Association between glycaemia risk index (GRI) and diabetic retinopathy in type 2 diabetes: A cohort study.

Aim: To investigate the association between a new composite metric, glycaemia risk index (GRI), and incident diabetic retinopathy (DR).

Methods: A total of 1204 adults with type 2 diabetes without DR at baseline were included between 2005 and 2019 from a single centre in Shanghai, China. GRI was obtained from continuous glucose monitoring data at baseline.

Proof-of-concept Application of Continuous Glucose Monitoring Data Analytics to Identify Diabetes Glucotypes.

Background: In this proof-of-concept study, we evaluated if monogenic diabetes resulting from mutations of the gene (HNF1A-MODY) has a distinctive continuous glucose monitoring (CGM) glucotype, in comparison to type 1 diabetes (T1D).

Methods: Using CGM data from 5 subjects with HNF1A-MODY and 115 subjects with T1D, we calculated multiple glucose metrics, including measures of within- and between-day variability (such as coefficient variation for each hour [CV]).

Results: The MODY and T1D cohorts had minimum CV of 11.

Continuous glucose monitoring metrics (Mean Glucose, time above range and time in range) are superior to glycated haemoglobin for assessment of therapeutic efficacy.

Aim: To evaluate continuous glucose monitoring (CGM) metrics for use as alternatives to glycated haemoglobin (HbA1c) to evaluate therapeutic efficacy.

Methods: We re-analysed correlations among CGM metrics from studies involving 545 people with type 1 diabetes (T1D), 5910 people with type 2 diabetes (T2D) and 98 people with T1D during pregnancy and the postpartum period.

Results: Three CGM metrics, interstitial fluid Mean Glucose level, proportion of time above range (%TAR) and proportion of time in range (%TIR), were correlated with HbA1c and provided metrics that can be used to evaluate therapeutic efficacy.

Consensus Recommendations for the Use of Automated Insulin Delivery Technologies in Clinical Practice.

The significant and growing global prevalence of diabetes continues to challenge people with diabetes (PwD), healthcare providers, and payers. While maintaining near-normal glucose levels has been shown to prevent or delay the progression of the long-term complications of diabetes, a significant proportion of PwD are not attaining their glycemic goals. During the past 6 years, we have seen tremendous advances in automated insulin delivery (AID) technologies.