Digitally enabled flash glucose monitoring for inpatients with COVID-19: Feasibility and pilot implementation in a teaching NHS Hospital in the UK

Background COVID-19 placed significant challenges on healthcare systems. People with diabetes are at high risk of severe COVID-19 with poor outcomes. We describe the first reported use of inpatient digital flash glucose monitoring devices in a UK NHS hospital to support management of people with diabetes hospitalized for COVID-19. Methods Inpatients at University Hospitals Coventry & Warwickshire (UHCW) NHS Trust with COVID-19 and diabetes were considered for digitally enabled flash glucose monitoring during their hospitalization. Glucose monitoring data were analysed, and potential associations were explored between relevant parameters, including time in hypoglycaemia, hyperglycaemia, and in range, glycated haemoglobin (HbA1c), average glucose, body mass index (BMI), and length of stay. Results During this pilot, digital flash glucose monitoring devices were offered to 25 inpatients, of whom 20 (type 2/type 1: 19/1; mean age: 70.6 years; mean HbA1c: 68.2 mmol/mol; mean BMI: 28.2 kg/m2) accepted and used these (80% uptake). In total, over 2788 h of flash glucose monitoring were recorded for these inpatients with COVID-19 and diabetes. Length of stay was not associated with any of the studied variables (all p-values >0.05). Percentage of time in hyperglycaemia exhibited significant associations with both percentage of time in hypoglycaemia and percentage of time in range, as well as with HbA1c (all p-values <0.05). The average glucose was significantly associated with percentage of time in hypoglycaemia, percentage of time in range, and HbA1c (all p-values <0.05). Discussion We report the first pilot inpatient use of digital flash glucose monitors in an NHS hospital to support care of inpatients with diabetes and COVID-19. Overall, there are strong arguments for the inpatient use of these devices in the COVID-19 setting, and the findings of this pilot demonstrate feasibility of this digitally enabled approach and support wider use for inpatients with diabetes and COVID-19.

NCOG-11. ASSOCIATION OF HYPERGLYCEMIA AND TUMOR SUBCLASS ON SURVIVAL IN IDH-WILDTYPE GLIOBLASTOMA

BACKGROUND RNA expression and DNA methylation studies have identified different subclasses of isocitrate dehydrogenase (IDH)-wildtype (wt) glioblastoma (GBM). However, the prognostic significance of molecular subclasses is unclear. Although hyperglycemia has been previously associated with worse survival, attempts to lower glucose have yielded mixed responses. The role of hyperglycemia may be confounded by molecular heterogeneity and have different impact in molecularly distinct GBM subclasses. METHODS Clinical, laboratory, and molecular data on 89 IDH-wt GBMs profiled by clinical next-generation sequencing and treated with Stupp protocol were reviewed. IDH-wt GBMs were subclassified into RTKI (Proneural), RTKII (Classical) and Mesenchymal subtypes using DNA methylation. Average glucose was calculated by time-weighting plasma glucose measurements between diagnosis and last follow-up. RESULTS Patients were stratified into three groups using average glucose: tertile one (&lt; 100mg/dL), tertile two (100-115mg/dL), and tertile three ( &gt; 115mg/dL). Comparison across glucose tertiles revealed no significant differences in Karfnosky Performance Status (KPS), dexamethasone dose, MGMT methylation, or methylation subclass. Overall survival (OS) was not affected by methylation subclass (log-rank p=0.9) but decreased with higher glucose (log-rank p=0.015). Higher glucose tertiles were associated with poorer OS among RTK I (log-rank p=0.08) and mesenchymal tumors (log-rank p=0.05), but not RTK II (log-rank p=0.99). After controlling for age, KPS, dexamethasone dose, and MGMT status, glucose remained significantly associated with survival (adjusted hazard ratio=5.2, p=0.02). DNA methylation clustering did not identify a unique signature associated with high or low glucose levels. Metabolomic analysis of 23 tumors showed minimal variation across metabolites within the cohort with no differences across molecular subclasses. CONCLUSION Higher average glucose values were associated with poorer OS in RTKI and Mesenchymal IDH-wt GBM, but not RTKII. There were no discernible epigenetic or metabolomic differences between tumors in different glucose environments, suggesting a potential survival benefit with systemic glucose lowering in selected molecular subtype.

