Abstract

BackgroundThis study aimed to explore predictive factors of time below target glucose range (TBR) ≥ 1% among patients’ characteristics and glycemic variability (GV) indices using continuous glucose monitoring data in elderly patients with type 2 diabetes.MethodsWe conducted a prospective observational study on 179 (71 female) Japanese outpatients with type 2 diabetes aged ≥ 65 years. The characteristics of the participants with TBR ≥ 1% were evaluated by multivariate logistic regression analysis. Receiver-operating characteristic (ROC) curve analyses of GV indices, comprising coefficient of variation (CV), standard deviation, and mean amplitude of glycemic excursions, were performed to identify the optimal index for the identification of patients with TBR ≥ 1%.ResultsIn the multivariate logistic regression analysis, none of the clinical characteristics, including HbA1c and C-peptide index, were independent markers for TBR ≥ 1%, while all three GV indices showed significant associations with TBR ≥ 1%. Among the three GV indices, CV showed the best performance based on the area under the curve in the ROC curve analyses.ConclusionsAmong elderly patients with type 2 diabetes, CV reflected TBR ≥ 1% most appropriately among the GV indices examined.Trial registration UMIN-CTR: UMIN000029993. Registered 16 November 2017

Highlights

  • The number of elderly patients with diabetes increased to 111.2 million worldwide in 2019 [1], reflecting a substantial burden on the medical care system

  • The 179 elderly patients with type 2 diabetes were divided into two subgroups: Time below target glucose range (TBR) ≥ 1% (n = 57) and TBR < 1% (n = 122)

  • For the three glycemic variability (GV) indices, coefficient of variation (CV), standard deviation (SD) and mean amplitude of glycemic excursions (MAGE) were significantly higher in the TBR ≥ 1% group compared with the TBR < 1% group (Table 2)

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Summary

Introduction

The number of elderly patients with diabetes increased to 111.2 million worldwide in 2019 [1], reflecting a substantial burden on the medical care system. Continuous glucose monitoring (CGM) has been used worldwide for daily clinical practice [7]. An international consensus recommended the coefficient of variation (CV) as the main measure of GV, because it can predict hypoglycemia more accurately than other GV indices including the standard deviation (SD) [8]. The international consensus recommended percentage of time below target glucose range (TBR; < 70 mg/ dL) < 1% as an appropriate CGM-related value for prevention of hypoglycemia in elderly patients with diabetes [10]. This study aimed to explore predictive factors of time below target glucose range (TBR) ≥ 1% among patients’ characteristics and glycemic variability (GV) indices using continuous glucose monitoring data in elderly patients with type 2 diabetes

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