Ambulatory Glucose Profiles Research Articles

INfluenza VaccInation To mitigate typE 1 Diabetes (INVITED): a study protocol for a randomised, double-blind, placebo-controlled clinical trial in children and adolescents with recent-onset type 1 diabetes

IntroductionChildren and adolescents with recent-onset type 1 diabetes (T1D) commonly maintain a certain level of insulin production during the remission phase, which can last months to years. Preserving β-cell function...

Comparison of Glycemia Risk Index with Time in Range for Assessing Glycemic Quality.

Background: The glycemia risk index (GRI) is a novel composite continuous glucose monitoring (CGM) metric that gives greater weight to hypoglycemia than to hyperglycemia and to extreme hypo/hyperglycemia over less extreme hypo/hyperglycemia. This study aimed at validating the effectiveness of GRI and at comparing it with time in range (TIR) in assessing glycemic quality in clinical practice. Methods: A total of 524 ninety-day CGM tracings of 194 insulin-treated adults with diabetes were included in the analysis. GRI was assessed according to standard metrics in ambulatory glucose profiles. Both cross-sectional and longitudinal analyses were performed to compare the GRI and TIR. Results: The GRI was strongly correlated not only with TIR (r = -0.974), but also with the coefficient of variation (r = 0.683). To identify whether the GRI differed by hypoglycemia even with a similar TIR, CGM tracings were grouped according to TIR (50% to <60%, 60% to <70%, 70% to <80%, and ≥80%). In each TIR group, the GRI increased as time below range (TBR)<70 mg/dL increased (P < 0.001 for all TIR groups). In longitudinal analysis, as TBR<70 mg/dL improved, the GRI improved significantly (P = 0.003) whereas TIR did not (P = 0.704). Both GRI and TIR improved as time above range (TAR)>180 mg/dL improved (P < 0.001 for both). The longitudinal change was easily identifiable on a GRI grid. Conclusions: The GRI is a useful tool for assessing glycemic quality in clinical practice and reflects hypoglycemia better than does TIR.

Case Reports Using Continuous Glucose Monitoring: Analysis For Application Of Digitalization In Management Of Diabetes Mellitus

Diabetes has emerged as a burgeoning health challenge in the last two decades. Specifically, there is an alarming rate of adult-onset diabetes mellitus, a point of deep concern. Therefore, cohesive steps are essential for the management of symptoms of diabetes mellitus to regulate its prevalence rate globally. Continuous glucose monitoring (CGM) technology can aid in this effort by allowing for safe therapy intensification with HbA1c (hemoglobin-a1c) reduction and by assisting in lowering some of the psychosocial impacts of diabetes. We aim to analyze the application of the digital device Freestyle Libre Pro in the management of diabetes mellitus. Using the FreeStyle Libre Pro CGM system, we analyzed the datasets for eight patients over 14 days. In addition, regular 12-hour data was monitored on a fortnight basis. Two of the eight cases were on insulin, and the rest were administered oral medications for diabetes care. Ambulatory Glucose Profiles, Average Glucose Levels, Time in Range, Time Below Range, Time Above Range, and, afterward, calculation of HbA1c levels were determined for eight patients using the FreeStyle Libre Pro system's current glucose measurements. We observed that for four patients, the average glucose levels were maintained in range, and for f our patients, the average glucose levels were above range. Regarding Time, four were above range, and four were in range. Our analysis shows that the Freestyle Libre Pro offers an alternative to current CGM devices for professional use as it may aid clinics and patients.

Changes in ambulatory glucose profile in people with type 1 diabetes using an automated insulin delivery system - two year follow-up retrospective analysis of real-world data

The number of available automated insulin delivery (AID) systems is increasing in Austria and people with diabetes (PwD) replace sensor-augmented pump (SAP) therapy more and more frequently. The present study is the two years follow-up of our prior monocentric, retrospective analysis conducted between 2019 and 2021, comparing SAP and open-source AID systems in people with type 1 diabetes. This second-year analysis included 25 PwD and investigated glycemic changes based on ambulatory glucose profiles (AGP). In comparison to the first year, a worsening of mean glucose (125.4 to 135.2 mg/dl, P = 0.038), time in range ((TIR), 84.2 to 77.0%, P = 0.012), time above range ((TAR), 11.6% to 18.5%, P = 0.017) and glycemia risk index ((GRI), 24.8 to 35.0%, P = 0.026) was observed. The reduction of mean glucose and glucose variability with AID in the first year was due to a significant decrease in time in hyperglycemia with resulting higher TIR and lower GRI. In this second-year follow up, TIR and GRI showed a significant deterioration, a familiar phenomenon in diabetology. However, open-source AID systems showed continuous safety, as there was no increase in time below range (TBR) even after two years. Despite the slight deterioration in the glycemic parameters, open-source AID systems were able to demonstrate sufficient glycemic control according to international consensus guidelines while offering the characteristic benefits of a reduced burden of diabetes management. A descriptive comparison of different AID algorithms indicated an improved glycemic control with more advanced features such as basal rate modification, auto bolus function and autotuning.

