Background The metabolic score for insulin resistance (METS-IR) is a neoteric score for assessing insulin resistance that has been used as a non-insulin-based, objectively measured method. It is an easily accessible tool that can be used on a large scale to detect insulin resistance in a community. Methods We conducted a retrospective cohort study to explore the utility of this score in identifying metabolic risk in those individuals attending a master health checkup in a tertiary care setting. Data were collected from 254 individuals between October and December 2023. Results According to the univariate regression analysis, METS-IR had a strong correlation in predicting cardiovascular health risks, as evidenced by its positive linear association with an increase in age (β=0.186, p=0.003), weight (β=0.534, p<0.001), waist circumference (β=0.405, p<0.001), and body mass index (BMI; β=0.635, p<0.001). This explained the value of this score in depicting adiposity and insulin resistance. Lab parameters that showed a significant association were fasting blood sugar (β=0.176, p=0.005) and fasting triglycerides (β=0.175, p=0.005). According to the multivariate regression analysis, METS-IR had a significant positive association with fasting blood sugar (B=0.489, p<0.001) and fasting triglycerides (B=0.022, p=0.003), implicating its importance in cardiovascular health. High-density lipoprotein cholesterol (HDL-c; B=-0.168, p=0.005) confirmed its protective role with its negative association in higher quartile groups. An increase in serum albumin levels (B=-0.168, p=0.005) and raised gamma-glutamyl transpeptidase (GGT) (B=0.059, p=0.022) portrays its due diligence in liver health. METS-IR had a weak association with the estimated glomerular filtration rate (eGFR) with Pearson's correlation coefficient of 0.020 (p=0.756) and Spearman's rho of 0.021 (p=0.739). However, raised serum creatinine had a significant association in higher quartile groups, with a p-value of 0.018. Conclusions METS-IR is useful as a screening tool for predicting cardiovascular disease. However, the complex interplay of other confounding factors in identifying renal dysfunction has yet to be explored when considering this score in our study population.
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