Clinical Variables Additionally Improved The Performance Of The Catlet(?)Angiographic Scoring System In Terms Of Outcome Predictions For Patients With Acute Myocardial Infarction:a Follow-up Study Of 4.3-years

Objective:The present study aimed at assessing whether the clinical variables(CVs)additionally improved outcome predictions of the Coronary Artery Tree description and Lesion EvaluaTion(CatLet)angiographic scoring system for patients with acute myocardial infarction(AMI).Background:The CatLet score accommodating the variability in the coronary anatomy is a recently developed and comprehensive angiographic scoring system aiming to assist in risk-stratification of coronary artery disease(CAD)patients(http://www.catletscore.com).Our preliminary study demonstrated that the CatLet score better predicted the clinical outcomes in patients with AMI undergoing primary percutaneous intervention(PCI)than the SYNTAX score.Furthermore,the inter-and intra-observer reproducibility of the CatLet score for assessment of the stenotic lesions and their pertinent adverse characteristics was substantial or excellent.The current study was designed to evaluate whether the CVs(age,creatinine and left ventricular ejection fraction)additionally improved the performance of the CatLet score with respect to outcome predictions in AMI patients undergoing primary PCI.Methods:This study was a post hoc study of the validation trial of the CatLet angiographic scoring system.The CatLet score was calculated retrospectively in consecutively enrolled 308 AMI patients.All patients were followed up for 4.3 years.The primary end point was major adverse cardiac or cerebrovascular events(MACCEs)and secondary endpoints were all-cause death and cardiac death events.Cox regression analysis was used to discover the correlations among the CatLet score,CVs and clinical outcomes.Discrimination was measured by Harrell's C index,net reclassification improvement(NRI)and integrated discrimination improvement(IDI).Calibration was assessed by Hosmer-Lemeshow test and validation plots.Net benefit was assessed by decision curve analysis(DCA).Results:The CatLet score remained a significant predictor for outcome predictions at a median 4.3-year follow-up after adjusting for the three CVs.The model incorporating the CatLet score as well as these three CVs(CVs-adjusted model)performed better than the stand-alone CatLet model in terms of outcome predictions.Compared with the stand-alone CatLet model,Harrell's C index with the CVs-adjusted model significantly increased by 0.0967(P=0.002)in MACCE,by 0.1354(P<0.001)in all-cause death events,and by 0.1187(P=0.001)in cardiac death events.When reclassifying patients with 4.3-year MACCE from the stand-alone CatLet model into the CVs-adjusted model,out of the 244 subjects who remained free of MACCEs,101 were properly reclassified to a lower risk category and 42 were properly reclassified to a higher risk category(categories:?10%,10%to ?20%,20%to ?40%,>40%);out of the 64 subjects who developed MACCE events,26 were correctly reclassified to a higher risk category and 10 were reclassified to a lower risk category.The category-based overall NRI was 0.49(P<0.001)and the continuous overall NRI was 0.74(P<0.001).And IDI was 0.15(P<0.001).Hosmer-Lemeshow test showed a better calibration in MACCEs in the CVs-adjusted model(?2=4.14,P=0.8440)than in the stand-alone CatLet model(x2=5.06,P=0.7515).For all-cause death and cardiac death,similar results were obtained.DCA also showed that the net benefit of CVs-adjusted model was higher in terms of outcome predictions when compared with the stand-alone CatLet model.Conclusions:The three CVs(age,creatinine and left ventricular ejection fraction)additionally improved outcome predictions of the CatLet score in AMI patients undergoing primary PCI.(Registry Number:ChiCTR-POC-17013536)...