Objective: To investigate whether telemetric continuous glucose monitoring (CGM) in hospitalized and isolated patients with diabetes mellitus and coronavirus disease 2019 (COVID-19) is associated with better glycaemic outcomes and fewer patient-health care worker contacts compared to blood glucose monitoring by traditional point-of-care (POC) glucose testing and to investigate the user aspect of implementing a CGM-system inhospital. Methods: A randomized controlled exploratory trial was performed on hospitalized and isolated patients with diabetes and COVID-19 from May 2020 until February 2021 at Nordsjaellands Hospital, Denmark. Participants were randomized to nonblinded telemetric CGM (as the only glucose monitoring method) or traditional POC glucose testing + blinded CGM. The primary endpoint was Time In Range (TIR) based on CGM data in both groups. A questionnaire about the user aspect of the CGM system was answered by health care personnel (HCP). Results: We included 64 participants in the analysis, 31 in the CGM group and 33 in the POC glucose group. TIR median was 46% for the CGM group and 68% for the POC glucose group (p=0.368). The mean glucose value for the CGM group was 11.1 mmol/L and 10.8 mmol/L in the POC glucose group (p=0.372). CGM was associated with fewer POC glucose measurements (p<0.001). Out of 30 HCPs, 28 preferred telemetric CGM over POC glucose testing. Conclusion: Remote glucose monitoring by CGM did not improve glycaemic outcomes compared to traditional POC glucose testing but was associated with fewer patientpersonnel contacts, saving time for HCPs performing diabetes-related tasks. Most HCPs preferred CGM.

Background Glycemic variability (GV) has only been sparsely studied in patients with community-acquired pneumonia (CAP). This study aimed to quantify in-hospital GV in CAP patients, including determining the impact of type 2 diabetes mellitus (T2DM) and glucocorticoid (GC) treatment on GV. Methods This is a prospective cohort study of CAP patients (N = 40) with or without T2DM and treated or not with GCs. The primary endpoint was GV measured as glucose standard deviation (SD), coefficient of variation (CV), and postprandial glucose excursions (PPGE) based on continuous glucose monitoring (CGM). Analysis of glucose data was split into daytime and nighttime when possible. Results Patients included had a mean age of 74 (range 55 to 91) years. SD (95%CI) increased by a factor of 1.93 (1.40 to 2.66) and 2.29 (1.38 to 3.81) in patients with T2DM and not treated with GCs during the daytime and the nighttime, respectively (both P < 0.01), and by a factor of 1.42 (1.04 to 1.97) in patients treated with GCs but without T2DM during the daytime (P = 0.031) compared to patients without T2DM and not treated with GCs. CV (95%CI) increased by 5.1 (0.0 to 10.1) and 8.1 (1.0 to 15.2) percentage points during the daytime and the nighttime, respectively, in patients with T2DM and not treated with GCs compared to patients without T2DM and not treated with GCs (P = 0.046 and P = 0.026, respectively). PPGE (95% CI) increased during lunch by 2.5 (0.7 to 4.3) mmol/L (45 (13 to 77) mg/dL) in patients with T2DM and treated with GCs compared to patients without T2DM and not treated with GCs (P = 0.018). Conclusions CAP patients receiving GCs, especially those with T2DM, are at great risk of developing high GV and therefore require clinical attention to mitigate GV. This applies particularly during the daytime. Results support the 1 to 2-h post-lunch screening procedure for glucocorticoid-induced hyperglycemia in patients without diabetes. SD was positively correlated with hospital length of stay.

Introduction: Lipohypertrophy (LH) is caused by repetitively injecting insulin into the same location. This can lead to unpredictable insulin absorption and increased glucose variability (GV). A new medical device, ROTO Track, automatically guides the user to rotate abdominal insulin injections to avoid LH lesions. This study aimed to test whether the medical device could reduce the number of insulin injections in the same subcutaneous area as compared with non-aided standard insulin injection techniques. Methods: In this proof-of-concept cross-over study, baseline data about injection site in the abdominal region were collected blinded for 1 week with a nonguiding version of the device and compared to 1 and 12 weeks of device guidance in 35 people with type 1 diabetes. The device registered time and location of abdominal injections. The primary endpoint was a “rotation score.” Secondary endpoints included number and size of LH, GV, and hemoglobin A1c. Results: The rotation score improved significantly from a baseline mean of 40.2% to 49.9% after 1 week (confidence interval: 2.2-17.2%, P = .012) and improved further after 12 weeks to 52.2% ( P < .001). After 12 weeks, LH was reduced both in median size from 9.2 (range: [0.9-29.4]) cm2 to 5.4 (range: [0.0- 26.8]) cm2 ( P = .041) and mean count from 1.4 (range: [1-2]) to 1.1 (range: [0-2], P = .039) and the coefficient of variation of interstitial glucose was reduced from 38.6 to 35.1 ( P = .009). Conclusion: This proof-of-concept study indicates that the device improves rotation of insulin injections, and reduces LH and GV.