An Old Theme and New Technology: Marked Glucocorticoid-Induced Hyperglycemia in a Hospitalized Patient Uncovered Retrospectively by Her Flash Glucose Monitoring

Abstract Background Glucocorticoid-induced hyperglycemia is a problem-facing endocrinologists and internal medicine specialists in hospital wards. Case History A 63-year-old woman with type 2 diabetes was admitted to the hospital with acute exacerbation of chronic obstructive airway disease. She was treated with a short course of intravenous hydrocortisone followed by oral prednisolone. On discharge, she attended her regular diabetes consultation. Throughout the period, she had her flash glucose monitoring (FGM) sensor in place, and she was monitoring her blood glucose regularly. As part of her diabetes clinic routine, the meter data uploaded and ambulatory glucose profiles were examined. These revealed three distinctly different blood glucose levels before, during, and after glucocorticoid therapy. Glucocorticoid therapy resulted in a marked rise in blood glucose that lasted for a further week before it returned to the pre-treatment levels. This old phenomenon has yet to be demonstrated using the new FGM technology. Conclusions The story (1) asserts the significant impact of glucocorticoid therapy on glycemic control, (2) demonstrates the prolonged impact on glycemic control following discontinuation of glucocorticoids, (3) suggests a lack of adequate monitoring and timely recognition of hyperglycemia in the hospital, and poor management glucocorticoid-induced hyperglycemia either due to failure of conventional monitoring methods or a degree of complacency to appreciate its magnitude.

Adherence to Mediterranean Diet Is Associated With Better Glycemic Control in Children With Type 1 Diabetes: A Cross-Sectional Study.

Type 1 diabetes (T1D) is a chronic condition, with increased morbidity and mortality, due to a higher rate of cardiovascular disease among other factors. Cardiovascular risk increases with the worse glycemic profile. Nutrition has a deep impact on diabetes control. Adherence to the Mediterranean diet (MD) has been shown to decrease cardiovascular risk in children and adults with obesity and adults with type 2 diabetes, but its impact on T1D children has been scarcely analyzed. We hypothesized that the degree of adherence to MD could relate to the increased time in range in children with T1D.Patients and MethodsCross-sectional analysis involving two university hospitals. We measured the adherence to MD with the Mediterranean Diet Quality Index for children and teenagers (KIDMED) questionnaire, which is a validated tool for this purpose. A score of <5 indicates poor adherence to MD, while a good adherence is indicated by a score of >7. Demographic and clinical data were registered on the same day that the questionnaire was taken, with informed consent. Additionally, the patients' ambulatory glucose profiles (AGPs), were registered from the participants' glucose monitors (continuous or flash devices), and daily insulin needs were recorded from patients' insulin pumps (n=28). Other cardiovascular risk factors such as lipid profile, vitamin D levels, and other biochemical parameters were registered from a blood test, performed 2 weeks before recruitment, as part of the patients' annual screening.ResultsNinety-seven patients (44 girls), with an average age of 11.4 years (± 3.01), were included. Seventy-one of them were on multiple daily injection regimens, and all had either continuous or flash glucose monitoring. Fifty-three had HbA1c levels of <7.5%, while only 21 had a time in range (TIR) of >70%. Contingency analysis showed that the odds of having HbA1c <7.5% increase in children with KIDMED score of >7 (O.R. 2.38; ICR 1.05–5.41; p = 0.036). Moreover, the KIDMED score and the HbA1c levels were negatively correlated (R: −0.245; p-value: 0.001), while the KIDMED score and TIR showed a positive correlation (R: 0.200; p-value: 0.009).ConclusionsOur data suggest that adherence to MD may contribute to better glycemic control in children. This should be taken into account at the time of nutritional education on T1D patients and their families.

Abstract 93: Ambulatory glucose profiles of children and adolescents with T1DM: Identification of factors affecting glycemic control

Background: Continuous glucose monitoring (CGM) provides information about glycemic control, beyond that provided by HbA1c and SMBG, including short-term glycemic variability, hypoglycemic and hyperglycemic events.Aims and Objectives: To describe ATTD endorsed CGM derived glycemic variables from a cohort of T1DM, assess possible factors influencing glycemic control and study the association between HbA1c and these variables.Results: 61 patients (age, 15.9 + 5), median duration of diabetes 6 years, wore the FreeStyle libre for a median of 14 days. Mean TIR was 46.3 + 15.5, TBR 16.7 + 13.5 and TAR 36.9 + 22.0. Mean glycemic variability (%CV) was 48% and 90% had high %CV. Those using NPH had a significantly higher %CV (P=0.007) compared to those on glargine. Females (n=34, P=0.05) and those using NPH (n=18, P=0.08) tended to spend a longer time in hypoglycemia. HbA1c showed a negative correlation with TIR (r=-0.441), TBR (r=-0.544), %CV (r=-0.335) and a positive correlation with TAR (r=0.656), mean glucose (r=0.714). On subgroup analysis, group with lowest HbA1c (<6.8%, n=16), although had highest TIR but also highest TBR.Conclusion: Our findings demonstrate wide gaps between the recommended versus real world glycemic variables in children with T1DM and highlight the need to implement interventions for better glycemic control.Acknowledgements: This work was supported by a grant from the Endocrine Society of India.

