Aims/Introduction The predictive value of admission hyperglycemia in the long‐term prognosis of acute myocardial infarction patients is still controversial. We aimed to investigate this value based on the diabetes status. Materials and Methods We carried out a multicenter, retrospective study of 1,288 acute myocardial infarction patients enrolled in 11 hospitals between March 2014 and June 2019 in Chengdu, China. The patients were classified into those with diabetes and those without diabetes, each was further divided into: hyperglycemia and non‐hyperglycemia subgroups, according to the optimal cut‐off value of the blood glucose to predict all‐cause mortality during follow up. The end‐points were all‐cause death and major adverse cardiovascular and cerebrovascular events, including all‐cause death, non‐fatal myocardial infarction, vessel revascularization and non‐fatal stroke. Results In the follow‐up period of 15 months, we observed 210 (16.3%), 6 (0.5%), 57 (4.4%) and 34 (2.6%) cases of death, non‐fatal myocardial infarction, revascularization and non‐fatal stroke, respectively. The optimal cut‐off values of admission blood glucose for patients with diabetes and patients without diabetes to predict all‐cause mortality during follow up were 14.80 and 6.77 mmol/L, respectively. We divided patients with diabetes (n = 331) into hyperglycemia (n = 92) and non‐hyperglycemia (n = 239), and patients without diabetes (n = 897) into hyperglycemia (n = 425) and non‐hyperglycemia (n = 472). The cumulative rates of all‐cause death and major adverse cardiovascular and cerebrovascular events among the patients in each hyperglycemia group was higher than that in the corresponding non‐hyperglycemia group (P < 0.001). In patients without diabetes, admission hyperglycemia was an independent predictor of all‐cause mortality and major adverse cardiovascular and cerebrovascular events. Conclusion Admission hyperglycemia was an independent predictor for long‐term prognosis in acute myocardial infarction patients without diabetes.

Nutritional status is associated with prognosis in acute coronary syndrome (ACS) patients. Although the Global Registry of Acute Coronary Events (GRACE) risk score is regarded as a relevant risk predictor for the prognosis of ACS patients, nutritional variables are not included in the GRACE score. This study aimed to compare the prognostic ability of the Geriatric Nutritional Risk Index (GNRI) and Prognostic Nutritional Index (PNI) in predicting long-term all-cause death in ACS patients undergoing percutaneous coronary intervention (PCI) and to determine whether the GNRI or PNI could improve the predictive value of the GRACE score. A total of 799 patients with ACS who underwent PCI from May 2018 to December 2019 were included and regularly followed up. The performance of the PNI in predicting all-cause death was better than that of the GNRI [C-index, 0.677 vs. 0.638, p = 0.038]. The addition of the PNI significantly improved the predictive value of the GRACE score for all-cause death [increase in C-index from 0.722 to 0.740; IDI 0.006; NRI 0.095; p < 0.05]. The PNI was superior to the GNRI in predicting long-term all-cause death in ACS patients undergoing PCI. The addition of the PNI to the GRACE score could significantly improve the prediction of long-term all-cause death.

Background The residual SYNTAX score (rSS), a quantitative measure of angiographic completeness of revascularization after percutaneous coronary intervention (PCI), and the triglyceride–glucose index (TyG index), a reliable surrogate marker of insulin resistance, have been regarded as independent predictors of major adverse cardiac events (MACEs) after PCI. Whether a combination of the rSS and the TyG index improves the predictive ability for MACEs in patients with type 2 diabetes mellitus (T2DM) undergoing PCI remains unknown. Methods A total of 633 consecutive patients with T2DM who underwent PCI were included in the present analyses. Patients were stratified according to the optimal cutoff point value of the TyG index, or the rSS determined by receiver‑operating characteristic (ROC) curve analysis. The primary endpoint was the composite of MACEs, including all-cause death, nonfatal myocardial infarction, and unplanned repeat revascularization. Cumulative curves were calculated using the Kaplan–Meier method. Multivariate Cox regression was used to identify predictors of MACEs. The predictive value of the TyG index combined with the rSS was estimated by the area under the ROC curve, continuous net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Results During a median follow-up of 18.83 months, 99 patients developed MACEs, more frequently in the patients with a higher TyG index or rSS. Multivariate Cox hazards regression analysis revealed that both the TyG index and rSS were independent predictors of MACEs (hazard ratio 1.8004; 95% CI 1.2603–2.5718; P = 0.0012; 1.0423; 95% CI 1.0088–1.0769; P = 0.0129, respectively). Furthermore, Kaplan–Meier analysis demonstrated that both the TyG index and the rSS were significantly associated with an increased risk of MACEs (log-rank, all P < 0.01). The addition of the rSS and the TyG index to the baseline risk model had an incremental effect on the predictive value for MACE (increase in C-statistic value from 0.660 to 0.732; IDI 0.018; NRI 0.274; all P < 0.01). Conclusions The TyG index predicts intermediate-term MACE after PCI in patients with T2DM independent of known cardiovascular risk factors. Adjustment of the rSS by the TyG index further improves the predictive ability for MACEs in patients with T2DM undergoing PCI.