The effect of fasting plasma glucose on in-hospital mortality after acute myocardial infarction in patients with and without diabetes:findings from a prospective,nationwide,and multicenter registry

OBJECTIVES To evaluate the predictive value of fasting plasma glucose(FPG)for in-hospital mortality in patients with acute myocardial infarction(AMI)with different glucose metabolism status.METHODS We selected 5,308 participants with AMI from the prospective,nationwide,multicenter CAMI registry,of which 2,081 were diabetic and 3,227 were nondiabetic.Patients were divided into high FPG and low FPG groups according to the optim-al cutoff values of FPG to predict in-hospital mortality for diabetic and nondiabetic cohorts,respectively.The primary endpoint was in-hospital mortality.RESULTS Overall,94 diabetic patients(4.5%)and 131 nondiabetic patients(4.1%)died during hospitalization,and the optimal FPG thresholds for predicting in-hospital death of the two cohorts were 13.2 mmol/L and 6.4 mmol/L,respectively.Compared with individuals who had low FPG,those with high FPG were significantly associated with higher in-hospital mortality in diabet-ic cohort(10.1%vs.2.8%;odds ratio[OR]=3.862,95%confidence interval[CI]:2.542-5.869)and nondiabetic cohort(7.4%vs.1.7%;HR=4.542,95%CI:3.041-6.782).After adjusting the potential confounders,this significant association was not changed.Further-more,FPG as a continuous variable was positively associated with in-hospital mortality in single-variable and multivariable models regardless of diabetic status.Adding FPG to the original model showed a significant improvement in C-statistic and net reclassification in diabetic and nondiabetic cohorts.CONCLUSIONS This large-scale registry indicated that there is a strong positive association between FPG and in-hospital mor-tality in AMI patients with and without diabetes.FPG might be useful to stratify patients with AMI.

Development and validation of a model integrating clinical and coronary lesion-based functional assessment for longterm risk prediction in PCI patients

OBJECTIVES To establish a scoring system combining the ACEF score and the quantitative blood flow ratio(QFR) to improve the long-term risk prediction of patients undergoing percutaneous coronary intervention(PCI).METHODS In this population-based cohort study, a total of 46 features, including patient clinical and coronary lesion characteristics, were assessed for analysis through machine learning models. The ACEF-QFR scoring system was developed using 1263consecutive cases of CAD patients after PCI in PANDA Ⅲ trial database. The newly developed score was then validated on the other remaining 542 patients in the cohort.RESULTS In both the Random Forest Model and the Deep Surv Model, age, renal function(creatinine), cardiac function(LVEF)and post-PCI coronary physiological index(QFR) were identified and confirmed to be significant predictive factors for 2-year adverse cardiac events. The ACEF-QFR score was constructed based on the developmental dataset and computed as age(years)/EF(%) + 1(if creatinine ≥ 2.0 mg/d L) + 1(if post-PCI QFR ≤ 0.92). The performance of the ACEF-QFR scoring system was preliminarily evaluated in the developmental dataset, and then further explored in the validation dataset. The ACEF-QFR score showed superior discrimination(C-statistic = 0.651;95% CI: 0.611-0.691, P < 0.05 versus post-PCI physiological index and other commonly used risk scores) and excellent calibration(Hosmer–Lemeshow χ^(2)= 7.070;P = 0.529) for predicting 2-year patient-oriented composite endpoint(POCE). The good prognostic value of the ACEF-QFR score was further validated by multivariable Cox regression and Kaplan–Meier analysis(adjusted HR = 1.89;95% CI: 1.18–3.04;log-rank P < 0.01) after stratified the patients into high-risk group and low-risk group.CONCLUSIONS An improved scoring system combining clinical and coronary lesion-based functional variables(ACEF-QFR)was developed, and its ability for prognostic prediction in patients with PCI was further validated to be significantly better than the post-PCI physiological index and other commonly used risk scores.

Triglyceride glucose index predicts in-hospital mortality in patients with ST-segment elevation myocardial infarction who underwent primary angiography

OBJECTIVES To assess the correlation between triglyceride glucose(TyG)index and in-hospital mortality in patients with ST-segment elevation myocardial infarction(STEMI).METHODS A total of 2190 patients with STEMI who underwent primary angiography within 12 h from symptom onset were selected from the prospective,nationwide,multicenter CAMI registry.TyG index was calculated with the formula:Ln[fasting triglycerides(mmol/L)×fasting glucose(mmol/L)/2].Patients were divided into three groups according to the tertiles of TyG index.The primary endpoint was in-hospital mortality.RESULTS Overall,46 patients died during hospitalization,in-hospital mortality was 1.5%,2.2%,2.6%for tertile 1,tertile 2,and tertile 3,respectively.However,TyG index was not significantly correlated with in-hospital mortality in single-variable logistic regression analysis.Nonetheless,after adjusting for age and sex,TyG index was significantly associated with higher mortality when regarded as a continuous variable(adjusted OR=1.75,95%CI:1.16-2.63)or categorical variable(tertile 3 vs.tertile 1:adjus-ted OR=2.50,95%CI:1.14-5.49).Furthermore,TyG index,either as a continuous variable(adjusted OR=2.54,95%CI:1.42-4.54)or categorical variable(tertile 3 vs.tertile 1:adjusted OR=3.57,95%CI:1.24-10.29),was an independent predictor of in-hospital mortality after adjusting for multiple confounders in multivariable logistic regression analysis.In subgroup analysis,the pro-gnostic effect of high TyG index was more significant in patients with body mass index<18.5 kg/m2(P interaction=0.006).CONCLUSIONS This study showed that TyG index was positively correlated with in-hospital mortality in STEMI patients who underwent primary angiography,especially in underweight patients.