bluuebunny/crossref_metadata_2025_split huggingface dataset:
893-P: A Smartphone App-Based Lifestyle Intervention for Weight Loss, Improvement of Hemoglobin A1c (A1c), and Prediabetes
Authors: VAZ CHERIE LISA , CARNES NICHOLAS , ZHAO HUAQING , WILLIAMS KEVIN JON 
Published: June 2019

We previously reported the successful RCT of our smartphone app-based lifestyle intervention in overweight or obese subjects (ClinicalTrials.gov NCT02742662). Our intervention met the prespecified primary outcome of clinically meaningful, statistically significant weight loss at 6 months over standard of care in wait-listed controls (ADA 2018). Here we report effects of the intervention on glycemia and risk of diabetes as assessed by A1c, a prespecified secondary endpoint. The app downloads daily weights from smartscales and physical activity from 3-axis accelerometers. The technology allows peer social networking and remote coaching. Subjects chose diets from a selection of low glycemic index, low fat, low carb or Mediterranean. We performed comparisons using the t test. Intervention group (I) N=13, no dropouts, 84.62% F, age 40.2 ± 3.73 y (means ± SE), initial weight 94.2 ± 3.41 kg, BMI 34.5 ± 1.25 kg/m2. Wait-listed Control group (C) n=15, 86.67% F, age 45.9 ± 3.29 y, initial weight 92.3 ± 4.37 kg, BMI 34.4 ± 1.48 kg/m2. N=14 began the study and received in-person weight management visits at 0, 3, and 6 months. N=10 completed the 6-12 month phase during which they received the app-based lifestyle intervention. The intervention significantly improved A1c at 6 months -0.251 ± 0.0894 (95% CI -0.4419 to -0.0609) p=0.013 (I over C, per protocol analysis). At 6 months (I) change in A1c (n=9) -0.189 ± 0.0389 (95% CI -0.2786 to -0.0992) p= 0.0013, (C) change in A1c (n=8) +0.0625 ± 0.0844 (95% CI -0.1370 to 0.2620) p=0.48. After receiving the intervention from 6-12 months (C) group (n=10) improved A1c by -0.26 ± 0.0718 (95% -0.4224 to -0.0976) p=0.0056. All (C) subjects with prediabetes (n=4 of 10) who received the intervention resolved prediabetes at 12 months. Thus, the intervention produced clinically and statistically significant improvements in A1c. Our smartphone app-based lifestyle intervention may be a useful tool to treat prediabetes and prevent diabetes.

Disclosure
C. Vaz: None. N. Carnes: None. H. Zhao: None. K. Williams: Advisory Panel; Self; Gemphire Therapeutics Inc. Stock/Shareholder; Self; Gemphire Therapeutics Inc., Hygieia.

Funding
Temple University; Obesity Treatment Foundation
90-OR: High-Fat Diet Acutely Decreases Adipose Immunosuppressive T Regulatory Cells Leading to Insulin Resistance
Authors: BRADLEY DAVID , BLASZCZAK ALECIA M. , JALILVAND ANAHITA D. , WRIGHT VALERIE P. , NORIA SABRENA , JOSEPH JOSHUA , LIU JOEY Z. , HSUEH WILLA 
Published: June 2019

Adipose resident T lymphocytes (ARTs) are known metabolic mediators in mice. In particular, immunosuppressive regulatory T cells (Tregs) protect against insulin resistance. However, little is known about ARTs in humans or the effect of human weight gain on the AT immunoenvironment. We obtained visceral AT (VAT) and subcutaneous AT (SAT) biopsies from obese (n=83, BMI 48.9±8.5 kg/m2) and lean (n=15, BMI 23.6±1.9 kg/m2) patients undergoing elective surgery. A separate group of lean metabolically healthy patients (n=15, BMI 22.4 ± 1.8 kg/m2) underwent baseline and repeat SAT biopsies and hyperinsulinemic clamps before and after 2 weeks of a high-fat diet (HFD) overfeeding protocol (additional 1,320 kcal/day:&gt;50% total fat:&gt;10% saturated fat). Adipocytes were isolated for gene expression and flow analysis. Tregs (CD4+CD25+FOXP3+) as percent (%) of CD4+ cells were substantially increased in lean compared to obese SAT (22.1±15.0% vs. 7.3±3.8%; p&lt;0.001) and VAT (18.9±16.8% vs. 3.9±2.7%; p&lt;0.001) and negatively correlated with BMI and insulin sensitivity. After HFD, there was a significant increase in BMI (p&lt;0.001) and fasting glucose (p&lt;0.001), but no change in fasting insulin or HOMA-IR. We noted a dramatic overall decline in SAT Tregs after HFD (7.5 ± 1.0% to 3.3 ± 0.5%, p&lt;0.001), with all participants experiencing a decrease. The post-surgical change in SAT %Tregs positively correlated with the change in insulin sensitivity (M value) by hyperinsulinemic-euglycemic clamp (p=0.003, r=+0.797), so that those subjects with the greatest decline in Tregs had the largest decline in insulin sensitivity. This relationship persisted despite adjusting for, age, gender, pre-intervention BMI, and the change in weight from pre to post intervention (p=0.012). Our data thus demonstrates that Tregs decline in response to acute overfeeding, potentially contributing to development of insulin resistance. These results highlight a role for adipose tissue Tregs in human metabolism.

