bluuebunny/crossref_metadata_2025_split huggingface dataset:
891-P: Hypoglycemia Prevention Behaviors Prevent Moderate Hypoglycemic Events: The REPLACE-BG Trial
Authors: CRAWFORD MARGARET A. , WHITE MARTHA M. , STRONG DAVID R. , PIERCE JOHN P. 
Published: June 2019

Background: Continuous glucose monitoring (CGM) provides real-time glucose levels and alarms for hypoglycemia. We analyze CGM data from the REPLACE-BG trial, which had 6 months of CGM data on people with well controlled type 1 diabetes (T1D), to characterize hypoglycemic events and evaluate their association with hypoglycemia-related behaviors.
Methods: We conducted a psychometric analysis of the Hypoglycemia Fear Survey- Behavior scale to identify unique hypoglycemia behavior constructs. We identified and categorized hypoglycemic events in CGM data as mild (min glucose &lt;70 mg/dL) and moderate (min glucose &lt;50 mg/dL) and used ANOVA to evaluate differences in the frequency and duration of events by high and low score categories of hypoglycemia behavior constructs. We used multivariate linear regression to evaluate the association between hypoglycemia behavior constructs and 1) duration of moderate hypoglycemic events and 2) proportion of moderate hypoglycemic events.
Results: We separated the HFS-B into three scales: hypoglycemia avoidance, reaction, and prevention. In low vs. high hypoglycemia prevention score categories, the duration of moderate hypoglycemic events was significantly longer (73 vs. 66 minutes, p&lt;0.05) and proportion of moderate hypoglycemic events was higher (22.4 vs. 20.1, p&lt;0.1). In multivariate models that included all three hypoglycemia behavior scales, hypoglycemia prevention behavior was significantly, inversely associated with 1) duration of moderate hypoglycemic events (β= -6.9, SE= 2.2, p&lt; 0.01) and 2) proportion of moderate hypoglycemic events (β= -2.2, SE= 0.7, p-value &lt; 0.01).
Conclusion: Hypoglycemia is common in T1Ds. The increased likelihood of engaging in hypoglycemia prevention behaviors reduces the frequency and duration of dangerous moderate hypoglycemic events. Analyzing CGM data in its continuous form reveals the frequency and characteristics of individual hypoglycemic events.

Disclosure
M.A. Crawford: Employee; Self; Dexcom, Inc. M.M. White: None. D.R. Strong: None. J.P. Pierce: None.
894-P: The Risk for Type 2 Diabetes beyond Age: Contributors to the FINDRISC-Score in Each Age Category
Authors: EHRMANN DOMINIC , ETTER TOBIAS J. , WEISSMANN JOERG , KULZER BERNHARD , HERMANNS NORBERT 
Published: June 2019

With increasing age, the risk for type 2 diabetes increases. Little is known about the relative importance of other risk factors for different age groups. Pharmacy customers in Germany completed the FINDRISC questionnaire. An ANOVA with age category as between factor and the age-adjusted FINDRISC-score as the dependent variable was conducted. Separate linear regression analyses for each age group were conducted to predict the total risk score from the risk factors. A total of 292 people participated. The ANOVA revealed that while the age-adjusted risk score for the first age category (&lt; 35 years) was significantly different from all other age categories (p &lt; .01 for all comparisons), there were no differences between the different age categories ≥ 35 years (p &gt; .35 for all) indicating a similar risk exposition across these age groups. Results of the linear regression analyses (Table) revealed that the relative importance of genetic factors in younger people (&lt; 35 years) is more pronounced and relatively more important than other factors. Additionally, fat distribution played an important role only in the youngest age groups. In older people, the importance of genetic factors for the overall risk score dropped while previously elevated blood sugar levels were more important. Understanding possible risk factors beyond age are helpful to develop targeted educational material or raise awareness for specific age groups.

