Discriminant Model for Insulin Resistance in Type 2 Diabetic Patients

Medicina (Kaunas). 2023 Apr 26;59(5):839. doi: 10.3390/medicina59050839.

Abstract

Introduction: Patients with type 2 diabetes mellitus tend to have insulin resistance, a condition that is evaluated using expensive methods that are not easily accessible in routine clinical practice. Objective: To determine the anthropometric, clinical, and metabolic parameters that allow for the discrimination of type 2 diabetic patients who have insulin resistance from those who do not. Methods: A cross-sectional analytical observational study was carried out in 92 type 2 diabetic patients. A discriminant analysis was applied using the SPSS statistical package to establish the characteristics that differentiate type 2 diabetic patients with insulin resistance from those without it. Results: Most of the variables analyzed in this study have a statistically significant association with the HOMA-IR. However, only HDL-c, LDL-c, glycemia, BMI, and tobacco exposure time allow for the discrimination of type 2 diabetic patients who have insulin resistance from those who do not, considering the interaction between them. According to the absolute value of the structure matrix, the variable that contributes most to the discriminant model is HDL-c (-0.69). Conclusions: The association between HDL-c, LDL-c, glycemia, BMI, and tobacco exposure time allows for the discrimination of type 2 diabetic patients who have insulin resistance from those who do not. This constitutes a simple model that can be used in routine clinical practice.

Keywords: anthropometric indicators; insulin resistance; lipid profile; type 2 diabetes mellitus.

Publication types

  • Observational Study

MeSH terms

  • Blood Glucose / metabolism
  • Cholesterol, LDL
  • Cross-Sectional Studies
  • Diabetes Mellitus, Type 2*
  • Humans
  • Insulin
  • Insulin Resistance*
  • Triglycerides

Substances

  • Cholesterol, LDL
  • Blood Glucose
  • Insulin
  • Triglycerides