Clinical Factors Associated with High Glycemic Variability Defined by Coefficient of Variation in Patients with Type 2 Diabetes
AM Gómez,1– 3 DC Henao-Carillo,1– 3 L Taboada,1,3 O Fuentes,1,3 O Lucero,2,3 A Sanko,3 MA Robledo,3 O Muñoz,2,3 M Rondón,4 M García-Jaramillo,5 F León-Vargas6 1Endocrinology Unit, Hospital Universitario San Ignacio, Bogot&...
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| Autores principales: | , , , , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
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Dove Medical Press
2021
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| Acceso en línea: | https://doaj.org/article/07c0466f6cbb478baffd1dbabe6968df |
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| Sumario: | AM Gómez,1– 3 DC Henao-Carillo,1– 3 L Taboada,1,3 O Fuentes,1,3 O Lucero,2,3 A Sanko,3 MA Robledo,3 O Muñoz,2,3 M Rondón,4 M García-Jaramillo,5 F León-Vargas6 1Endocrinology Unit, Hospital Universitario San Ignacio, Bogotá, Colombia; 2Department of Internal Medicine, Hospital Universitario San Ignacio, Bogotá, Colombia; 3Faculty of Medicine, Pontificia Universidad Javeriana, Bogotá, Colombia; 4Department of Clinical Epidemiology, Pontificia Universidad Javeriana, Bogotá, Colombia; 5Faculty of Engineering, Universidad EAN, Bogotá, Colombia; 6Faculty of Engineering, Universidad Antonio Nariño, Bogotá, ColombiaCorrespondence: AM GómezEndocrinology Unit, Hospital Universitario San Ignacio, Carrera 7 No. 40-62, Bogotá, ColombiaEmail amgomezm5@gmail.comBackground: High glycemic Variability (HGV) has become a stronger predictor of hypoglycemia. However, clinical factors associate with HGV still are unknown.Objective: To determine clinical variables that were associated with a coefficient of variation (CV) above 36% evaluated by continuous glucose monitoring (CGM) in a group of patients with diabetes mellitus.Methods: A cohort of patients with type 2 diabetes (T2D) was evaluated. Demographic variables, HbA1c, glomerular filtration rate (GFR) and treatment regimen were assessed. A bivariate analysis was performed, to evaluate the association between the outcome variable (CV> 36%) and each of the independent variables. A multivariate model was constructed to evaluate associations after controlling for confounding variables.Results: CGM data from 274 patients were analyzed. CV> 36% was present in 56 patients (20.4%). In the bivariate analysis, demographic and clinical variables were included, such as time since diagnosis, hypoglycemia history, A1c, GFR and treatment established. In the multivariate analysis, GFR < 45 mL/min (OR 2.81; CI 1.27,6.23; p:0.01), A1c > 9% (OR 2.81; CI 1.05,7.51; p:0.04) and hypoglycemia history (OR 2.09; CI 1.02,4.32; p:0.04) were associated with HGV. Treatment with iDPP4 (OR 0.39; CI 0.19,0.82; p:0.01) and AGLP1 (OR 0.08; CI 0.01,0.68; p:0.02) was inversely associated with GV.Conclusion: Clinical variables such as GFR < 45 mL/min, HbA1C> 9% and a history of hypoglycemia are associated with a high GV. Our data suggest that the use of technology and treatments able to reduce glycemic variability could be useful in this population to reduce the risk of hypoglycemia and to improve glycemic control.Keywords: glycemic variability, variation coefficient, continuous glucose monitoring, diabetes mellitus |
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