Glycemic variability assessed by continuous glucose monitoring and the risk of diabetic retinopathy in latent autoimmune diabetes of the adult and type 2 diabetes

Abstract

Aims/Introduction The relationship between glycemic variability ( GV ) and diabetic complications has gained much interest and remains under debate. Furthermore, the association of GV with diabetic complications has not been examined in latent autoimmune diabetes of the adult ( LADA ). Therefore, we evaluated the relationships among several metrics of GV with diabetic retinopathy ( DR ) in patients with LADA and type 2 diabetes mellitus. Materials and Methods A total of 192 patients with LADA and 2,927 patients with type 2 diabetes mellitus were enrolled. After continuous glucose monitoring for 72 h, three metrics of GV including standard deviation, coefficient of variation and mean amplitude of glycemic excursions were calculated. DR was assessed by fundus photography performed with a digital non‐mydriatic camera. Results The prevalence of DR was 20.3 and 26.4% in LADA and type 2 diabetes mellitus patients ( P < 0.001), respectively. Generally, LADA patients had fewer cardiometabolic risk factors than type 2 diabetes mellitus patients, and all GV metrics were significantly higher in LADA than in type 2 diabetes mellitus. In the multivariate logistic regression analysis, no metrics for GV were identified as independent risk factors of DR (standard deviation: P = 0.175; coefficient of variation: P = 0.769; mean amplitude of glycemic excursions: P = 0.388) in LADA . However, the standard deviation was significantly associated with DR ( OR 1.15, P = 0.017) in patients with type 2 diabetes mellitus after adjusting for confounders. The independent relationships of coefficient of variation and mean amplitude of glycemic excursions with DR ( P = 0.194 and P = 0.251, respectively) did not reach statistical significance in type 2 diabetes mellitus. Conclusions GV is more strongly associated with DR in type 2 diabetes than in LADA , suggesting that different glucose‐lowering strategies should be used for these two types of diabetes.

Associations Between Continuous Glucose Monitoring-derived Metrics and Diabetic Retinopathy and Albuminuria in Patients With Type 2 Diabetes

“…Nevertheless, until now, only limited data from cross-sectional studies investigating the relationship between CGM metrics and diabetic microvascular complications have been available. Intriguingly, two recent cross-sectional studies conducted by the same group demonstrated that standard deviation (SD) and TIR are each signi cantly associated with the presence of DR in inpatients with type 2 diabetes [16,17]. Another study showed that TIR is associated with the presence of albuminuria in patients with type 2 diabetes, but this relationship did not reach statistical signi cance after adjusting for HbA1c levels [18].…”

Smartphone-Based Data Collection in Ophthalmology

“…These data can be used in patient risk stratification, as well as for better adjustment of treatment, and thus are also of interest to ophthalmologists, for example, for monitoring patients with diabetic retinopathy or in the course of studies [18,19].…”

Chinese clinical guidelines for continuous glucose monitoring (2018 edition)

“…Glycemic variability includes short‐term glycemic variability such as postprandial hyperglycemia and long‐term glycemic variability as assessed by HbA 1c variability. Studies have shown that both short‐term and long‐term glycemic variability may be an important factor in the development of diabetes complications . CGM continuously captures patterns of hypoglycemia, hyperglycemia, and the short‐term glucose variability.…”