Real-world glycaemic outcomes in patients with type 1 diabetes using glucose sensors-Experience from a single centre in Dublin.

AIMS: To evaluate changes in glycated haemoglobin (HbA1 c) and sensor-based glycaemic metrics after glucose sensor commencement in adults with T1D. METHODS: We performed a retrospective observational single-centre study on HbA1 c, and sensor-based glycaemic data following the initiation of continuous glucose monitoring (CGM) in adults with T1D (n = 209). RESULTS: We observed an overall improvement in HbA1 c from 66 (59-78) mmol/mol [8.2 (7.5-9.3)%] pre-sensor to 60 (53-71) mmol/mol [7.6 (7.0-8.6)%] on-sensor (p < .001). The pre-sensor HbA1 c improved from 66 (57-74) mmol/mol [8.2 (7.4-8.9)%] to 62 (54-71) mmol/mol [7.8 (7.1-8.7)%] within the first year of usage to 60 (53-69) mmol/mol [7.6 (7.0-8.4)%] in the following year (n = 121, p < .001). RT-CGM-user had a significant improvement in HbA1 c (Dexcom G6; p < .001, r = 0.33 and Guardian 3; p < .001, r = 0.59) while a non-significant reduction was seen in FGM-user (Libre 1; p = .279). Both MDI (p < .001, r = 0.33) and CSII group (p < .001, r = 0.41) also demonstrated significant HbA1 c improvement. Patients with pre-sensor HbA1 c of ≥64 mmol/mol [8.0%] (n = 125), had attenuation of pre-sensor HbA1 c from 75 (68-83) mmol/mol [9.0 (8.4-9.7)%] to 67 (59-75) mmol/mol [8.2 (7.6-9.0)%] (p < .001, r = 0.44). Altogether, 25.8% of patients achieved the recommended HbA1 c goal of ≤53 mmol/mol and 16.7% attained the recommended ≥70% time in range (3.9-10.0 mmol/L). CONCLUSIONS: Our study demonstrated that minimally invasive glucose sensor technology in adults with T1D is associated with improvement in glycaemic outcomes. However, despite significant improvements in HbA1 c, achieving the recommended goals for all glycaemic metrics remained challenging.

Association between Sleep Disruption and Levels of Lipids in Caucasians with Type 2 Diabetes.

Aim. To investigate the association between sleep quality and duration with lipid and glycaemic control in Caucasian subjects with type 2 diabetes. Methods. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) in 114 type 2 diabetes (T2DM) subjects. Comparisons were made between subjects with different sleep quality and sleep duration. Hierarchical multiple regression analyses were used to determine contributors to metabolic parameters. Results. Subjects with poor sleep quality (PQ; PSQI ≥ 6) had higher systolic blood pressure, glycated haemoglobin, urine albumin : creatinine ratio (UAC), total cholesterol (TC), and triglycerides (TG) (P < 0.05 for all) compared to those with good sleep quality (GQ; PSQI ≤ 5). Long sleep duration (LSD) subjects had higher TC and short sleep duration (SSD) subjects had higher TG compared to those with medium sleep duration. Sleep duration and PSQI score were independent predictors of TC and low-density lipoprotein cholesterol (LDL), contributing to 14.0% and 6.1% of the total variance, respectively. Conclusions. In this Caucasian T2DM population, PQ is associated with adverse cardiovascular risk markers, and long and short sleep disruptions have an independent negative impact on lipids. Sleep assessment should be included as part of a diabetes clinic review.