Aspartate Aminotransferase to Platelet Ratio Index (APRI) as a Predictor of Metabolic Syndrome (MetS) Development in Individuals With Type 2 Diabetes Mellitus

Introduction: Despite ongoing findings on the relationship between liver fibrosis in nonalcoholic fatty liver disease (NAFLD) and metabolic syndrome (MetS), this association in diabetic patients remains unclear. Early diagnosis of liver fibrosis is important due to the easily available diagnostic tools, such as noninvasive indices that combine clinical and laboratory variables, and the possibility of preventing its complications in type 2 diabetes mellitus (T2DM) patients with MetS. Objective: This study examines the potential predictive values of non-invasive liver fibrosis indices for MetS in T2DM patients. Patients and methods: Over the course of a two-year prospective, observational, clinical study, 80 individuals with T2DM randomly selected from the Diabetes Counseling Centers of the Public Institution Health Center of Sarajevo Canton were divided into two groups: T2DM-MetS and T2DM-non-MetS, based on the development of MetS. The study included individuals with T2DM aged 30 to 60 who were clinically diagnosed without MetS, voluntarily agreed to participate, and provided complete data in the collection forms. Serum samples from the patients were assessed for levels of liver enzymes, platelet counts, total cholesterol, high-density lipoprotein cholesterol, fasting glucose, and triglycerides. Various equations were utilized to calculate liver fibrosis indices, including the Aspartate Aminotransferase to Platelet Ratio Index (APRI), Aspartate Aminotransferase to Gamma-Glutamyl Transferase to Platelet Ratio (AGPR), Aspartate Aminotransferase to Alanine Aminotransferase Ratio to Platelet Ratio Index (AARPRI), Fibrosis-4 (FIB-4) Index, Forns Index, and Gamma-Glutamyl Transpeptidase to Platelet Ratio (GPR). Receiver operating characteristic (ROC) analysis was utilized to determine the usefulness of noninvasive liver fibrosis indices for diagnosing MetS in individuals with T2DM. Logistic regression analysis was used to predict the onset of MetS in T2DM patients. Results: Significant differences in the values of APRI (p<0.001), AGPR (p<0.05), AARPRI (p<0.001), and the FIB-4 index (p=0.001) were observed in T2DM-MetS individuals compared to T2DM-non-MetS. According to ROC analysis, the area under the curve (AUC) was found to be highest for APRI (0.84), followed by FIB-4 (0.783) and AARPRI (0.747). Logistic regression analysis identified APRI as an independent positive predictor of MetS (OR 18.179, 95% CI 6.035-24.58, p=0.015). Conclusion: This research highlights the effectiveness of the APRI index as a reliable predictor of MetS development in individuals with T2DM.