Discriminant Model for Insulin Resistance in Type 2 Diabetic Patients

Author:

López-Galán Erislandis1,Barrio-Deler Rafael2,Fernández-Fernández Manuel Alejandro1,Del Toro-Delgado Yaquelin1,Peñuela-Puente Isaac Enrique1,Sánchez-Hechavarría Miguel Enrique34ORCID,Muñoz-Bustos Mario Eugenio5,Muñoz-Bustos Gustavo Alejandro6ORCID

Affiliation:

1. Facultad de Medicina No.2, Universidad de Ciencias Médicas de Santiago de Cuba, Santiago de Cuba 90100, Cuba

2. Hospital Pediátrico Juan de la Cruz Martínez Maceira, Santiago de Cuba 90100, Cuba

3. Programa de Promoción de la Salud y Prevención de la Enfermedad del Núcleo Científico Tecnológico para el Desarrollo Costero Sustentable, Facultad de Medicina, Universidad Católica de la Santísima Concepción, Concepcion 4090541, Chile

4. Núcleo Científico de Ciencias de la Salud, Facultad de Ciencias de la Salud, Universidad Adventista de Chile, Chillán 3780000, Chile

5. Departamento de Kinesiología, Facultad de Medicina, Universidad de Concepción, Concepción 4030000, Chile

6. Escuela de Kinesiología, Facultad de Salud y Ciencias Sociales, Campus El Boldal, Sede Concepción, Universidad de las Américas, Santiago 4030000, Chile

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.

Funder

Apoyo a la Publicaciones Open Acces de la Universidad de las Americas de Chile

Publisher

MDPI AG

Subject

General Medicine

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