24-h Glycaemic profiles in peritoneal dialysis patients and non-dialysis controls with advanced kidney disease

Background: For patients on peritoneal dialysis (PD), the deleterious effects of high concentrations of dialysate glucose on the peritoneal membrane are well-documented. Systemic effects of peritoneally absorbed glucose are more poorly defined. Using continuous glucose monitoring (CGM), we aimed to describe 24-h glycaemic profiles of PD patients without diabetes and compare with non-dialysis controls with stage 5 chronic kidney disease (CKD-5). Methods: In this cross-sectional, case-control study, 15 patients on PD (9 automated PD (APD) and 6 continuous ambulatory PD (CAPD)) and 16 CKD-5 controls underwent 72 h of CGM and metabolic profiling. CGM was used to derive average glucose concentrations and within-participant standard deviation (SD) of glucose. Data were analysed for the whole 72-h monitoring period and as daytime (09.00 to 21.00) and night-time (21.00 to 09.00). Results: Average glucose concentrations and within-participant SD of glucose for the whole monitoring period were not different between the three groups ( p ≥ 0.5). Daytime average glucose concentrations were also similar across the three groups ( p = 0.729). APD was associated with a significantly higher nocturnal glucose than CAPD (5.25 mmol/L ± 0.65 vs. 4.28 ± 0.5, p = 0.026). A significant drop in nocturnal glucose compared with daytime average seen in both CAPD patients and controls was absent in APD patients. Conclusions: Systematically different glycaemic patterns were observed in non-diabetic APD and CAPD patients, including an absence of physiological nocturnal glucose dipping in patients on APD. Comprehensive CGM data sets highlight subtleties not appreciated by traditional metabolic biomarkers; this has implications when choosing the most appropriate outcome measures in future research addressing the metabolic impact of PD.

Benefits of a Switch from Intermittently Scanned Continuous Glucose Monitoring (isCGM) to Real-Time (rt) CGM in Diabetes Type 1 Suboptimal Controlled Patients in Real-Life: A One-Year Prospective Study

The switch from intermittently scanned continuous glucose monitoring (isCGM) to real-time (rt) CGM could improve glycemic management in suboptimal controlled type 1 diabetes patients, but long-term study is lacking. We evaluated retrospectively the ambulatory glucose profile (AGP) in such patients after switching from Free Style Libre 1 (FSL1) to Dexcom G4 (DG4) biosensors over 1 year. Patients (n = 21, 43 ± 15 years, BMI 25 ± 5, HbA1c 8.1 ± 1.0%) had severe hypoglycemia and/or HbA1c ≥ 8%. AGP metrics (time-in-range (TIR) 70–180 mg/dL, time-below-range (TBR) <70 mg/dL or <54 mg/dL, glucose coefficient of variation (%CV), time-above-range (TAR) >180 mg/dL or >250 mg/dL, glucose management indicator (GMI), average glucose) were collected the last 3 months of FSL1 use (M0) and of DG4 for 3, 6 (M6) and 12 (M12) months of use. Values were means ± standard deviation or medians [Q1;Q3]. At M12 versus M0, the higher TIR (50 ± 17 vs. 45 ± 16, p = 0.036), and lower TBR < 70 mg/dL (2.5 [1.6;5.5] vs. 7.0 [4.5;12.5], p = 0.0007), TBR < 54 mg/dL (0.7 [0.4;0.8] vs. 2.3 [0.8;7.0], p = 0.007) and %CV (39 ± 5 vs. 45 ± 8, p = 0.0009), evidenced a long-term effectiveness of the switch. Compared to M6, TBR < 70 mg/dL decreased, %CV remained stable, while the improvement on hyperglycemia exposure decreased (higher GMI, TAR and average glucose). This switch was a relevant therapeutic option, though a loss of benefit on hyperglycemia stressed the need for optimized management of threshold alarms. Nevertheless, few patients attained the recommended values for AGP metrics, and the reasons why some patients are “responders” vs. “non-responders” warrant to be investigated.

Effects of Academic Stress on Teenagers with Type 1 Diabetes

Type one diabetes is a a condition that is exponentially growing in the US and all over the world. As the majoirty of these patients are diagnosed at a young age, much research is being completed in order to find ways to help these adolescents live a more normal life by minimizing its effects. The goal of this research is to find a possible correlation between diabetic teenagers’ academic stress levels and their average glucose levels. By means of an extensive 3 week survey in which each participant was asked to share their stress levels, lifestyle habits, and glucose reports on a daily basis, it was found that there is a strong positive correlation between he two variables. They produced an r-value of about 0.9939, suggesting statistical significance. Knowing this information will help patients within this age group manage their glucose readings better and keep them at better control throughout the day.

