Risk Factors Analysis and Predictive Model Efficacy Study of Myocardial Ischemia-reperfusion Injury in Patients with Coronary Heart Disease
Objective To analyze the risk factors of myocardial ischemia-reperfusion injury(MIRI)in patients with coronary heart disease,establish a predictive model and evaluate its effectiveness.Methods A total of 80 patients with coronary heart disease who received thrombolytic therapy or percutaneous coronary intervention(PCI)treatment at The Southeast General Hospital of Dongguan from October 2021 to September 2022 were selected as the subjects.They were divided into a control group(45 cases without MIRI)and an observation group(35 cases occurred MIRI)based on whether the patients occurred MIRI after treatment.The clinical data of all patients were reviewed,the possible influencing factors of MIRI in patients with coronary heart disease were statistically analyzed,the prediction model of MIRI nomogram was established,and the prediction efficiency of the model was evaluated.Results Among 80 patients with coronary heart disease,35 cases(43.75%)occurred MIRI.The results of multiple logistic regression showed that the time from onset to surgery,left ventricular ejection fraction(LVEF),neutrophil to lymphocyte ratio(NLR),platelet count to lymphocyte count ratio(PLR),troponin T(TNT),and brain natriuretic peptide(BNP)were independent risk factors for MIRI in patients with coronary heart disease(P<0.05);The calibration curve slope of the column chart prediction model constructed in this study was relatively high.The results of the Hosmo-Lemeshau(H-L)goodness of fit test showed that the model fits well with a chi square value of 1.334 and a p-value of 0.323;The receiver operating characteristic(ROC)curve results showed that the area under the curve was 0.817,95%CI(0.759,0.871).Conclusion The time from onset to surgery,LVEF,NLR,PLR,TNT,and BNP are the risk factors for MIRI in patients with coronary heart disease.The predictive model constructed based on these factors in this study has a high degree of fit and predictive efficacy.
Coronary heart diseaseMyocardial ischemia-reperfusion injuryNomogram prediction model
万方数据
维普