59-LB: The Impact of Glycemic Variability on the Relationship between Hypoglycemia and HbA1c

Introduction: Continuous glucose monitoring (CGM) guidelines suggest a target glycemic variability, as measured by coefficient of variation (CV) ≤36%, to mitigate hypoglycemia in people with type 1 diabetes (T1D). However, they provide no context to hemoglobin A1c (HbA1c) values. The aim of this study was to evaluate the relationship between CV, hypoglycemia, and HbA1c among adults with T1D.Methods: A retrospective sample of adults (≥18 years) with T1D from the Barbara Davis Center for Diabetes who had available ambulatory glucose profiles and laboratory-measured HbA1c were analyzed at the patient-visit level between 2014 and 2020. Negative binomial regression of aggregated data over 7 days was used to estimate the number of level-2 (<54 mg/dL) hypoglycemic events at cross-sections of HbA1c and CV for a maximum of 2 weeks, after adjusting for time of CGM use.Results: Among 466 adults with T1D (mean age=37 years) at 1,648 visits, percentage of CGM use was 91%. We observed wide variation in level 2 hypoglycemic events across CV and HbA1c categories (Figure 1). The highest mean estimated number of events was 3.5 (95% CI: 2.4, 4.6) per week, found in patients with CV > 36%, HbA1c<6.5%.Conclusion: Glycemic variability (CV) provides meaningful insights about level 2 hypoglycemia that should be used in combination with HbA1c and other factors to inform clinical decision making to help mitigate risk for possible hypoglycemia.View largeDownload slideView largeDownload slide DisclosureR. Mcqueen: Research Support; Self; Eli Lilly and Company. S. Ellis: Research Support; Self; Eli Lilly and Company. M. Perez-nieves: Employee; Self; Eli Lilly and Company. G. T. Alonso: None. R. Juneja: Employee; Self; Eli Lilly and Company. K. Hannah: None. L. Fan: Employee; Self; Eli Lilly and Company, Stock/Shareholder; Self; Eli Lilly and Company, Stock/Shareholder; Spouse/Partner; Eli Lilly and Company. E. R. Hankosky: Employee; Self; Eli Lilly and Company, Stock/Shareholder; Self; Eli Lilly and Company. V. Shah: Advisory Panel; Self; Medscape, Sanofi, Research Support; Self; Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Novo Nordisk, Sanofi, vTv Therapeutics. Y. Yan: Employee; Self; Eli Lilly and Company.FundingEli Lilly and Company

Ultra-Rapid Lispro Improves Postprandial Glucose Control and Time in Range in Type 1 Diabetes Compared to Lispro: PRONTO-T1D Continuous Glucose Monitoring Substudy.

Background: This study evaluated glucose control by continuous glucose monitoring (CGM) during treatment with ultra-rapid lispro (URLi) or lispro used in combination with insulin glargine or degludec in adults with type 1 diabetes in a substudy of the PRONTO-T1D study.Methods: Ambulatory glucose profiles were evaluated in 269 patients from PRONTO-T1D assigned to double-blind URLi (n = 97) or lispro (n = 99) given 0–2 min before the start of the meal (mealtime), or open-label URLi (n = 73) given 20 min after the meal (postmeal URLi). Blinded CGM was used for up to 14 days before baseline and the 26-week primary endpoint. The primary objective was to compare mealtime URLi and lispro with respect to incremental area under the serum glucose concentration versus time curve from 0 to 2 h (iAUC0–2h) after breakfast.Results: Mealtime URLi was superior in reducing the iAUC0–2h when compared to lispro for breakfast (least squares mean [LSM] difference −28.1 mg·h/L, P = 0.048) and for all meals combined. iAUC0–3h and iAUC0–4h were also reduced. Postmeal URLi resulted in similar postprandial glucose (PPG) control to mealtime lispro, but less optimal PPG control compared to mealtime URLi. Mealtime URLi increased daytime time in range (71–180 mg/dL [3.9–10.0 mmo/L]) (LSM difference = +43.6 min, P = 0.020) and decreased nighttime time in hypoglycemia (LSM difference ≤70 mg/dL [3.9 mmol/L] = −11.5 min, P = 0.009) compared to mealtime lispro.Conclusions: Results of this CGM substudy support the improved PPG control seen with mealtime URLi in the PRONTO-T1D study and show that mealtime URLi resulted in improved daytime time in target range.

Continuous Glucose Monitoring in Adults with Type 1 Diabetes: Real-World Data from the German/Austrian Prospective Diabetes Follow-Up Registry.

