The Triglyceride-Glucose Index Might Be a Better Indicator for Predicting Poor Cardiovascular Outcomes in Chronic Coronary Syndrome.
Aslan ErdoğanDuygu İnanÖmer GençUfuk YıldızAyse Irem Demirtolaİlyas ÇetinYeliz GulerAli Fuat TekinSüleyman BarutçuAhmet GülerAli KaragözPublished in: Journal of clinical medicine (2023)
This study aimed to explore the potential association between the triglyceride-glucose index (TyG) and the atherogenic index of plasma (AIP)-both considered surrogate markers for atherosclerosis-and major adverse cardiovascular events (MACEs) in patients diagnosed with chronic coronary syndrome (CCS). We conducted a retrospective analysis, encompassing 715 consecutive patients with intermediate CCS risk, who presented at the outpatient clinic between June 2020 and August 2022. MACEs included non-fatal myocardial infarction, hospitalization for heart failure, cerebrovascular events, non-cardiac mortality, and cardiac mortality. The primary outcome was the composite occurrence of MACEs during the follow-up period. For time-to-event analysis of the primary outcome, we employed Kaplan-Meier plots and Cox proportional hazard models. The median age of the overall study population was 55 years, with a median follow-up duration of 17 months. Multivariate Cox regression analysis identified age, hypertension, Coronary Artery Disease-Reporting and Data System score, and TyG index as independent predictors of the primary outcome. Notably, individuals with high TyG levels exhibited a significantly higher primary outcome rate compared to those with low TyG levels (18.7% vs. 3.8%, p < 0.001). Similarly, patients with elevated TyG values demonstrated statistically higher rates of cerebrovascular events, hospitalizations for heart failure, non-fatal myocardial infarctions, non-cardiac mortality, and cardiac mortality. These findings suggest that TyG may serve as a predictive marker for adverse cardiovascular outcomes in patients with CCS.
Keyphrases
- cardiovascular events
- coronary artery disease
- left ventricular
- heart failure
- cardiovascular disease
- percutaneous coronary intervention
- coronary artery bypass grafting
- aortic stenosis
- risk factors
- cardiac resynchronization therapy
- end stage renal disease
- blood pressure
- adverse drug
- primary care
- chronic kidney disease
- type diabetes
- ejection fraction
- newly diagnosed
- skeletal muscle
- emergency department
- acute coronary syndrome
- machine learning
- patient reported outcomes
- low density lipoprotein
- human health
- deep learning
- prognostic factors
- transcatheter aortic valve replacement