,为B组。通过单因素与多因素Logistic回归分析,分别构建临床特征、CT影像特征及联合诊断模型。采用受试者操作特征(receiver operating characteristic,ROC)曲线、校准曲线和决策曲线(decision curve analysis,DCA)评估各个模型的预测能力、校准能力和临床效能。采用DeLong检验比较不同模型之间曲线下面积(area under the curve,AUC)的差异。结果多因素Logistic回归显示,慢性阻塞性肺疾病(简称慢阻肺)、重症肺炎、实变影、胸腔积液4个自变量是独立预测因子。临床模型、CT影像模型及联合诊断模型AUC分别为0.893(95%CI:0.843~0.943)、0.838(95%CI:0.773~0.903)、0.948(95%CI:0.915~0.981)。临床与CT影像模型之间差异不具有统计学意义(Z=1.467,P=0.142)。联合诊断模型与临床、CT影像模型间差异均具有统计学意义(Z分别为3.236、4.293,P分别为0.001、<0.001)。校准曲线表明,联合诊断模型预测概率与实际概率之间的良好一致性。DCA示联合诊断模型的净收益最大。结论基于临床及影像学特征的构建的联合诊断模型诊断效能优异,可用于新型冠状病毒Omicron变异株合并细菌感染的诊断与鉴别。
