Comparative Evaluation of Non-HDL Cholesterol and the Triglyceride-Glucose Index for Predicting Acute Myocardial Infarction Risk in a Nepalese Hospital Population: A Cross-Sectional Study

Background Myocardial infarction (MI) remains a leading cause of morbidity and mortality worldwide, with South Asian populations facing a disproportionately high burden. In Nepal, the incidence of MI has been rising, and recent data suggest that cardiovascular diseases constitute a significant percentage of total deaths annually. While non-high-density lipoprotein cholesterol (non-HDL-C) is established in long-term cardiovascular risk stratification, newer metabolic markers such as the triglyceride-glucose (TyG) index have emerged as promising predictors. However, comparative evidence regarding their diagnostic and predictive roles in the acute setting, particularly in Nepal, is lacking. Methods This hospital-based, cross-sectional study enrolled adult individuals presenting with and without acute MI. Demographic, lifestyle, and clinical data were collected, and biochemical profiles — including fasting lipid profile, fasting glucose, and derived indices (non-HDL-C, TyG, Atherogenic Index of Plasma, and lipid ratios) — were analyzed. Receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of non-HDL-C and the TyG index. Univariate and multivariate logistic regression identified independent MI risk factors. Correlation analyses were used to explore relationships among biochemical parameters. Results A total of 200 participants (100 MI and 100 non-MI) were included (mean age for MI: 59.9 ± 13.0 years; non-MI: 45.0 ± 9.3 years). MI patients were predominantly male and more likely to be current smokers. Non-HDL-C did not significantly differ between the MI and non-MI groups (median 125.0 mg/dL, p = 0.880) and demonstrated poor diagnostic performance (AUC 0.49, 95% CI 0.41–0.57). In contrast, the TyG index was significantly higher in MI patients (8.91 ± 0.61 vs. 8.63 ± 0.45, p < 0.001) and showed modestly better discrimination (AUC 0.64, 95% CI 0.56–0.72). Traditional risk factors such as older age, male sex, smoking, low HDL-C, higher BMI, and fasting glucose remained strong independent predictors of MI. Lipid ratios (non-HDL/HDL, TC/HDL, TG/HDL) and the Atherogenic Index of Plasma were also elevated in MI patients (p < 0.01). Spearman correlation revealed strong associations among non-HDL-C, TG, and TyG index, while HDL-C was inversely related to atherogenic markers. Conclusion In this first Nepalese study comparing non-HDL-C and the TyG index for acute MI diagnosis, the TyG index emerged as a more effective marker of metabolic risk, though its incremental diagnostic utility was modest. Non-HDL-C did not enhance acute MI detection. Traditional risk factors continue to dominate MI prediction in this population. These findings suggest that while non-HDL-C and the TyG index are valuable for long-term risk assessment, their roles in acute MI diagnosis are limited. Integrating the TyG index with existing regional lipid-management and acute coronary syndrome protocols could potentially refine risk stratification for better clinical outcomes. Larger, multi-center studies are warranted to validate the clinical utility of the TyG index, especially in high-risk and metabolically diverse South Asian populations.