Clinical Characteristics And Prognostic Analysis Of Patients Over 80 Years Old With Acute Non-ST Segment Elevation Myocardial Infarction

Objective: The purpose of this study was to analyze the incidence of cardiovascular adverse events in hospitalized NSTEMI patients through retrospective clinical case analysis,and to evaluate the clinical characteristics of older patients(≥80 years old)with NSTEMI and the risk factors affecting the prognosis in hospital.A risk prediction model for NSTEMI patients was constructed based on independent risk factors.Method: In this study,case data of hospitalized patients with NSTEMI diagnosed in the Department of Cardiovascular Medicine of Ningxia Medical University General Hospital from January 2015 to August 2021 were collected.After the inclusion and exclusion criteria,426 eligible patients with complete case data were enrolled,and 127 patients were divided into groups ≥80 years old according to the age of patients.There were 299 cases in ≥60 years old and < 80 years old.NSTEMI patients aged ≥80 years old were selected as the case group,and NSTEMI patients aged ≥60 years old and < 80 years old were selected as the control group.Clinical data related to NSTEMI patients in the two groups were collected and analyzed.At the same time,univariate logistic regression analysis was carried out on the case group.Factors with correlation after univariate logistic regression analysis were included in Lasso regression for further screening,and interaction between variables was excluded.Finally,two combinations of variables to be selected were obtained,and multivariate logistic regression analysis was carried out respectively.To investigate the independent risk factors for in-hospital end events in elderly NSTEMI patients,and establish a logistic regression risk prediction model for two in-hospital end events in elderly NSTEMI patients.The two risk prediction models were tested,and the optimal risk prediction model for NSTEMI patients was finally obtained.A nomogram was drawn to visualize the optimal model for clinical application.Results: 1.The results of this study showed that the incidence of in-hospital end-point events in elderly(≥80 years old)NSTEMI patients admitted to XXX Hospital from January 2015 to August 2021 was 37.01%.2.In comparison results between the two groups in this study: There were statistically significant differences in age,body mass index and BMI,systolic blood pressure,diastolic blood pressure,heart rate,hemoglobin,NT-pro BNP,hypersensitive CRP,D-D poly,killip grade ≥3,number of vascular lesions,choice of conservative drug therapy and PCI(P<0.05).3.After univariate logistic regression analysis,a total of 14 factors were correlated with the occurrence of in-hospital end events in NSTEMI patients(P<0.05),the 14 factors were :age,WBC,NT-ProBNP,TNI,MYO,CK,CK-MB,hypersensitive CRP,TG,D-D polymerization,left ventricular end-diastolic diameter,left ventricular end-systolic diameter,EF,abnormal segmenial wall motion,killip grade ≥3.4.Lasso regression analysis was carried out on 14 factors with correlation after univariate logistic regression analysis,and two variable combinations were selected.9variables included in variable combination 1 were killip grade ≥3,age,NT-ProBNP,TNI,MYO,CK,hypersensitive CRP,TG and EF.The four variables included in variable combination 2 are killip grade ≥3,age,TG and EF value.5.Multivariate logistic regression analysis after Lasso regression analysis showed that killip grade ≥3,age,TG,and EF were independent correlated factors for in-hospital end events in older NSTEMI patients(P<0.05).killip grade ≥3,age and TG were risk factors(OR>1),and EF was a protective factor(OR<1).6.After the Lasso regression analysis,two variable combinations were selected and two risk prediction models were constructed.Internal evaluation and internal verification were carried out on the two models,and the results showed that model 1 was the optimal logistic regression risk prediction model.This model can preliminarily predict the risk of in-hospital end events in older NSTEMI patients with good differentiation and consistency.Conclusions: 1.Killip grade ≥3,age,TG,and EF values were independently correlated with the occurrence of in-hospital end events in elderly NSTEMI patients.2.In this study,the optimal risk prediction model established by Lasso regression analysis has good discrimination and consistency,and can preliminarily predict the risk of in-hospital endpoint events in elderly NSTEMI patients.It has certain reference value for clinical diagnosis and prognosis of elderly NSTEMI patients.