The role of triglyceride glucose index in predicting in-hospital adverse cardiovascular outcomes in patients with acute coronary syndrome

Previous studies have shown the association of triglyceride glucose (TyG) index with metabolic syndrome (MetS), cardiovascular disease (CVD) and long-term adverse cardiovascular outcomes. However, to best our knowledge, the relation between the TyG index and in-hospital adverse cardiovascular outcomes in acute coronary syndrome (ACS) has not yet been reported. Hence, in this study, we aimed to evaluate the role of the TyG index in predicting in-hospital adverse cardiovascular outcomes in ACS and to compare its performance with the Global Acute Coronary 3Department of XXX, University of XXX, XXX Training and Research Hospital, City, Country Events Register (GRACE) risk score. 170 patients diagnosed with ACS and underwent coronary angiography were analyzed retrospectively. The 4Department of XXX, Faculty of XXX, City, Country TyG index was calculated using the following formula: ln [fasting triglycerides (mg/dL)×fasting blood glucose (mg/dL)/2]. Receiver operating characteristics (ROC) curve analysis was used to evaluate the performance of the TyG index and GRACE risk score in predicting in-hospital adverse cardiovascular outcomes. A binary logistic regression model was applied to determine the independent predictors for in-hospital adverse cardiovascular outcomes. At the initial analysis, patients with adverse cardiovascular outcomes had higher TyG index and GRACE risk score (p=0.011, p<0.001). In ROC curve analysis, the GRACE score performed better in predicting in-hospital adverse cardiovascular outcomes compared to TyG index (AUC:0.716, p<0.001; AUC:0.588, p=0.054 respectively). In binary logistic regression analysis, left ventricular ejection fraction (LVEF), multi-vessel disease and GRACE risk score were independent predictors for in-hospital adverse cardiovascular outcomes (OR: 0.840, 95% CI: 0.791-0.891, p<0.001; OR: 3.581, 95% CI:1.382-9.282, p=0.009; OR= 1.017, 95% CI: 1.001-1.034, p=0.04 respectively). Our study findings revealed that the TyG index was scant in predicting in-hospital adverse cardiovascular outcomes compared to GRACE risk score. The independent predictors for in-hospital adverse cardiovascular outcomes were LVEF, multivessel disease and GRACE risk score.

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The new classification method in ACEF score is more useful in patients with acute coronary syndrome without ST segment elevation

Kardiologiia ◽

10.18087/cardio.2021.2.n1404 ◽

2021 ◽

Vol 61 (2) ◽

pp. 83-90

Author(s):

Saadet Demirtas Inci ◽

Mustafa Agah Tekindal

Keyword(s):

Acute Coronary Syndrome ◽

Ejection Fraction ◽

Hospital Mortality ◽

Risk Score ◽

Primary Outcome ◽

Characteristic Curve ◽

Curve Analysis ◽

Coronary Syndrome ◽

Grace Risk Score ◽

All Cause Mortality

Goal In this study, it was investigated whether the age, creatinine, and ejection fraction (ACEF) score [age (years) / ejection fraction (%) +1 (if creatinine >2 mg / dL)] could predict in-hospital mortality in patients with non-ST-elevation acute coronary syndrome (NSTE-ACS) and its relationship with the Global Record of Acute Coronary Events (GRACE) risk score were investigated.Material and methods The study enrolled 658 NSTE-ACS patients from January 2016 to August 2020. The patients were divided into two groups according to the ACEF score with an optimum cut-off value of 1.283 who were divided into two groups according to the ACEF score: low ACEF (≤1.283, n:382) and high ACEF (>1.283, n: 276). The primary outcome of the study was in-hospital all-cause mortality. The primary outcome of the study was in-hospital all-cause mortality. Statistically accuracy was defined with area under the curve by receiver-operating characteristic curve analysis.Results In total, 13 (4.71 %) patients had in-hospital mortality. The ACEF score was significantly higher in the group with higher mortality than in the group with low mortality (2.1±0.53 vs. 1.34±0.56 p=0.001). The ACEF score was positively correlated with GRACE risk score (r=0.188 p<0.0001). In ROC curve analysis, the AUC of the ACEF score for predicting in-hospital mortality was 0.849 (95 % CI, 0.820 to 0.876; p<0.0001); sensitivity, 92.3 %; specificity, 59.2 %, and the optimum cut-off value was >1.283.Conclusion The ACEF score presented excellent discrimination in predicting in-hospital mortality. We obtained an easier and more useful result by dividing the ACEF score into two groups instead of three in NSTE-ACS patients. As a simple, useful, and easily applicable risk stratification in the evaluation of an emergency event such as the ACEF score, it can significantly contribute to the identification of patients at high risk.

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