Disclosure
D. Bradley: None. A.M. Blaszczak: None. A.D. Jalilvand: None. V.P. Wright: None. S. Noria: None. J. Joseph: None. J.Z. Liu: None. W. Hsueh: None.

Funding
American Diabetes Association (1-16-ICTS-049 to W.H.); National Institutes of Health (KL2TR001068, HL135622)
901-P: Effects of Dapagliflozin, Metformin, or Exercise on Glycaemic Variability and Mean Glucose Levels in Prediabetes: The PRE-D Trial
Authors: FÆRCH KRISTINE , VISTISEN DORTE , BLOND MARTIN B. , NIELSEN LEA BRUHN , AMADID HANAN , DEJGAARD THOMAS F. , RIED-LARSEN MATHIAS , KARSTOFT KRISTIAN , PERSSON FREDERIK , JØRGENSEN MARIT E. 
Published: June 2019

Introduction: We assessed the efficacy of three glucose-lowering interventions in persons with HbA1c-defined prediabetes.
Methods: 120 participants were randomised 1:1:1:1 to 13 weeks of 1) dapagliflozin (DAP, 10 m/day); 2) metformin (MET, 1700 mg/day); 3) exercise (EXE, 5 x 30 min/week); or 4) control (CON, no treatment). Continuous glucose monitor (CGM) was used for 6 days before, during (6 weeks) and after (13 weeks) the intervention. Treatments were stopped the day before the last visit (two days before in EXE). Primary outcome was 13-week change in mean amplitude of glycaemic excursions (MAGE). Intention-to-treat analysis was conducted.
Results: At baseline, median (Q1;Q3) HbA1c was 5.9 (5.7;6.1)%; BMI 30.8 (28.6;34.3) kg/m2; age 62 (54;68) years; 44% were men. No within- or between-group changes were observed for MAGE. Mean CGM glucose (MG) was slightly reduced in MET and DAP at 6 weeks (Table 1). The 6-week change in MG in DAP was different from that in CON (mean diff. (95% CI): -0.3 mM (-0.5;0.0), P=0.031). At 13 weeks, MG had increased in MET and CON, and the change in MET was different from those in EXE (0.2 mM (0.0;0.5), P=0.041) and DAP (0.2 mM (0.0;0.5), P=0.039).
Conclusion: 13 weeks of treatment with MET, DAP or EXE did not change MAGE. Treatment with DAP or MET for 6 weeks slightly reduced MG; these improvements disappeared immediately after treatments were stopped at 13 weeks.

Disclosure
K. Færch: Research Support; Self; Ascensia Diabetes Care, AstraZeneca, Unilever. Stock/Shareholder; Self; Novo Nordisk A/S. D. Vistisen: Stock/Shareholder; Self; Novo Nordisk A/S. M.B. Blond: None. L.B. Nielsen: None. H. Amadid: None. T.F. Dejgaard: Consultant; Self; Novo Nordisk A/S. Research Support; Self; AstraZeneca, Novo Nordisk A/S. Speaker's Bureau; Self; Boehringer Ingelheim International GmbH. 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
909-P: Real-World Assessment of Connected Remote Continuous Glucose Monitoring Combined with Tele-consultations in a Pediatric Type 1 Diabetes Population
Authors: GIES INGE , VERMEULEN BRECHT 
Published: June 2019

Objectives: To study effectiveness and predictors of tele-monitoring on metabolic outcome of T1DM CGM treated children in real world.
Methods: CGM data of 47 T1DM patients (3-18 years) were studied during two years (October 2016 - September 2018): 6 months without bi-weekly tele-consultations (T0), 6 months with connected CGM and tele-consultations (T1-2), 6 months washout period and 6 months without tele-consultations (T3). HbA1C, time-in-hypo, and days-in-hospital were measured. Relationship between metabolic outcome and age, gender, baseline HbA1C, insulin regimen (pen vs. pump), puberty and compliance towards the tele-consultations, was studied.
Results: 2.836.322 CGM values (16.479 total days) were analysed. Baseline HbA1C (±SD) for the total group was 7.7±1% and did not change significantly; time-in-hypo decreased from 8±5% (T0) to 5±3% (T2) (p=0.002) and increased to 6±4% (T3) (p=0.143). HbA1C of patients with HbA1C &gt; 7.5% at T0 decreased significantly from 8.3±0.6% to 8±0.7% at T1 (p=0.024), to 8.1±1% at T2 (p=0.176) and stabilized at 8.1±1 at T3 (p=0.742). During 6 months of tele-monitoring, 352 therapy adjustments were proposed during 585 tele-consultations. In compliant patients (n=8) with baseline HbA1C &gt;7.5%, HbA1C changed from 8.1±0.5% (T0) to 7.6±0.4% (T1) (p=0.029), to 7.3±0.3% (T2) (p=0.001), and to 7.9±0.9% at T3 (p=0.035) while time in hypo was on average 6% and 7% before and after the tele-consultations and 4% during tele-consultations. Time-in-range with this group improved by 6% during 6 months of tele-consultations, and number of serious hypos decreased from 9 (T0) to 1 (T2) and 1 (T3); days-in-hospital from 7 (T0) to 0 (T2). No effect of age, gender, insulin regimen or puberty was found on HbA1C or time-in-hypo.
Conclusions: A benefit of tele-consultations in pediatric CGM patients was seen only in compliant patients with HbA1C &gt; 7.5%. Targeted use of tele-consultations can increase CGM benefits.