Background: To analyze key indicators of metabolic control in adults with type 1 diabetes (T1D) using real-time or intermittent scanning continuous glucose monitoring (rtCGM/iscCGM) during real-life care, based on the German/Austrian/Swiss Prospective Diabetes Follow-up (DPV) registry. Methods: Cross-sectional analysis including 233 adults with T1D using CGM. We assessed CGM metrics by gender, age group (18 to <30 years vs. ≥30 years), insulin delivery method (multiple daily injections vs. continuous subcutaneous insulin infusion [CSII]) and sensor type (iscCGM vs. rtCGM), working days versus weekends, and daytime versus night-time using multivariable linear regression models (adjusted for demographic variables) or Wilcoxon signed-rank test. Results: Overall, 79/21% of T1D patients used iscCGM/rtCGM. Those aged ≥30 years spent more time in range (TIR [70-180 mg/dL] 54% vs. 49%) and hypoglycemic range <70 mg/dL (7% vs. 5%), less time in hyperglycemic range >180 mg/dL (38% vs. 46%) and had a lower glucose variability (coefficient of variation [CV] 36% vs. 37%) compared with adults aged <30 years. We found no significant differences between genders. Multivariable regression models revealed the highest Time In Range (TIR) and lowest time with sensor glucose >250 mg/dL, CV and daytime-night-time differences in those treated with CSII and rtCGM. Glucose profiles were slightly more favorable on working days. Conclusions: In our real-world data, rtCGM versus iscCGM was associated with a higher percentage of TIR and improved metabolic stability. Differences in ambulatory glucose profiles on working and weekend days may indicate lifestyle habits affecting glycemic stability. Real-life CGM results should be included in benchmarking reports in addition to hemoglobin A1c (HbA1c) and history of hypoglycemia.

89-LB: Low Level of Agreement in Evaluation of Continuous Glucose Monitoring Profiles

Nearly 20 years after the introduction of Continuous Glucose Monitoring (CGM) it is clear that CGM reports can effectively guide clinical decision making but the large amount of information contained in the CGM profile may also complicate the evaluation of the profiles. We hypothesized that there would be a relatively low level of agreement in evaluations of CGM-profiles performed by a diverse group of HCPs and patients, with higher level of agreement between diabetes experts. We investigated the interobserver variation in the two groups when asked to subjectively prioritize 9 Ambulatory Glucose Profiles from ‘best’ to ‘worst’ through an internet-based portal (www.glucoseprofile.com). A total of 88 responses were collected. The groups were defined as non-experts (N = 73) and self-evaluated experts (&amp;gt;10 years of experience and &amp;gt; 1 CGM evaluation per week) (N = 15). The interobserver variation between the groups were calculated using Interclass Correlation Coefficients (ICC) showing moderate agreement among the non-experts group (ICC = 0.60) and a good degree of agreement among the diabetes experts (ICC=0.75) [Figure]. Despite standardized CGM metrics and reports there is still a relatively low level of agreement in interpretation and ranking of CGM-profiles even among diabetes experts. This may allow for undesirable variation in diabetes management. More tools are needed to optimize the use of CGM for clinical decision making. Disclosure E. Hachmann-Nielsen: Employee; Self; Novo Nordisk A/S. K. Kvist: Employee; Self; Novo Nordisk A/S. Stock/Shareholder; Self; Novo Nordisk A/S. R.M. Bergenstal: Research Support; Self; Abbott, Boehringer Ingelheim Pharmaceuticals, Inc., Dexcom, Inc., Glooko, Inc., Hygieia, JDRF, Johnson &amp; Johnson Medical Devices Companies, Lilly Diabetes, Medtronic MiniMed, Inc., Merck &amp; Co., Inc., National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk Inc., Roche Diabetes Care, Sanofi. Other Relationship; Self; Abbott, Helmsley Charitable Trust, Hygieia, Lilly Diabetes, Novo Nordisk Inc., Onduo LLC, Sanofi, UnitedHealth Group Inc. Funding Novo Nordisk

102-LB: GP-OSMOTIC: An RCT to Determine the Effect of 3-Monthly Retrospective Continuous Glucose Monitoring (rCGM) on 12-Month HbA1c in Adults with Type 2 Diabetes (T2D) in Primary Care

