Early and sustained increase in time in range 1 year after initiation of hybrid close loop therapy via telemedicine in type 1 diabetes patients.

BACKGROUND AND AIMS: Evidence supports the efficacy and safety of the Hybrid Close loop (HCL) system in patients with type 1 diabetes (T1D). However, limited data are available on the long-term outcomes of patients on HCL with telemedicine follow-up. METHODS: A prospective observational cohort study including T1D patients, who were upgrading to HCL system. Virtual training and follow-up were done through telemedicine. CGM data were analyzed to compare the baseline time in range (TIR), time below range (TBR), glycemic variability and auto mode (AM), with measurements performed at 3, 6 and 12 months. RESULTS: 134 patients were included with baseline A1c 7.6% ± 1.1. 40.5% had a severe hypoglycemia event in the last year. Baseline TIR, measured two weeks after starting AM was 78.6 ± 9.94%. No changes were evident at three (Mean difference - 0.15;CI-2.47,2.17;p = 0.96), six (MD-1.09;CI-3.42,1.24;p = 0.12) and 12 months (MD-1.30;CI-3.64,1.04;p = 0.08). No significant changes were found in TBR or glycemic variability throughout the follow-up. Use of AM was 85.6 ± 17.5% and percentage of use of sensor was 88.75 ± 9.5% at 12 months. No severe hypoglycemic (SH) events were reported. CONCLUSIONS: HCL systems allow to improve TIR, TBR and glycemic variability safely, early and sustained up to 1 year of follow-up in patients with T1D and high risk of hypoglycemia followed through telemedicine.

Glycemic control metrics using flash glucose monitoring and hospital complications in patients with COVID-19.

BACKGROUND AND AIMS: Few studies have reported on the use of continuous glucose monitoring (CGM) during the Covid-19 pandemic. We aimed to examine glycemic control metrics using flash glucose monitoring during insulin treatment and the clinical outcome in hospitalized patients with COVID-19. METHODS: Prospective, single-center cohort of adult patients diagnosed with type 2 diabetes or hyperglycemia and COVID-19 infection treated with basal bolus insulin regimen. Glycemic control was assessed with the use of intermittent Freestyle Libre flash glucose monitoring during the hospital stay. Outcome of interest were time in range [TIR], time above [TAR] and below [TBR] range, glycemic variability [coefficient of variation [% CV]), and differences in a composite of complications including ICU admission, acute respiratory distress syndrome (ARDS) and acute kidney injury. RESULTS: A total of 60 patients were included (44 known diabetes and 16 new onset hyperglycemia). In total 190,080 data points of CGM were available, of which 72.5% of values were within the target area [TIR (70-180 mg/dL)], 22% TAR (>180 mg/dL), and 3% were TBR (<70 mg/dL). During treatment, the coefficient of variation (% CV) was 30%. There were no association with TIR, but patients with TAR >180 mg/dl had higher rates of a composite of complications (22.5% vs 16%, p = 0.04). CONCLUSIONS: Basal bolus insulin regimen was safe and effective in achieving inpatient glycemic control in most patients with COVID-19. The association between TAR and complications indicates the need for improved inpatient glycemic control in hospitalized patients with COVID-19.

Virtual training on the hybrid close loop system in people with type 1 diabetes (T1D) during the COVID-19 pandemic.

BACKGROUND AND AIMS: In Colombia, the government established mandatory isolation after the first case of COVID-19 was reported. As a diabetes care center specialized in technology, we developed a virtual training program for patients with type 1 diabetes (T1D) who were upgrading to hybrid closed loop (HCL) system. The aim of this study is to describe the efficacy and safety outcomes of the virtual training program. METHOD: ology: A prospective observational cohort study was performed, including patients with diagnosis of T1D previously treated with multiple doses of insulin (MDI) or sensor augmented pump therapy (SAP) who were updating to HCL system, from March to July 2020. Virtual training and follow-up were done through the Zoom video conferencing application and Medtronic Carelink System version 3.1 software. CGM data were analyzed to compare the time in range (TIR), time below range (TBR) and glycemic variability, during the first two weeks corresponding to manual mode with the final two weeks of follow-up in automatic mode. RESULTS: 91 patients were included. Mean TIR achieved with manual mode was 77.3 ± 11.3, increasing to 81.6% ± 7.6 (p < 0.001) after two weeks of auto mode use. A significant reduction in TBR <70 mg/dL (2,7% ± 2,28 vs 1,83% ± 1,67, p < 0,001) and in glycemic variability (% coefficient of variation 32.4 vs 29.7, p < 0.001) was evident, independently of baseline therapy. CONCLUSION: HCL systems allows T1D patients to improve TIR, TBR and glycemic variability independently of previous treatment. Virtual training can be used during situations that limit the access of patients to follow-up centers.