Secretaría de Gobernación
CONACYT
INGER
Por favor, use este identificador para citar o enlazar este ítem: http://repositorio.inger.gob.mx/jspui/handle/20.500.12100/17270
Título : The combination of insulin resistance and visceral adipose tissue estimation improves the performance of metabolic syndrome as a predictor of type 2 diabetes
Autor: Neftali Eduardo Antonio Villa
OMAR YAXMEHEN BELLO CHAVOLLA
ARSENIO VARGAS VAZQUEZ
ROOPA PRAVIN MEHTA
CARLOS ALBERTO AGUILAR SALINAS
Palabras clave : MEDICINA Y CIENCIAS DE LA SALUD;Ciencias médicas;Ciencias clínicas;Enfermedades metabólicas;Trastornos del metabolismo de la glucosa;Diabetes mellitus;Diabetes mellitus tipo 2;Metabolic diseases;Glucose metabolism disorders;Diabetes Mellitus, Type 2
Fecha de publicación: 2020
Editorial : Wiley & Diabetes UK
Descripción : Aims To assess the performance of metabolic syndrome as a predictor of type 2 diabetes in a model that also includes both a measure of insulin resistance and a metabolic score for visceral fat, and to propose a novel metabolic syndrome definition. Methods In a prospective Metabolic Syndrome Cohort (n=6143), we evaluated improvements in type 2 diabetes risk prediction using International Diabetes Federation‐defined and Adult Treatment Panel III‐defined metabolic syndrome, after inclusion in the model of updated homeostatic model assessment of insulin resistance and a metabolic score for visceral fat. We also developed a modified metabolic syndrome construct, 'MS‐METS', which used the metabolic score for visceral fat instead of waist circumference to evaluate improved predictive performance for risk of developing type 2 diabetes. Results Participants who had metabolic syndrome as defined by both the Adult Treatment Panel III and the International Diabetes Federation criteria had a higher risk of type 2 diabetes compared to participants who did not meet these criteria. Addition of updated homeostatic model assessment of insulin resistance and metabolic score for visceral fat to both metabolic syndrome definitions increased predictive performance for type 2 diabetes risk. Homeostatic model assessment of insulin resistance was the only additional predictor of type 2 diabetes in participants without metabolic syndrome. Conversely, in participants with metabolic syndrome, the use of the metabolic score for visceral fat was the stronger added predictor for type 2 diabetes. When evaluating participants using the MS‐METS definition we observed the largest improvement in predictive ability for type 2 diabetes risk and a significant reduction in risk overestimation compared to evaluation using metabolic syndrome defined according to the International Diabetes Federation and Adult Treatment Panel III criteria alone. Conclusion Inclusion of updated homeostatic model assessment of insulin resistance and metabolic score for visceral fat increases performance of metabolic syndrome in prediction of type 2 diabetes. Assessment of insulin resistance could be more useful than conventional metabolic syndrome and assessment of visceral adipose tissue could be more useful in people with metabolic syndrome. Metabolic syndrome as defined using our modified MS‐METS construct improved the accuracy of type 2 diabetes prediction.
URI : http://repositorio.inger.gob.mx/jspui/handle/20.500.12100/17270
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