Introduction: Reviewing rCGM patterns may prompt lifestyle or therapeutic changes to achieve glycaemic targets but evidence for rCGM use in primary care management of T2D is limited. Methods: Two-arm RCT. Participants: Adults with T2D, HbA1c ≥0.5% above target, prescribed ≥2 non-insulin glycemia medications or insulin. Intervention: 1-hour diabetes education and (at 0/3/6/9/12 months): HbA1c assessment + wearing FreeStyle Libre Pro (Abbott) for up to 14 days prior to being discussed at a clinic visit. Physicians were trained in interpreting ambulatory glucose profiles. Control: 3-monthly ‘usual care’ clinic visits + r-CGM device worn (blinded, research data) at 0 and 12 months. Primary outcome: difference in mean HbA1c at 12 months. Secondary outcomes: mean differences in time in range (TIR: 4-10 mmol/L) and diabetes-specific distress (PAID) at 12 months, and HbA1c at 6 months. ITT analysis. Results: In 25 primary care practices, participants were: 299 adults with T2D, aged (mean(SD)) 60(10) years, HbA1c: 8.9(1.2)%, diabetes duration (median(IQR)) of 12(8,20) years. At 12 months, the between-group difference in mean HbA1c was 0.2% (p=0.112). The estimated mean percentage TIR was 8.4% higher in the intervention than the control arm (p=0.004). Diabetes-specific distress did not differ between arms (0.5; p=0.71). At 6 months, HbA1c was significantly lower in the intervention arm (0.5%; p&amp;lt;0.001). We found little evidence of changes in the number of glycemic medications in either arm. Discussion: Use of 3-monthly rCGM in adults with T2D in primary care does not improve HbA1c at 12 months. We showed a statistically and clinically significant reduction in HbA1c at 6 months in the intervention group, as well as significant improvements in TIR at 12 months, with no change in diabetes distress. Our findings suggest the primary impact of r-CGM use on HbA1c in this setting is short term, and not associated with increase in the number of diabetes medications. Disclosure J. Furler: Research Support; Self; Abbott, Sanofi. D.N. O’Neal: None. J. Speight: Research Support; Self; AstraZeneca, Medtronic, Sanofi. Speaker’s Bureau; Self; Novo Nordisk A/S, Roche Diabetes Care. J.E. Manski-Nankervis: Research Support; Self; Australian National Health and Medical Research Council, Boehringer Ingelheim International GmbH, Diabetes Australia, Eli Lilly and Company. Speaker’s Bureau; Self; RACGP. S. Thuraisingam: None. E. Holmes-Truscott: Research Support; Self; Sanofi. Speaker’s Bureau; Self; Novo Nordisk Inc. K.R. De La Rue: None. L.E. Ginnivan: None. R.C. Doyle: None. K. Khunti: Advisory Panel; Self; Amgen Inc., AstraZeneca, Eli Lilly and Company, Merck Sharp &amp; Dohme Corp., Novo Nordisk A/S, Sanofi. Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Merck Sharp &amp; Dohme Corp., Novartis AG, Novo Nordisk A/S, Pfizer Inc., Sanofi-Aventis, Servier, Takeda Pharmaceutical Company Limited. Research Support; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck Sharp &amp; Dohme Corp., Novartis AG, Novo Nordisk A/S, Pfizer Inc., Sanofi-Aventis. Speaker’s Bureau; Self; AstraZeneca, Berlin-Chemie AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Menarini Group, Merck Sharp &amp; Dohme Corp., Novartis AG, Novo Nordisk A/S, Roche Pharma, Sanofi, Servier, Takeda Pharmaceutical Company Limited. M. Catchpool: None. K. Dalziel: None. J.I. Chiang: None. I. Blackberry: None. R. Audehm: Advisory Panel; Self; AstraZeneca, Novartis Pharmaceuticals Corporation. M. Kennedy: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Merck Sharp &amp; Dohme Corp., Novo Nordisk Inc., Sanofi. M.J. Clark: None. A.J. Jenkins: Advisory Panel; Self; Abbott, Australian Diabetes Society, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Mylan. Speaker’s Bureau; Self; Eli Lilly and Company, Novo Nordisk Inc. A.S. Januszewski: None. D. Liew: Advisory Panel; Self; AstraZeneca, Bayer AG. Research Support; Self; AbbVie Inc., AstraZeneca, Bristol-Myers Squibb Company, CSL Behring, Pfizer Inc. P.M. Clarke: None. J.D. Best: Consultant; Self; Abbott. Funding National Health and Medical Research Council of Australia (APP1104241); Sanofi Australia; Abbott Diabetes Care

1089-P: Ultra Rapid Lispro (URLi) Improves Postprandial Glucose (PPG) Control and Time in Range (TIR) in T1D Compared with Humalog (Lispro): PRONTO-T1D Continuous Glucose Monitoring (CGM) Substudy

