Predictive value of right ventricular features on three-dimensional echocardiography for heart failure after PCI in patients with inferior wall myocardial infarction
Aim To investigate the predictive value of right ventricular features on three-dimensional echocardio-graphy for heart failure(HF)after percutaneous coronary intervention(PCI)in patients with inferior wall myocardial in-farction(INFMI).Methods 261 patients with INFMI from October 2018 to October 2021 were included.Patients were divided into heart failure group(n=42)and no heart failure group(n=219)based on one-year follow-up records af-ter PCI.Clinical data and echocardiographic characteristics of the two groups were compared.LASSO-Logistic regression was used to screen the independent influencing factors for the occurrence of postoperative HF.A column-line diagram model was constructed and validated.Results After screening,the LASSO model at the optimal λ value in-corporated free wall mid-segment and global longitudinal strain,inflow tract end-diastolic volume and ejection fraction,and body end-diastolic volume and ejection fraction in INFMI patients.Higher predictive value for HF was found in lower postoperative body ejection fraction(cutoff value 43.27％),lower inflow tract ejection fraction(cutoff value 51.49％),and higher global longitudinal strain(cutoff value-13.52％).Ultrasound indices combined with age,Killip classification,and N-terminal pro-brain natriuretic peptide(NT-proBNP)were used to construct a columnar graphical model.The model was highly discriminative,with a consistency index of 0.981(95％CI:0.872～0.997).The model predicted values fitted well with the actual values.Conclusion Right ventricular global longitudinal strain,inflow tract ejection fraction,body ejection fraction,age,Killip classification,and NT-proBNP in patients with INFMI have a high predictive value for the risk of HF one year after PCI.The jointly constructed prediction model can be used as a clinical decision-making tool.
万方数据
维普
