| BackgroundAcute myocardial infarction(AMI)is the most serious cardiovascular disease.Acute total occlusion of coronary artery will cause myocardial ischemia and hypoxia,as well as a large number of cardiomyocytes necrosis and apoptosis,causing irreversible damage to cardiomyocytes.With the continuous development of novel drugs and percutaneous coronary intervention(PCI),revolutionary changes have taken place in the treatment and management of cardiovascular diseases,and the mortality has been significantly reduced.However,there is still a high risk of cardiovascular adverse events after PCI,especially in patients with AMI,mainly cardiac death in the early stage,and a gradual increase in the risk of long-term non-cardiac death.Long-term risk stratification for AMI patients is helpful to guide clinical management decisions,weigh post-AMI treatment strategies,and reduce the risk of cardiovascular adverse events.As a disease risk prediction tool integrating multiple risk factors,the nomogram model can improve the ability of individual clinical indicators to predict adverse events,provide a quantitative scoring system,and accurately identify high-risk patients.At present,the international scoring system for evaluating the prognosis of AMI is mainly GRACE and TIMI scoring system.However,TIMI scoring system is mainly suitable for patients after thrombolysis,and its predictive ability is obviously limited in the era of direct PCI.GRACE scoring system is more complex,which hinders its clinical application.Therefore,we urgently need to explore a simpler and more suitable scoring system for predicting the prognosis of Chinese patients with AMI.ObjectiveTo screen the independent risk factors that can predict the risk of main cardiovascular adverse events(MACE)and all-cause death after PCI in patients with AMI,as well as development and validation of a prognostic nomogram model after PCI in patients with AMI.MethodThe baseline characteristics,laboratory and imaging parameters and follow-up data of AMI patients in the department of cardiology,the first Affiliated Hospital of Zhengzhou University from June 2014 to January 2020 were collected retrospectively.A total of 450 patients were included according to the inclusion and exclusion criteria,and were randomly divided into two groups:development cohort(n=315)and validation cohort(n=135).In the development cohort,univariate and multivariate COX regression were used to screen the independent predictors of MACE and all-cause death after PCI in patients with AMI,which were included in the nomogram model.The R software was used to construct the MACE and all-cause death risk nomogram model.C index and calibration curve were used to evaluate the differentiation and calibration of the nomogram model in the development cohort and validation cohort.Result1.Multivariate COX regression analysis showed that NT-proBNP≥1800 or 3600 pg/ml,Gensini score≥90 and eGFR<90 ml/min/1.73m2 were independent predictors of MACE after PCI in patients with AMI(all P<0.05).A nomogram model of MACE in 3 and 5 years after PCI in patients with AMI was constructed based on the above three risk factors.The C index of MACE risk nomogram model in the development cohort and validation cohort was 0.712(0.688-0.736)and 0.774(0.739-0.809),respectively.The calibration curve showed that the fitting curves of MACE prediction and actual incidence at 3 and 5 years after PCI in patients with AMI were close to diagonal,showing good differentiation and calibration.2.According to the corresponding scores of NT-proBNP,Gensini and eGFR on the MACE risk nomogram model,the total MACE risk score of each patient was calculated.According to the median score,the patients were divided into low risk group(<55)and high risk group(>55).Kaplan-Meier survival curve showed that the risk of MACE events in the high risk group was significantly higher than that in the low risk group(P<0.001).3.Multivariate COX regression analysis showed that Age≥ 65 years,systolic blood pressure(SBP)<125mmHg,NT-proBNP>3600 pg/ml,fasting plasma glucose(FPG)≥126mg/dl and eGFR<90 ml/min/1.73m2 were independent predictors of all-cause death after PCI in patients with AMI(all P<0.05).A nomogram model of all-cause death at 3 and 5 years after PCI in patients with AMI was established based on the above five risk factors.The C index of the all-cause death risk nomogram model in the development cohort and validation cohort was 0.826(0.787-0.866)and 0.917(0.891-0.942),respectively.The calibration curve showed that the fitting curvesof predicted and actual incidence of all-cause death at 3 and 5 years after PCI in patients with AMI were close to diagonals,showing good differentiation and calibration.4.According to the corresponding scores of age,SBP,FPG,NT-proBNP and eGFR on the all-cause death risk nomogram model after PCI in patients with AMI,the total risk score of all-cause death of each patient was calculated.According to the median score,the patients were divided into low risk group(≤115)and high risk group(>115).Kaplan-Meier survival curve showed that the risk of all-cause death in the high risk group was significantly higher than that in the low risk group(P<0.001).Conclusion1.NT-proBNP>1800 or 3600 pg/ml,Gensini score>90 and eGFR<90 ml/min/1.73m2 are independent predictors of MACE risk after PCI in patients with AMI.2.Age≥65 years,SBP<125mmHg,NT-proBNP>3600 pg/ml,FPG≥126mg/dl and eGFR<90 ml/min/1.73m2 are independent risk factors for all-cause death after PCI in patients with AMI.3.The nomogram model based on NT-proBNP,Gensini score and eGFR has high accuracy in predicting the risk of MACE after PCI in patients with AMI,and the calculation is simple and convenient,so it has certain clinical application value.4.The nomogram model based on age,SBP,NT-proBNP,FPG and eGFR covers demographic characteristics,cardiac and renal function indicators and glucose metabolism indicators.It has high accuracy in predicting the risk of all-cause death after PCI in patients with AMI,and can screen high-risk groups in time,so it has high clinical application value. |
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