Ambulatory glucose profiles were evaluated in 269 (22%) patients (pts) in PRONTO-T1D assigned to double-blind URLi (n=97) or lispro (n=99) given at start of the meal, or open-label URLi (n=73) given 20 min after the meal (URLi +20). Primary endpoint was incremental AUC0-2h (iAUC) after breakfast. Blinded CGM (Dexcom G4 Platinum) was worn for 14 days before baseline and week 26. Pts reflected main study population: mean A1C at week 26 was 7.15% - URLi, 7.12% - lispro, 7.35% - URLi+20. Compared to lispro, URLi had significantly smaller breakfast iAUC0-2h with estimated treatment difference (ETD) -28.1 mg.h/dL, p=0.048; more daytime TIR (71-180 mg/dL) ETD +43.6 min, p=0.020; and similar nighttime TIR. Time &amp;lt;50 mg/dL and &amp;gt;180 mg/dL were both numerically lower with URLi in daytime, with less time &amp;lt;50 mg/dL at nighttime vs. lispro: 7.0 vs. 12.6 min, p=0.023. PPG control in pts who marked meal times improved with URLi, while URLi +20 showed greater PPG variability (Figure). Glucose variability via CV and SD metrics was similar between groups, but less glucose variability was noticeable in CGM profiles of pts treated with URLi. When injected at the start of the meal, URLi resulted in significantly better PPG control and increased daytime TIR vs. lispro without increasing time in hypoglycemia. CGM results augment findings from PRONTO-T1D. Disclosure B.W. Bode: Consultant; Self; ADOCIA, Lexicon Pharmaceuticals, Inc., Novo Nordisk Inc. Research Support; Self; Becton, Dickinson and Company, Dexcom, Inc., Diasome Pharmaceuticals, Inc., Eli Lilly and Company, Eyenuk Inc., Insulet Corporation, National Institutes of Health, Novo Nordisk Inc., Sanofi Research &amp; Development, Senseonics, Xeris Pharmaceuticals, Inc. Speaker's Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Janssen Pharmaceuticals, Inc., Novo Nordisk Inc., Sanofi US, Senseonics. Stock/Shareholder; Self; AgaMatrix, Glytec, LLC. D. Cao: Employee; Self; Eli Lilly and Company. R. Liu: Employee; Self; Eli Lilly and Company. Employee; Spouse/Partner; Eli Lilly and Company. T. Hardy: Employee; Self; Eli Lilly and Company. Stock/Shareholder; Self; Eli Lilly and Company. J.M. Bue-Valleskey: Employee; Self; Eli Lilly and Company. Funding Eli Lilly and Company

Ambulatory glucose profile in diabetes-related dementia.

Diabetes-related dementia (DrD), a dementia subgroup associated with specific diabetes mellitus (DM)-related metabolic abnormalities rather than Alzheimer's disease (AD) pathology or cerebrovascular disease, is characterized by less well-controlled glycemia. We investigated the glucose level, variability and stability, and risk of hypoglycemia in DrD to determine characteristic ambulatory glucose profiles (AGP). We obtained AGP for 14 days of 40 patients with AD associated with DM and 19 patients with DrD using a novel sensor-based flash glucose monitoring system (FreeStyle Libre Pro). Despite similar mean glucose and estimated A1c values, the DrD group showed significantly greater glucose variability and higher percentage of time spent in hypoglycemia than the AD associated with DM group. Glucose level and variability correlated significantly and negatively with Mini-Mental State Examination in DrD, but not in AD associated with DM The estimated A1c levels calculated from the 14 days of AGP data significantly correlated with the HbA1c levels measured within 2 months of the insertion of the sensor. DrD has a distinctively different AGP from that of AD associated with DM. Glucose variability and hypoglycemia are more involved in the pathophysiology of DrD than in that of AD associated with DM. The AGP analysis using the flash glucose monitoring system might provide useful information undetected by HbA1c values. Geriatr Gerontol Int 2019; 19: 282-286.

Differences of FreeStyle Libre Flash Glucose Monitoring System and Finger Pricks on Clinical Characteristics and Glucose Monitoring Satisfactions in Type 1 Diabetes Using Insulin Pump.

Background:To evaluate the different experience of freestyle libre and finger pricks on clinical characteristics and glucose monitoring satisfaction (GMS) in patients with type 1 diabetes (T1D) using insulin pump (IP).Methods:A prospective study was carried out on 47 (aged 17-21 years) T1D, who used conventional finger-pricking method for self-testing the glucose. The experiments were conducted between March 2018 and September 2018. For carrying out the study, the flash glucose monitoring (FGM) sensors were placed on each participant, at the baseline visit, by a trained diabetes educator. Furthermore, to determine the total number of scans conducted during the study period, the respective ambulatory glucose profiles were generated by computing the data collected from the sensors. In addition, a trained interviewer handed over the GMS questionnaire to each patient, at the baseline and at 12 weeks of the study.Results:In comparison to the baseline (finger pricks), various parameters such as: HbA1c (P = .042), hypoglycemia (P = .001), mean capillary glucose (P = .004), total daily insulin dose (P = .0001), percentage of bolus insulin (P = .0001), daily bolus frequency (P = .0001), and daily carbohydrates intake (P = .0001) showed a significant improvement at 12 weeks. Similarly, substantial augmentation was noticed, in the sub domains of GMS, that is, openness (P = .0001), emotional burden (P = .0001), behavioral burden (P = .0001), and trust (P = .0001) at 12 weeks as compared to baseline. Overall, total GMS score at baseline was 1.72 ± 0.37, which increased up to 3.41 ± 0.49 (P = .0001) in the time period of 12 weeks. The HbA1c (r2 = 0.45), hypoglycemia (r2 = 0.58), and the mean number of FGM scans, exhibited a negative correlation, while GMS (r2 = 0.52) and the mean number of FGM scans, exhibited a positive correlation.Conclusion:The frequency of hypoglycemia, HbA1c level, capillary glucose, daily carbohydrates intake decreased, while the total daily insulin dose, daily bolus insulin and total GMS score increased with the use of FGM scanning for 12 weeks.