Disclosure
D. Ehrmann: Advisory Panel; Self; Medtronic. Speaker's Bureau; Self; Abbott, Berlin-Chemie AG, Dexcom, Inc. T.J. Etter: Employee; Self; Roche Diabetes Care. J. Weissmann: Employee; Self; Roche Diabetes Care. B. Kulzer: Advisory Panel; Self; Ascensia Diabetes Care, Berlin-Chemie AG, Medtronic, Novo Nordisk Inc., Roche Diabetes Care. Research Support; Self; Abbott, Berlin-Chemie AG, Roche Diabetes Care. Speaker's Bureau; Self; Abbott, Ascensia Diabetes Care, Berlin-Chemie AG, Eli Lilly and Company, Novo Nordisk Inc., Roche Diabetes Care. N. Hermanns: Advisory Panel; Self; Abbott. Board Member; Self; Eli Lilly and Company. Research Support; Self; Abbott, Berlin-Chemie AG, Dexcom, Inc., Roche Diabetes Care. Speaker's Bureau; Self; Berlin-Chemie AG, Dexcom, Inc., Novo Nordisk A/S.

Funding
Roche Diabetes Care GmbH
895-P: Effects of Dapagliflozin, Metformin, or Exercise on Markers of Cardiometabolic Risk: The PRE-D Trial
Authors: FÆRCH KRISTINE , BLOND MARTIN B. , AMADID HANAN , NIELSEN LEA BRUHN , TVERMOSEGAARD MARIA , RIED-LARSEN MATHIAS , KARSTOFT KRISTIAN , PERSSON FREDERIK , JØRGENSEN MARIT E. 
Published: June 2019

We assessed effects of dapagliflozin, metformin or exercise on markers of cardiometabolic health in individuals with prediabetes.
Methods: 120 participants were randomized to 13 weeks to either 1) dapagliflozin (DAP, 10 mg once daily); 2) metformin (MET, 850 mg twice daily); 3) exercise (EXE, interval training 5x30 min/week); or 4) control (CON, no treatment). Intention-to-treat analyses were conducted (baseline-adj.).
Results: 44% were men. At baseline, the median (Q1; Q3) age was 62 (54; 68) years, HbA1c 41 (39; 43) mmol/mol (5.9 (5.7; 6.1)%), BMI 30.8 (28.6; 34.3) kg/m2, fat mass 34.5 (28.7; 40.7) kg, waist circumference (WC) 104 (97; 113) cm, blood pressure 131/86 (123/79; 144/91) mmHg, cardiorespiratory fitness (CRF) 23.0 (20.4; 27.7) mLO2/kg/min, total cholesterol 5.1 (4.2, 5.9) mmol/L, HDL 1.3 (1.1; 1.5) mmol/L, VLDL 0.6 (0.4; 0.8) mmol/L and triglycerides 1.3 (0.9; 1.8) mmol/L. EXE led to a small reduction (1.1 kg) in fat mass which was also reflected in the change in BMI and weight (Table 1). Small reductions of 2.4 cm in WC were observed in DAP and EXE. In addition, EXE increased CRF by 2.8 mLO2/kg×min and decreased triglycerides and VLDL by 12-13%. DAP increased HDL by 0.1 mmol/l.
Conclusion: DAP and EXE led to minor improvements in body composition and lipids. EXE improved cardiorespiratory fitness; otherwise the risk profile of the participants was largely unaffected by the interventions.

Disclosure
K. Færch: Research Support; Self; Ascensia Diabetes Care, AstraZeneca, Unilever. Stock/Shareholder; Self; Novo Nordisk A/S. M.B. Blond: None. H. Amadid: None. L.B. Nielsen: None. M. Tvermosegaard: None. M. Ried-Larsen: Other Relationship; Self; Novo Nordisk A/S. K. Karstoft: Employee; Self; Novo Nordisk A/S. F. Persson: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Novo Nordisk A/S. Research Support; Self; AstraZeneca, Sanofi. Speaker's Bureau; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Sanofi. M.E. Jørgensen: Research Support; Self; Amgen Inc., AstraZeneca, Danish Diabetes Association, Sanofi-Aventis. Stock/Shareholder; Self; Novo Nordisk A/S.

