Circulating Biomarkers In STEMI And Prediction Of Prognosis And Adverse Events After Primary PC

Background:The main pathological types of culprit plaques among patients with acute myocardial infarction(AMI)include plaque rupture,plaque erosion,and calcified nodules.Optical coherence tomography(OCT)is the main method to distinguish culprit plaques in patients with AMI.However,there is still a lack of specific biomarkers combined with morphological characteristics of culprit plaques to predict prognosis among patients with AMI after primary percutaneous coronary intervention(PCI).Triglyceride glucose index(TyG)was a substitute for insulin resistance.This prospective study explored plaque morphology according to the underlying culprit lesion pathology(rupture versus erosion)in relation to the TyG index in patients with acute ST-elevated myocardial infarction(STEMI)who underwent primary PCI and OCT for culprit lesions to elucidate the effects of the TyG index and type of plaque on the incidence of major adverse cardiovascular events(MACEs).Methods:A total of 274 patients with STEMI aged≥18 years who underwent pre-intervention OCT imaging of culprit lesions between March 2017 and March 2019 were enrolled.The TyG index was calculated using the formula In[fasting TG(mg/dL)×fasting glucose(mg/dL)/2].Patients with plaque rupture(PR)and plaque erosion(PE)were divided into three groups across the TyG tertiles.MACEs were defined as a composite of all-cause death,myocardial infarction(MI)recurrence,and ischaemic stroke.Results:Fully adjusted Cox regression models indicated a significantly higher HR for MACEs in patients in the middle tertile of TyG than in those in the low tertile of TyG(hazard ratio[HR]=5.45;95%confidence interval[CI],1.10-27.09;P=0.038).However,being in the high tertile of TyG independently and significantly increased the risk of major bleeding events among patients with PE(HR,2.50;95%CI,1.115.65;P=0.028).The area under the receiver operating characteristic curve for predicting MACEs to evaluate the diagnostic value of the TyG index combined with the morphological characteristics of plaque after full adjustment was 0.881(Sensitivity=94.74%,Specificity=78.04%,cutoff level=0.73).Kaplan-Meier curves were generated for the cumulative incidence of MACEs and indicated that there were significant differences among the tertiles of TyG(p=0.030)mong patients with PR.Conclusion:Microstructural OCT features of culprit lesions in combination with the TyG index,a surrogate estimate of insulin resistance,can be used in clinical practice to support predict adverse events in patients with STEMI.Background:Proprotein Convertase subtilisin/Kexin Type 9(PCSK9)as a popular target of lipid-lowering drugs is an independent risk factor of coronary atherosclerosis in recent years.Serum pentraxin 3(PTX-3)is one of the acute inflammatory response proteins.The increase of PTX-3 is closely related to the instability of plaque and the occurrence and development of acute coronary syndrome which may be associated with the risk of major adverse cardiovascular events(MACEs).However,the prognostic value of the combination of the two indexes among different pathological types of culprite plaques is still unclear.Therefore,the aim of prospective study was to determine the prognostic value of combined measures of plasma PCSK9 and PTX3 according to the culprit-plaque morphology(plaque rupture versus plaque erosion)by optical coherence tomography(OCT)in relation to the in patients with acute ST-elevated myocardial infarction(STEMI)who underwent primary percutaneous coronary intervention(PCI).Methods:A total of 434 patients with STEMI aged>18 years who underwent pre-intervention OCT imaging of culprit lesions between March 2017 and March 2019 were enrolled.Finally,235 patients who meet the inclusion criteria were enrolled and the cohort was divided into 3 groups according to PCSK9 and PTX3 levels:group A:PCSK9<median and Pentraxin 3<median;group B:PCSK9 ≥median or Pentraxin 3≥median;group C:PCSK9≥median and Pentraxin 3≥median.MACEs were defined as a composite of all-cause death,myocardial infarction(MI)recurrence,and ischemic stroke,revascularization and heart failure.Results:1)During a median follow-up of 2.01 years,MACEs was higher in group C(23/31.9%)than in group B(16/17.6%)and group A(11/15.3%)(p=0.028).2)There was a correlation between PCSK9 and PTX3(correlation=0.302,p<0.003).3)In multivariable analysis adjusted for age,gender,risk factors,and serum indexes,being in group C remained independently associated with an increased risk of MACE(hazard ratio[HR]:2.90;p=0.010),and group B tended to have higher MACE(HR:1.76;p=0.172)compared with group A.4)Among patients with plaque erosion by OCT,group C was independently associated with an increased risk of MACE(HR:9.04;p=0.048)after fully adjustment.However,the significant association was absence among patients with plaque rupture.Conclusions:This study demonstrated the usefulness of combined measures of PCSK9 and PTX3 to enhance risk stratification in patients with STEMI especially among patients with plaque erosion.Patients with elevation of both PCSK9 and PTX3 had a markedly increased risk of MACE.Background:Cardiovascular disease has become the leading cause of mortality worldwide and a major global economic burden.Early primary percutaneous coronary intervention(PCI)has increased the survival rate.The identification of pretreatment risk factors is beneficial to reduce the incidence of cardiovascular disease in high-risk patients using multivariable prediction equations rather than single risk factors.The population with myocardial infarction(MI)undergoing primary PCI is growing,but validated models to guide their clinical management are lacking.This study aimed to develop and validate prognostic models to predict major adverse cardiovascular events(MACEs)in patients with MI undergoing primary PCI.Methods:Models were developed in 4151 patients with MI who underwent PPCI in Fuwai Hospital between January 2010 and June 2017,with a median follow-up of 698 days during which 544 MACEs occurred.Results:The predictors included in the models were age,a history of diabetes mellitus,atrial fibrillation,chronic kidney disease,coronary artery bypass grafting,the Killip classification,ejection fraction at admission,the high-sensitivity C-reactive protein level,the estimated glomerular filtration rate,the d-dimer level,multivessel lesions,and the culprit vessel.The models had good calibration and discrimination in the derivation and internal validation with C-indexes of 0.74 and 0.60,respectively,for predicting MACEs.The new prediction model and GRACE risk score model were compared using the receiver operating characteristic curve.The areas under the curve of the new prediction model and GRACE risk score model were 0.821 and 0.794,respectively(difference between areas=0.024<0.05;z statistic,1.718).Conclusions:In summary,we present risk prediction models for estimating the risk for MACEs on the basis of clinical parameters that can be implemented alongside further medical investigations to support therapeutic decision-making.