Evaluation of FreeStyle Libre Flash Glucose Monitoring System on Glycemic Control, Health-Related Quality of Life, and Fear of Hypoglycemia in Patients with Type 1 Diabetes.

Background/objectives:In the current era of modern technology and the development of smart devices such as the flash glucose monitoring (FGM) systems, patients can easily monitor their glucose levels more frequently without any inconvenience. In this study, we evaluate the effect of FreeStyle Libre FGM system on glycemic control, hypoglycemia, health-related quality of life (QoL), and the fear of hypoglycemia (FOH) among children and young people with type 1 diabetes (T1D).Design and methods:A prospective study was conducted at the Diabetes Treatment Center, Prince Sultan Military Medical City, Riyadh, Saudi Arabia, between January 2017 and May 2017 on 47 (aged 13-19 years) registered patients with T1D who used conventional finger-pricking method for self-testing the glucose. At baseline visit, the FGM sensors were placed on each participant by a trained diabetes educator. The data collected from the sensors were computed to generate the respective ambulatory glucose profiles so as to determine the total number of scans conducted during the study period. At the baseline and at 3 months of the experiment, a trained interviewer administered the questionnaire Hypoglycemia Fear Survey-Child Version (HFS-C) and PedsQL 3.0 (QoL questionnaire) to each patient. The age, sex, weight, height, adjusted body mass index, duration of diabetes, treatment modality, and glycosylated hemoglobin A1c (HbA1c) levels of each patient were recorded.Results:As compared with the baseline, a significant improvement was noted in the behavior of FOH (P = .0001), worry (P = .0001), QoL (P = .002), HbA1c level (P = .008), and hypoglycemia (P = .023) at 3 months. Significant improvement was noted in the behavior (P = .0001), worry (P = .0001), QoL (P = .003), HbA1c level (P = .014), and hypoglycemia (P = .001) among the multiple-dose insulin injection–treated patients as compared with baseline. Significant improvement was noted in the behavior (P = .0001), worry (P = .0001), and hypoglycemia (P = .001) among the insulin pump–treated patients as compared with baseline. A positive correlation was recorded in the behavior (r = .47; P < .001), QoL (r = .70; P < .001), and the mean number of FGM scans. A negative correlation was recorded in the worry (r = −.43; P = .002), HbA1c level (r = −.58; P < .001), hypoglycemia (r = −.65; P < .001), and the mean number of FGM scans.Conclusions:The frequent use of FGM scanning reduced the frequency of hypoglycemia, HbA1c level, and worry and increased the behavior and QoL. As compared with self-testing by the conventional finger-pricking method, the use of FGM increased the frequency of self-testing and thus diabetes control.

Glucose homeostasis during ramadan fasting: First case series illustrated by flash glucose monitoring and ambulatory glucose profiling

Background: The impact of fasting during the month of Ramadan, practiced by adult Muslims, on glucose homeostasis has attracted much attention recently with view to understanding the metabolic price of fasting and to help plan rational management. The flash glucose monitoring (FGM) expressed as ambulatory glucose profiles (AGP) provides a minimally invasive yet comprehensive insight into blood glucose (BG) changes in relationship to various physiological and behavioral factors. Objectives: To investigate the BG homeostasis during Ramadan fasting in a group of individuals with different states of glucose tolerance. Methods: Eight individuals who were fasting during Ramadan were studied by FGM using the Abbott's FreeStyle® Libre™ system. They included individuals with normal glucose tolerance during pregnancy (1), prediabetes (2), postbariatric hypoglycemia (1) and type 2 diabetes mellitus (4). Results: In the normal pregnancy AGP's fluctuated minimally around meals with some asymptomatic low BG readings on prolonged fasting. In those with prediabetes, most of the daytime BG were within normal but there was a minimal post-prandial rises and some asymptomatic lower readings on prolonged fasting too. In the case of the patient with history of post-bariatric hypoglycemia, daytime fasting periods had perfectly stable normal BG. However, marked early postprandial hyperglycemia occurred in the evening followed by a short-lived symptomatic hypoglycemia. In the 4 patients with diabetes, AGP showed high glucose exposure, wide variation and marked instability after both traditional meals of dawn time (Suhor) and sunset (Iftar) particularly in the later. A variably slow downward trend throughout the day was observed. The differences in the AGP's reflected both biological and behavioral differences between patients within the general picture. AGP's before, during and after Ramadan in 3 patients revealed distinctly-different profiles reflecting the Middle Eastern meal pattern, Ramadan meal pattern and Eid feasting respectively. For patients these findings were discussed with them and used to plan glycemic management. Conclusions: This is the first comprehensive demonstration of glucose changes during Ramadan fasting using AGP. The visually illustrated data give insights into glucoses homeostasis in diabetes and related disorders throughout whole day of Ramadan. This may help inform therapeutic decisions on individual basis and help plan future studies.

Diurnal Glycemic Patterns during an 8-Week Open-Label Proof-of-Concept Trial of Empagliflozin in Type 1 Diabetes.

