Objective: Achieving good metabolic control in people with type 1 diabetes (T1D) remains a challenge, despite the evolutions in diabetes technologies over the past decade. Here we investigate the evolution of metabolic control in people with T1D, where care is provided by specialized centers with access to technology, diabetes education, and regular follow-up. Methods: Data were cross-sectionally collected between 2010 and 2018 from more than 100 centers in Belgium. The evolutions over time of hemoglobin A1C (HbA1c), low-density lipoprotein (LDL) cholesterol, and systolic blood pressure (SBP) were investigated, together with the evolutions of use of insulin pump (continuous subcutaneous insulin infusion [CSII]), continuous glucose monitoring (CGM), and lipid-lowering and antihypertensive drugs. Association of HbA1c with gender, age, diabetes duration, and technology use was analyzed on the most recent cohort. Results: The study population contained data from 89,834 people with T1D (age 1–80 years). Mean HbA1c decreased from 65 mmol/mol (8.1%) in 2010–2011 to 61 mmol/mol (7.7%) in 2017–2018 ( P < 0.0001, adjusted for gender, age, diabetes duration, and technology use). Respectively, mean LDL cholesterol decreased from 2.45 mmol/L (94.6 mg/dL) to 2.29 mmol/L (88.5 mg/dL) ( P < 0.0001, adjusted for gender, age, and diabetes duration), and mean SBP remained stable. CGM usage increased, whereas the use of CSII and lipid-lowering and antihypertensive drugs remained stable. Gender, age, diabetes duration, and technology use were independently associated with HbA1c. Conclusions: Our real-world data show that metabolic and lipid control improved over time in a system where T1D care is organized through specialized multidisciplinary centers with emphasis on linking education to provision of technology, and its quality is monitored.

Recent publications on Coronavirus Disease-2019 (COVID-19) report that diabetic people with or without co-morbidities are at higher risk of developing severe and/or fatal illnesses. We report the f...

Introduction: Assessment of glucose exposure via glycated hemoglobin A ₁ c (HbA ₁ c) has limitations for interpretation in individuals with diabetes and chronic kidney disease (CKD). The glucose management indicator (GMI) derived from continuous glucose monitoring (CGM) data could be an alternative. However, the concordance between HbA ₁ c measured in laboratory and GMI (HbA ₁ c-GMI) is uncertain in individuals with CKD. The purpose of this study is to analyze this discrepancy. Material and method: We performed a multicentric, retrospective, observational study. A group of individuals with diabetes and CKD (n = 170) was compared with a group of individuals with diabetes without CKD (n = 185). All individuals used an intermittently scanned continuous glucose monitoring (isCGM). A comparison of 14-day and 90-day glucose data recorded by the isCGM was performed to calculate GMI and the discordance between lab HbA ₁ c and GMI was analyzed by a Bland-Altman method and linear regression. Results: HbA ₁ c-GMI discordance was significantly higher in the CKD group versus without CKD group (0.78 ± 0.57 [0.66-0.90] vs 0.59 ± 0.44 [0.50-0.66]%, P < .005). An absolute difference >0.5% was found in 68.2% of individuals with CKD versus 42.2% of individuals without CKD. We suggest a new specific formula to estimate HbA ₁ c from the linear regression between HbA ₁ c and mean glucose CGM, namely CKD-GMI = 0.0261 × 90-day mean glucose (mg/L) + 3.5579 ( r ² = 0.59). Conclusions: HbA1c-GMI discordance is frequent and usually in favor of an HbA1c level higher than the GMI value, which can lead to errors in changes in glucose-lowering therapy, especially for individuals with CKD. This latter population should benefit from the CGM to measure their glucose exposure more precisely.