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Discriminant Model for Insulin Resistance in Type 2 Diabetic Patients

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 d...

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Autores principales: López-Galán, Erislandis, Barrio-Deler, Rafael, Fernández-Fernández, Manuel Alejandro, Del Toro-Delgado, Yaquelin, Peñuela-Puente, Isaac Enrique, Sánchez-Hechavarría, Miguel Enrique, Muñoz-Bustos, Mario Eugenio, Muñoz-Bustos, Gustavo Alejandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10222812/
https://www.ncbi.nlm.nih.gov/pubmed/37241071
http://dx.doi.org/10.3390/medicina59050839
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author López-Galán, Erislandis
Barrio-Deler, Rafael
Fernández-Fernández, Manuel Alejandro
Del Toro-Delgado, Yaquelin
Peñuela-Puente, Isaac Enrique
Sánchez-Hechavarría, Miguel Enrique
Muñoz-Bustos, Mario Eugenio
Muñoz-Bustos, Gustavo Alejandro
author_facet López-Galán, Erislandis
Barrio-Deler, Rafael
Fernández-Fernández, Manuel Alejandro
Del Toro-Delgado, Yaquelin
Peñuela-Puente, Isaac Enrique
Sánchez-Hechavarría, Miguel Enrique
Muñoz-Bustos, Mario Eugenio
Muñoz-Bustos, Gustavo Alejandro
author_sort López-Galán, Erislandis
collection PubMed
description 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.
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spelling pubmed-102228122023-05-28 Discriminant Model for Insulin Resistance in Type 2 Diabetic Patients López-Galán, Erislandis Barrio-Deler, Rafael Fernández-Fernández, Manuel Alejandro Del Toro-Delgado, Yaquelin Peñuela-Puente, Isaac Enrique Sánchez-Hechavarría, Miguel Enrique Muñoz-Bustos, Mario Eugenio Muñoz-Bustos, Gustavo Alejandro Medicina (Kaunas) Article 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. MDPI 2023-04-26 /pmc/articles/PMC10222812/ /pubmed/37241071 http://dx.doi.org/10.3390/medicina59050839 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
López-Galán, Erislandis
Barrio-Deler, Rafael
Fernández-Fernández, Manuel Alejandro
Del Toro-Delgado, Yaquelin
Peñuela-Puente, Isaac Enrique
Sánchez-Hechavarría, Miguel Enrique
Muñoz-Bustos, Mario Eugenio
Muñoz-Bustos, Gustavo Alejandro
Discriminant Model for Insulin Resistance in Type 2 Diabetic Patients
title Discriminant Model for Insulin Resistance in Type 2 Diabetic Patients
title_full Discriminant Model for Insulin Resistance in Type 2 Diabetic Patients
title_fullStr Discriminant Model for Insulin Resistance in Type 2 Diabetic Patients
title_full_unstemmed Discriminant Model for Insulin Resistance in Type 2 Diabetic Patients
title_short Discriminant Model for Insulin Resistance in Type 2 Diabetic Patients
title_sort discriminant model for insulin resistance in type 2 diabetic patients
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10222812/
https://www.ncbi.nlm.nih.gov/pubmed/37241071
http://dx.doi.org/10.3390/medicina59050839
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