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.

The Association of Physical Function Measures With Frailty, Falls History, and Metabolic Syndrome in a Population With Complex Obesity.

Background: Frailty, falls and metabolic syndrome are known to be associated with poorer physical function. This study builds on available research by further investigating the relationship between physical function measures, including those comprising frailty, with metabolic syndrome (MetS) and falls, in the context of complex obesity. Methods: Participants were recruited from the national Level 3 weight management service in Ireland. A retrospective audit of data gathered at initial assessment was performed. Data included past medical history, blood tests, blood pressure measurement, anthropometrics, falls history, self-reported physical activity levels (PALs) and physical function measures, including hand grip strength (HGS), "timed up and go" (TUG), functional reach (FR), sit to stand (STS) and gait speed. A modified version of the Fried Frailty Index was employed. Results: Of the 713 participants, 65.1% (n = 464) were female and 34.9% (n = 249) were male with a mean age of 44.2 (±11.7) years and body mass index (BMI) of 50.6 kg/m2 (±8.2). Frailty was identified in 3.4% (n = 24), falls in 28.8% (n = 205) and MetS in 55.1% (n = 393). Frailty was associated with older age (53.8 ± 14.3 vs. 43.9 ± 11.5 years), poorer PALs (27.29 ± 46.3 vs. 101.1 ± 147.4 min/wk), reduced grip strength (17.7 ± 4.6 vs. 34.2 ± 11.0 Kg) longer STS (21.7 ± 6.6 vs. 13.7 ± 5.7 s), shorter functional reach (29.7 ± 7.9 vs. 37.9 ± 8.2 cm) and slower gait speed (0.6 ± 0.2 vs. 1.1 ± 0.5 m/s). Those reporting a falls history had a reduced FR (35.8 ± 8.9 vs. 38.3 ± 7.8 cm) and slower STS (15.4 ± 8.0 vs. 13.3 ± 4.7 s). Participants with MetS had lower PALs (83.2 ± 128.2 vs. 119.2 ± 157.6) and gait speed (1.1 ± 0.3 vs. 1.2 ± 0.7 m/s). There was no difference in BMI between fallers and non-fallers (51.34 ± 8.44 vs. 50.33 ± 8.13 Kg/m2, p = 0.138), nor between those with or without MetS. Significant associations were found between BMI and all physical function measures except the TUAG. Conclusion: The associations between frailty, falls and MetS and their combined impact on physical function in people living with obesity demonstrates the need for appropriate screening. Utilising grip strength and gait speed to identify frailty in those with obesity and metabolic syndrome could help target therapies aimed at improving strength, physical function and ultimately quality of life.