BackgroundWe recently reported improved glycemic control with reduced insulin dose in subjects with type 1 diabetes treated with the sodium glucose co-transporter-2 inhibitor empagliflozin. To further characterize the effects, we analyzed diurnal glycemic patterns by continuous glucose monitoring (CGM).MethodsIn an 8-week single-arm open-label pilot study of empagliflozin, we compared ambulatory glucose profiles produced from CGM data during 2-week intervals in a placebo run-in baseline period, end-of-treatment, and post-treatment. Change in glycemic exposure was evaluated by area under the median curve according to time of day (AUCTOTAL 12:00am-11:55pm; AUCDAY 7:05am-10:55pm, AUCNIGHT 11:00pm-7:00am), as well as glycemic variability, glycemic stability and time-in-target (≥70 to ≤140mg/dL).ResultsThe 40 patients (26 on insulin pump) were aged 24±5 years and BMI 24.5±3.2 kg/m2. Consistent with the observed HbA1c decrease (8.0±0.9% to 7.6±0.9%, p<0.0001), normalized AUCTOTAL CGM decreased from 153.7±25.4 to 149.0±30.2mg/dL∙h at end-of-treatment (p = 0.31), and significantly increased post-treatment (164.1±29.5mg/dL∙h, p = 0.02). The numerical decrease in normalized AUCNIGHT (152.0±36.6 to 141.9±34.4mg/dL∙h, p = 0.13) exceeded AUCDAY (154.5±24.5 to 152.6±30.4mg/dL∙h, p = 0.65). Trends toward lower glycemic variability (83.1±18.9 to 75.6±28.6mg/dL, p = 0.06) and little change in glycemic stability (10.8±3.6 to 10.3±4.5mg/dL/h, p = 0.51) were observed. When empagliflozin was discontinued, these worsened relative to baseline (89.3±19.3mg/dL, p = 0.04 and 11.8±3.7mg/dL/hr, p = 0.08). Time-in-target numerically increased (40.2±11.9 to 43.1±13.5%, p = 0.69) at end-of-treatment but reversed post-treatment. Findings were similar on stratification of pump and MDI subjects.ConclusionsWe observed that empagliflozin was associated with patterns of improved nighttime glycemia more prominent than daytime.Trial RegistrationClinicaltrials.gov NCT01392560

Long-term continuous glucose monitoring with microdialysis in ambulatory insulin-dependent diabetic patients

Summary The glucose concentration in the extracellular space of subcutaneous adipose tissue closely mirrors the blood glucose concentration. With a microdialysis technique, we undertook continuous ambulatory monitoring of adipose tissue glucose in 17 insulin-dependent diabetic patients with labile glycaemic control. The aims of the study were to investigate performance of the microdialysis device and to evaluate whether consecutive 24 h glucose profiles could be used to adjust insulin therapy. A microdialysis probe was implanted subcutaneously, perfused by a portable microinfusion pump, and dialysate fractions were collected every 1 or 2 h for 75 h. The mean (SE) tissue dialysate glucose concentration was 93 (3)% of the concentration in venous plasma, and variations in adipose tissue glucose closely paralleled changes in plasma glucose. Mean 24 h tissue glucose concentration correlated significantly with glycosylated haemoglobin (HbA 1c; r=0·62, p<0·01). Most patients had a reproducible daily pattern of glucose swings, and in more than half the patients consecutive ambulatory glucose profiles were almost superimposed. When patients' insulin therapy was adjusted on the basis of ambulatory glucose monitoring, HbA 1c decreased by almost 2% (p < 0·01), and this decrease lasted for at least 9 months. Microdialysis of adipose tissue can be used for continuous long-term monitoring of glucose concentrations in diabetic patients during ordinary daily life. Daily glucose profiles are often reproducible and the recordings may thus be used for individual tailoring of insulin therapy to improve glycaemic control.

The relationship between large-for-gestational-age infants and glycemic control in women with gestational diabetes

In this prospective study 246 women with gestational diabetes were followed up to determine the characteristics of metabolic control associated with large-for-gestational-age infants. Memory-based reflectance meters were used for self-monitoring blood glucose. Ambulatory glucose profiles were produced to characterize glycemic control levels throughout pregnancy. With these novel approaches to the collection and representation of glucose data, the severity of glucose intolerance (hyperglycemia) was found to be associated with both maternal and neonatal morbidity in terms of infant size and cesarean section rate. By use of hierarchical cluster analysis to identify three groups on the basis of control levels (low <87 mg/dl, mid 87 to 105 mg/dl, high >105 mg/dl) we were able to show a positive outcome in the low group with reduced rates of large-for-gestational-age (2%) and macrosomatic (0%) infants. Furthermore, we showed that as mean blood glucose levels and instability in glycemic control increased from group to group, incidence of large-for-gestational-age and macrosomatic infants increased. Whereas obesity increased the relative risk of adverse neonatal outcome, type of treatment (insulin versus diet) did not appear to be significant. Appropriately monitored toward stability within a narrow range to achieve tight metabolic control, ambulatory glycemia in pregnancy is associated with a decreased risk of maternal and fetal complications.