Estimation of Average Blood Glucose Values Based on Fructosamine Values

Introduction: The fructosamine is originated of the glycation of plasmatic proteins, especially albumin, in addition to immunoglobulins and proteins diverse. It constitutes an alternative biomarker of glycemic control when glycated hemoglobin is not indicated for this purpose. Objective: To define the mathematical relationship between fructosamine and average glucose values. Method: The study comprised the laboratorial data collected of 1227 diabetic subjects (type 1 and type 2). Fructosamine levels obtained at the end of three weeks and measured were compared with the average glucose levels of the three previous weeks. The average glucose levels were determined by the weighted mean of the daily fasting capillary glucose results performed during the study period, and the plasma glucose taken at the time of the fructosamine. Results: A total of 9,450 glucoses were performed. Linear regression analysis between the fructosamine and average glucose levels showed that each increase of 1.0 lower case Greek mumol/L in fructosamine increase 0.5mg/dL in the average glucose levels as evidenced in the equation forward: Average glucose levels = 0.5157 x Fructosamine - 20. According to the coefficient of determination (r2 = 0.353492, P < 0.006881), making it possible to calculate the estimated average glucose according to the frutosamine values. Conclusion: Fructosamine levels can be expressed as average glucose levels for assessing the metabolic control of diabetic patients.

Benefits of a Switch From Intermittently Scanned Continuous Glucose Monitoring (isCGM) to Real-time (rt) CGM in Diabetes Type 1 Suboptimal Controlled Patients in Real-life: A One-year Prospective Study

The switch from intermittently scanned continuous glucose monitoring (isCGM) to real-time (rt) CGM could improve glycemic management in suboptimal controlled type 1 diabetes patients, but long-term study is lacking. We evaluated retrospectively the ambulatory glucose profile (AGP) in such patients after switching from Free Style libre 1 (FSL1) to Dexcom G4 (DG4) over 1 year. Patients (n=21, 43&plusmn;15 years, BMI 25&plusmn;5, HbA1c 8.1&plusmn;1.0%) had severe hypoglycemia and/or HbA1c&ge;8%. AGP metrics (time-in-range (TIR) 70-180 mg/dL, time-below-range (TBR)&lt;70 mg/dL or &lt;54 mg/dL, glucose coefficient of variation (%CV), time-above-range (TAR) &gt;180 mg/dL or &gt;250 mg/dL, glucose management indicator (GMI), average glucose) were collected the last 3 months of FSL1 use (M0) and of DG4 for 3, 6 (M6) and 12 (M12) months of use. Values were means &plusmn; standard deviation or medians [Q1;Q3]. At M12 versus M0, the higher TIR (50&plusmn;17 vs. 45&plusmn;16, P=0.036), and lower TBR&lt;70 mg/dL (2.5 [1.6;5.5] vs. 7.0 [4.5;12.5], P=0.0007), TBR&lt;54 mg/dL (0.7 [0.4;0.8] vs. 2.3 [0.8;7.0], P=0.007) and %CV (39&plusmn;5 vs. 45&plusmn;8, P=0.0009), evidenced a long-term effectiveness of the switch. Compared to M6, TBR&lt;70mg/dL decreased, %CV remained stable, while the improvement on hyperglycemia exposure decreased (higher GMI, TAR and average glucose). This switch was a relevant therapeutic option, though a loss of benefit on hyperglycemia stressed the need for optimized management of threshold alarms. Nevertheless, few patients attained the recommended values for AGP metrics, and the reasons why some patients are &ldquo;responders&rdquo; vs &ldquo;non-responders&rdquo; warrant to be investigated.

Impaired Glucose-Insulin Metabolism in Multisystem Inflammatory Syndrome Related to SARS-CoV-2 in Children

An interaction between metabolic glucose impairment and coronavirus disease 2019 is reported. The development of a severe multisystem inflammatory syndrome in children (MIS-C) related to SARS-CoV-2 infection has been described. We evaluated the impact of MIS-C on glycemic patterns in pediatric patients. A group of 30 children and adolescents affected by MIS-C were considered; all patients were normal weight. Clinical and biochemical assessments, including surrogate markers of insulin resistance (IR) such as homeostasis model analysis-IR (HOMA-IR) and triglyceride–glucose (TyG) indexes, were recorded. Patients were also invited to undergo an intermittently scanned continuous glucose monitoring (isCGM). HOMA-IR index was calculated in 18 patients (60%), of which 17 (94%) revealed a pathological value. TyG index was computed for all patients and pathological values were detected in all cases. In 15 patients, isCGM data were recorded on average for 9 days (±3 days). Overall, average glucose was 105 mg/dL (±16 mg/dL) and average time spent in the 70–180 mg/dL range (TIR) was 93.76%, with nearly 10% of glucose readings in the 141–180 mg/dL range; glycemic fluctuations over the hyperglycemic threshold were detected in four patients. Regular glucose monitoring may be useful to prevent metabolic imbalance and obtain a better outcome.