Funding
Novo Nordisk Foundation; AstraZeneca
903-P: Unique Cardiovascular Risk Stratification Using Prediabetes Metrics in High-Risk South Asian Cohort
Authors: SHEARER JENNIFER L. , JOSAN KIRANBIR , KHANDELWAL ABHA , NALLAMSHETTY SHRIRAM , ABBASI FAHIM , DASH RAJESH 
Published: June 2019

Background: Elevated 1 hour plasma glucose (&gt;155mg/dl) and glucose curve shape are predictive markers of diabetes risk. We evaluated varying patterns of impaired glucose tolerance and associated CVD risk.
Methods: At Stanford’s South Asian Translational Heart Initiative, 260 patients were evaluated for diabetic and CVD risk: OGTT with insulin, lipid panel, HbA1c, blood pressure, BMI, QRisk2 (10-year CVD risk), inflammatory markers, and FHx. Glucose curve “shape” was categorized by phase changes and time of curve peak.
Results: Classification showed 78.3% of patients were prediabetic and 5.2% had normal glucose tolerance (NGT) but elevated 1 hour glucose. These subgroups also exhibited more unclassified and monophasic 60 min glucose peak (Mono60) shapes compared to the total population (83.8% vs. 51.9%, p &lt;0.01). Mono 60 patients had significantly higher fasting and 2 hour glucose, insulin levels, and QRisk2 (16% vs. 12%, p&lt;0.01) than Mono30. The median CRP of Mono60 was higher than Mono 30 (1 vs. 1.5, p=0.02). A “dose-dependent” relationship between prediabetic criteria and average glucose area under curve (AUC) was observed; elevated 1 hour glucose further stratified prediabetic severity (Figure 1).
Conclusion: Mono60 glucose patterns exceed the CVD risk stratification of prediabetes alone and may indicate a need for more aggressive medical therapy to prevent diabetes and CVD progression.

Disclosure
J.L. Shearer: None. K. Josan: None. A. Khandelwal: None. S. Nallamshetty: None. F. Abbasi: None. R. Dash: None.
905-P: Safety, Adherence, and Treatment Satisfaction with Dapagliflozin, Metformin, or Exercise in Individuals with Prediabetes: The Pre-D Trial
Authors: AMADID HANAN , BLOND MARTIN B. , BRUHN LEA , CLEMMENSEN KIM K. , VAINØ CAMILLA T. , PERSSON FREDERIK , JØRGENSEN MARIT E. , FÆRCH KRISTINE 
Published: June 2019

Introduction: Safety, adherence and treatment satisfaction to interventions with dapagliflozin, metformin or exercise in individuals with prediabetes defined by the HbA1c criterion were studied in the randomized controlled PRE-D trial.
Methods: 120 participants were randomized 1:1:1:1 to 13 weeks of either: (1) dapagliflozin (DAP, 10 mg daily); (2) metformin (MET, 1700 mg daily); (3) exercise (EXE, 5x30 min/week); or (4) control (CON, no treatment). Adverse events (AE) were collected during the entire study. Satisfaction with the interventions was assessed at 6 and 13 weeks using questionnaires. Adherence was assessed at 6 and 13 weeks by pill count in DAP and MET and each week by uploaded training data in EXE. Comparisons between groups were performed by ANOVA and chi-square tests.
Results: At baseline, the median (Q1;Q3) HbA1c was 41 (39;43) mmol/mol (5.9 (5.7;6.1)%); age 62 (54;68) years, and 44% were men. Drop outs were 2 in DAP, 1 in MET, 3 in EXE and 2 in CON. One serious AE occurred in CON (cancer). 40% of the participants experienced at least one AE during the trial (15 in DAP, 22 in MET, 7 in EXE and 4 in CON (DAP vs. MET: P=0.111; MET vs. EXE: P&lt;0.001)). Most AEs were known side-effects of the two medications; urogenital symptoms in DAP, and gastrointestinal symptoms in MET. In all groups, median (Q1;Q3) adherence was high (DAP 100.0 (97.7;100.4)%; MET 96.0 (91.4;98.3)%; EXE 95.9 (89.9;103.2)% (session duration) and 94.5 (90.3;101.1)% (session completion)). Almost all participants in the EXE group were satisfied with their allocated intervention, while this was only true for half of the participants in the CON, DAP and MET groups. Most participants would have preferred allocation to the EXE intervention.
Conclusion: In individuals with prediabetes, treatment with DAP is safe and did not result in more side-effects than treatment with MET. Adherence to all interventions was high, although the most preferred intervention was the EXE intervention.

