Â鶹ֱ²¥app

Clinical Factors Associated with High Glycemic Variability Defined by the Variation Coefficient in Patients with Type 2 Diabetes

Authors

Ana María Gómez; Lucía B. Taboada; D Henao ; Andrey Alexandrovich Sankó Posada; Martin Rondón; Oscar Muñoz; Maira García-Jaramillo; Fabián León-Vargas

Introduction

The term glycemic variability is defined as the degree of fluctuation in blood glucose values in a given period of time. In patients with type 2 diabetes the presence of high glycemic variability in the short term has been associated in multiple studies with the presence of hypoglycaemia. Following the 2017 recommendations of the international consensus of interpretation of CGM, the variation coefficient (%VC) is considered the metric of choice to describe the unstable diabetic patient. High variability is considered a value equal to or greater than 36%. The aim of this study was to determine the clinical factors that are associated with an increased risk of glycemic variability in patients with type 2 diabetes so that the clinician is able to identify those patients at higher risk of presenting with hypoglycaemia episodes.

Methods

A cross-sectional analysis was made of a registry of 148 adult patients diagnosed with type 2 diabetes mellitus who had been taken to continuous glucose monitoring using the iPro2 Medtronic equipment at the Diabetes Clinic of San Ignacio University Hospital in Bogotá, Colombia. A Medtronic Enlite sensor was inserted subcutaneously in the anterior area of the abdomen and maintained for 6 days in every patient. The information was downloaded using the iPRO CareLink version 3.0 software. Patients were classified into groups of high and low variability being a coefficient of variation equal to or greater than 36% considered as high variability. The statistical system STATA 14 was used for the analysis.

Results

32% of patients had high glycemic variability. Using a bivariate analysis, overweight was significantly associated with a CV% above 36% (OR 0.44), considering in this case a protective variable compared to a normal BMI. Although obesity presented an OR of similar magnitude, it did not reach statistical significance (OR 0.41). A glomerular filtration rate below 45 mL/min was associated with twice the chance of presenting high variability, although this analysis does not reach statistical significance either. Using a multivariate analysis, both obesity and overweight were associated with less chance of having a CV greater than 36%, with a decrease of 58% and 66% respectively. On the other hand, decreased GFR was significantly associated with a 2.5-fold increase in the chance of presenting high variability (OR 2.55).

Conclusion

This study provides a slight approach to some clinical variables to which the physician must pay attention in the consultation which relate to glucose variability and therefore an increase or decrease in the risk of hypoglycaemia episodes in patients with type 2 diabetes. Yet, prospective and larger-scale studies designed to establish clinical variables that may constitute risk factors for variability are needed in the future.

References

  1. Gomez AM. Different Indexes of Glycemic Variability as Identifiers of Patients with Risk of Hypoglycemia in Type 2 Diabetes Mellitus. J Diabetes Sci Technol. 2018;12:1007–15.
  2. Gomez AM. The different methods of assessing glycemic variability, quality of glycemic control and glycemic risk cannot be interpreted as equivalent in clinical practice. Diabetes Metab Syndr [Internet]. 2018;12:555–61. Available from:
  3. Monnier L. Toward Defining the Threshold Between Low and High Glucose Variability in Diabetes. Diabetes Care. 2017;40:832–8.
  4. S Rama Chandran. Beyond HbA1c: Comparing Glycemic Variability and Glycemic Indices in Predicting Hypoglycemia in Type 1 and Type 2 Diabetes. Diebetes Technol Ther. 2018;20:353–62.
  5. F Uemura. Relation Between Hypoglycemia and Glycemic Variability in Type 2 Diabetes Patients with Insulin Therapy: A Study Based on Continuous Glucose Monitoring. Diebetes Technol Ther. 2018;20:140–6.
  6. Wang J. Association of lower body mass index with increased glycemic variability in patients with newly diagnosed type 2 diabetes: a cross-sectional study in China. Oncotarget. 2017;8:73133–43.
  7. Suh S. Glycemic Variability: How Do We Measure It and Why Is It Important? Diabetes Metab J [Internet]. 2015;39:273–82. Available from:
  8. Vaduva C. Analysis of chronic kidney disease – Associated glycemic variability in patients with type 2 diabetes using continuous glucose monitoring system. Rom J Diabetes Nutr Metab Dis. 2013;20:315–22.

Back to the November 2019 issue of ACP IMpact