Disclosure
H. Amadid: None. M.B. Blond: None. L. Bruhn: None. K.K. Clemmensen: None. C.T. Vainø: None. F. Persson: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Novo Nordisk A/S. Research Support; Self; AstraZeneca, Sanofi. Speaker's Bureau; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Sanofi. M.E. Jørgensen: Research Support; Self; Amgen Inc., AstraZeneca, Danish Diabetes Association, Sanofi-Aventis. Stock/Shareholder; Self; Novo Nordisk A/S. K. Færch: Research Support; Self; Ascensia Diabetes Care, AstraZeneca, Unilever. Stock/Shareholder; Self; Novo Nordisk A/S.
906-P: Safety and Efficacy of Continuous Glucose Monitoring at an ADA Camp
Authors: SOSNOWSKI ANIELA , SCHMELTZ LOWELL 
Published: June 2019

Personal use of Continuous Glucose Monitor (CGM) technology has increased as a tool to optimize glycemic control. CGM use at ADA camps has also risen over the past few years, however, some campers opt not to use their home CGM at camp as finger stick blood sugars were standard for monitoring glycemic control per camp protocols. At camp, kids are exposed to various levels of activity and different foods leading to variable insulin requirements compared to home regimens. This, in turn, could increase the number of potentially dangerous hypoglycemic episodes at camp if blood glucoses (BG) are not tightly monitored. The safety and efficacy of CGM in an ADA camp setting has not yet been published. This retrospective case-control quality review was performed on camper data from ADA Camp MIDICHA 2017 summer session. It was hypothesized that campers using CGM would have fewer severe glucose excursions (hypo- or hyperglycemia) compared to campers not using CGM. Of the 483 campers, 36 campers used CGM at camp. Another 36 campers (age/gender matched) who did not use CGM were identified as controls. Campers were further matched based on insulin administration method (pump vs. injections) and cabin (to reduce activity variability). BG data including average BG levels, hypoglycemic events (BG &lt;50, &lt;70, &lt;80 mg/dL), and hyperglycemic events (BG &gt;250, &gt;300, and &gt;400 mg/dL) were collected and analyzed. There was no significant difference in average BG levels of campers using CGM and those not using CGM (BG=179.6 vs. 178.53 mg/dL; p=0.8832). Binary logistics regressions were used to generate odds ratios for glycemic event data. Campers using CGM had a 74% lower relative risk of having at least one severe hypoglycemic episode (BG &lt;50) during their week at camp compared to controls (14% vs. 38%; OR: 0.26 (95% CI: 0.09, 0.73); P = 0.0012). No significant differences were noted in hyperglycemia frequency amongst campers using CGM and controls. Therefore, the use of CGM should be encouraged in the camp setting to reduce the incidence of severe hypoglycemia.

Disclosure
A. Sosnowski: None. L. Schmeltz: Advisory Panel; Self; Sanofi. Speaker's Bureau; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Dexcom, Inc., Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk Inc.
91-OR: Stem Cell-Derived Tissue-Associated Regulatory T Cells Suppress the Activity of Pathogenic Immune Cells in Autoimmune Diabetes
Authors: SONG JIANXUN J. 
Published: June 2019

The auto antigen (Ag)-specific regulatory T cells (Tregs) from pluripotent stem cells (PSCs), i.e., PSC-Tregs, have the ability to suppress autoimmunity. PSC-Tregs can be programmed to be tissue-associated and to infiltrate into local inflamed tissues to suppress autoimmune responses after adoptive transfer. Nevertheless, the mechanisms by which the auto Ag-specific PSC-Tregs suppress the autoimmune response remain to be fully elucidated. In this study, we generated the functional auto Ag-specific Tregs from the induced PSC (iPSCs), i.e., iPSC-Tregs, and investigated the underlying mechanisms of autoimmunity suppression by these Tregs in a type 1 diabetes (T1D) murine model. A double transgenic (Tg) mouse model of T1D was established in F1 mice in which the first generation of RIP-mOVA Tg mice that were crossed with OT-I T cell receptor (TCR) Tg mice was challenged with vaccinia viruses expressing OVA (VACV-OVA). We show that adoptive transfer of OVA-specific iPSC-Tregs greatly suppressed autoimmunity in the animal model and prevented the insulin-secreting pancreatic β cells from destruction. Further, we demonstrate that the adoptive transfer significantly reduced the expression of ICAM-1 in the diabetic pancreas and inhibited the migration of pathogenic CD8+ T cells and the production of the pro-inflammatory IFN-γ in the pancreas. These results indicate that the stem cell-derived tissue-associated Tregs can robustly accumulate in the diabetic pancreas, and through down-regulating the expression of ICAM-1 in the local inflamed tissues and inhibiting the production of pro-inflammatory cytokine IFN-γ, suppress the migration and activity of the pathogenic immune cells that cause T1D.

Disclosure
J.J. Song: None.

Funding
American Diabetes Association (1-16-IBS-281); National Institutes of Health (R01AI121180, R21AI109239)
910-P: Improved Accuracy of 14-Day Factory-Calibrated FreeStyle Libre System with New Glucose Algorithm
Authors: KARINKA SHRIDHARA ALVA , BAILEY TIMOTHY S. , BRAZG RONALD L. , BUDIMAN ERWIN S. , CASTORINO KRISTIN , CHRISTIANSEN MARK P. , LILJENQUIST DAVID R. , LIU HANQING 
Published: June 2019

We evaluated the accuracy of FreeStyle Libre 14-day system with new glucose algorithm in adults ages 18 years or older. This was a non-randomized, multi-center, single-arm study that enrolled 144 subjects with types 1 and 2 diabetes on intensive insulin therapy at 5 U.S. sites. Subjects participated in 3 clinic sessions of up to 10 hours each over the 14- day wear period to obtain comparator data. Glucose concentrations were manipulated to obtain glucose concentrations across the system dynamic range of 40-500mg/dL. System performance was evaluated in terms of percent accuracy with respect to venous plasma reference using YSI2300. Accuracy was characterized as the proportion of sensor results that were within ±15%, ± 20% of their paired YSI values for glucose levels ≥ 70 mg/dL or within ± 15 mg/dL, ± 20 mg/dL of YSI for glucose levels &lt; 70 mg/dL. Other accuracy metrics such as mean bias and mean absolute relative difference (MARD) of the FreeStyle Libre System with respect to YSI were also evaluated and are presented in Table 1.
FreeStyle Libre System with new algorithm showed 92.8% of the results within ±20mg/dL/±20% of the venous plasma reference with an overall MARD of 9.2% based on the data from 144 subjects with evaluable sensors.

Disclosure
S.A. Karinka: Employee; Self; Abbott. T.S. Bailey: Advisory Panel; Self; Abbott. Consultant; Self; Capillary Biomedical, Inc., Eli Lilly and Company, Medtronic, Novo Nordisk Inc., Sanofi. Research Support; Self; Abbott, Ascensia Diabetes Care, Becton, Dickinson and Company, Boehringer Ingelheim Pharmaceuticals, Inc., Calibra Medical, Capillary Biomedical, Inc., Companion Medical, Dance Biopharm Holdings Inc., Dexcom, Inc., Diasome Pharmaceuticals, Inc., Eli Lilly and Company, GlySens Incorporated, Kowa Pharmaceutical Europe Co. Ltd., Lexicon Pharmaceuticals, Inc., Medtronic, Novo Nordisk Inc., POPS! Diabetes Care, POPS! Diabetes Care, Sanofi, Senseonics, vTv Therapeutics, Xeris Pharmaceuticals, Inc., Zealand Pharma A/S. Speaker's Bureau; Self; Abbott, MannKind Corporation, Medtronic, Novo Nordisk Inc., Sanofi US, Senseonics. R.L. Brazg: Research Support; Self; Abbott, Ascensia Diabetes Care, Eli Lilly and Company, Gan & Lee Pharmaceuticals, Janssen Pharmaceuticals, Inc., Medtronic, Novo Nordisk Inc., ProSciento, Roche Diagnostic USA, Xeris Pharmaceuticals, Inc. E.S. Budiman: Employee; Self; Abbott. Stock/Shareholder; Self; Abbott, AbbVie Inc. K. Castorino: Consultant; Self; Abbott. Research Support; Self; Abbott, Dexcom, Inc., Drawbridge, Novo Nordisk Inc., Sanofi US. M.P. Christiansen: Research Support; Self; Abbott, Biolinq, Dexcom, Inc., Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Medtronic MiniMed, Inc., Novo Nordisk A/S, Sanofi-Aventis, Xeris Pharmaceuticals, Inc. D.R. Liljenquist: None. H. Liu: Employee; Self; Abbott Laboratories.

Funding
Abbott Diabetes Care
912-P: T2D Users of a Digital Diabetes Management System Experience an Increase of In-Range Glucose Levels Linked to App Engagement
Authors: HERSHCOVITZ YIFAT , DAR SHARON , FENIGER EITAN 
Published: June 2019

Time in-range blood glucose level (70-140 mg/dl) is one of the greatest challenges when managing diabetes. Digital engagement can play a pivotal role in the care of patients with diabetes and other chronical conditions, potentially improving patient’s compliance. In this study DarioTM Blood Glucose Monitoring System (BGMS) users were evaluated to examine whether higher App engagement contributes to better diabetes management.
Method: A retrospective data evaluation study was performed on the DarioTM cloud database. A population of active type 2 diabetic (T2D) users (&gt;15 measurements per month on average) was evaluated. The study assessed the ratio of in-range blood glucose readings (70-140 mg/dL) as a function of App engagement level for 6 months as recorded in the database compared to first 30 days as a starting point of analysis.
Results: A population of 4917 T2D non-insulin users measuring more than 15 times per month on average during 6 months in a row was evaluated. The ratio of in-range (70-140 mg/dL) readings was increased following 3 months in correlation to the level of tagging meal reference/carbs/physical activity occurrences (4.0%, 9.1% and 11.9% for tagging 0-1, 1-2 and &gt;2 times per day on average, respectively) and sustained for 6 months (3.1%, 7.0% and 12.2%, respectively). In subgroup analysis focusing on users entering their meal reference, high correlation was observed following 3 months with an increase of in-range measurements in 4.6%, 8.4% and 12.0% for 0-1, 1-2 and &gt;2 meal reference tagging per day on average, respectively, and maintained stability over 6 months period (3.2%, 7.4%, and 12.5%, respectively).
Conclusion: The combination of a glucose meter, an App and engaged user may promote better behavioral modification which enhance and sustain adherence to diabetes management.

Disclosure
Y. Hershcovitz: Employee; Self; DarioHealth. S. Dar: Employee; Self; DarioHealth. E. Feniger: Employee; Self; DarioHealth.
913-P: Reduction of Blood Glucose Average Less than 140mg/dl in People with Type 2 Diabetes Using a Digital Diabetes Management System
Authors: HERSHCOVITZ YIFAT , DAR SHARON , FENIGER EITAN 
Published: June 2019

Patients with high average of blood glucose levels (&gt;180mg/dL) are at high risk for developing clinical complications. Digital engagement can play a pivotal role in the care of patients with diabetes, assisting to reduce their blood glucose average (BG avg) over time. The study reviews DarioTM user’s ability to sustain BG avg&lt;140 mg/dL over time while using the DarioTM Blood Glucose Monitoring System (BGMS).
Method: A retrospective data evaluation study was performed on the DarioTM cloud database. A population of active T2D users that continuously measured for 6 months was evaluated. The study assessed their BG avg and estimated A1C (eA1C) values based on blood glucose readings as recorded in the database. Values were calculated in periods of 3 and 6 months and compared to their first 30 days as a starting point analysis.
Results: A group of 1248 Dario BGMS T2D active users (1.98 measurements per day on average during 6 months in a row) with BG avg &gt;140mg/dL (eA1C&gt;6.5) was evaluated. All (100%) reduced their BG avg along 6 months on average. A group of 31% (387) achieved BG avg of &lt;140 mg/dL (eA1C&lt;6.5) following 3 months showing 19% reduction on average from baseline (132.38±13.36 vs.162.79±25.41 mg/dL and eA1C 6.24±0.46 vs. 7.30±0.88) and sustained their glycemic control during a 6 months period (131.57±13.86 mg/dL and eA1C 6.21±0.48). Subgroup analyses of 568 non-insulin users revealed that 40% (226) achieved a BG avg &lt;140 mg/dL following 3 months (131.95±13.21 vs.161.67±24.18 mg/dL and eA1C 6.22±0.46 vs. 7.26±0.84) and sustained for 6 months period (131.03±13.70 mg/dL and eA1C 6.19±0.47). Along the 6 months period, hypo events (&lt;50mg/dL) per user per month on average remained stable.
Conclusion: Patients using a digital diabetes management platform have the potential to promote behavioral modification and sustain adherence to diabetes management, demonstrating better glycemic control.

Disclosure
Y. Hershcovitz: Employee; Self; DarioHealth. S. Dar: Employee; Self; DarioHealth. E. Feniger: Employee; Self; DarioHealth.