Disclosure
I. Gies: None. B. Vermeulen: None.

Funding
Belgian National Institute for Health and Disability Insurance
914-P: Connected Glucose Meter plus CDE Coaching Improves Diabetes Patient Empowerment and Distress in Real-World Outcomes Setting
Authors: BOLLYKY JENNIFER , LU WEI , PAINTER STEFANIE L. , POON JIAT LING , PEREZ-NIEVES MAGALY 
Published: June 2019

Background: Diabetes-related distress contributes to poor self-management and glycemic control over time. Empowering diabetes patients with health literacy and self-management skills improves self-management behaviors. The Livongo Diabetes Program offers a cellular-enabled, two-way messaging device that measures blood glucose, free unlimited blood glucose test strips; and access to CDE for real-time support and goal setting. We investigated the impact of the Livongo program on diabetes distress and empowerment over 12 months and characterized members with improved responses.
Methods: The Diabetes Distress Survey (DDS2) and Diabetes Empowerment Survey (DES-SF) were administered to 957 Livongo members via email at baseline and month 12. Demographic, clinical and medical spending characteristics of Responders (with improved DDS2 and DES-SF scores or high levels of empowerment and low levels of distress), were compared to Non-responders using student t-tests and Chi-square. Patient characteristics predicting Responder status were determined using logistic regression.
Results: Mean DES-SF improved from 3.9 (pre) to 4.3 (post) (p&lt;0.001). Mean DDS2 improved from 2.4 to 2.2 (p&lt;0.001). Sixty-one percent of members had an improvement in both DDS2 and DES-SF and 94% had improved scores in at least one. A greater proportion of Responders used oral medications only (64% vs. 55%, p=0.01) and had increased number of days with program activities (54% vs. 50%, p=0.02), while a smaller proportion had BG&gt;180 mg/dL (66% vs. 87%, p=0.04). Responders also had lower mean BG (139 vs. 147 mg/dL, p&lt;0.001). Upon multivariable adjustment, Responders were less likely to be Asian, more likely to be younger, have a lower BMI and diabetes duration of 5-10 years. Medical spending was not significantly different between the groups.
Conclusions: Significant improvements in both diabetes distress and empowerment were experienced by members of the Livongo program over 12 months.

Disclosure
J. Bollyky: Employee; Self; Livongo Health. Stock/Shareholder; Self; Livongo Health. W. Lu: None. S.L. Painter: Employee; Self; Livongo Health. J. Poon: Employee; Self; Eli Lilly and Company. M. Perez-Nieves: Employee; Self; Eli Lilly and Company. Stock/Shareholder; Self; Eli Lilly and Company.
92-LB: Real-World, Chart Review Study to Determine the Effectiveness of FreeStyle Libre Flash Glucose Monitoring System, in Adults with Type 2 Diabetes in France
Authors: HANAIRE HELENE , BENHAMOU PIERRE Y. , BURES CLEMENCE , FAVRE SANDRINE , FENDRI SALHA , JOUBERT MICHAEL 
Published: June 2019

This retrospective, real-world, chart review study determined the effectiveness of the FreeStyle Libre Flash Glucose Monitoring SystemTM on HbA1c when used by adults with type 2 diabetes (T2DM) as their standard of care in a real-world setting for between 3 months to 6 months. The study population included adults on a basal-bolus insulin regimen for at least 1 year, with HbA1c between 8.0 and 12.0% (64 to 108 mmol/mol), who had been prescribed and using FreeStyle Libre regularly for at least 3 months. Pregnant patients were excluded, as were patients on dialysis. A total of 88 records from insulin using patients with T2DM from 6 hospital sites in France were included in this chart review. On average, HbA1c was 9.0±0.9% (74.7±9.7 mmol/mol), prior to FreeStyle Libre use, age was 64.4±10.6 years, BMI was 32.9±5.5 kg/m2 and average duration of insulin use 9.9±6.4 years (mean±SD), 24.1% were CSII users, 58.0% of patients were on oral antidiabetic medications (metformin, SU or DPP-4) in addition to basal-bolus and 56.8% were male. CVD, renal and retinopathy complications were reported by 40.9%, 37.5% and 37.5% of patients, respectively. HbA1c results were recorded between 91 to 183 days from the start of use of FreeStyle Libre, between May 2017 and July 2018. To minimise selection bias records were selected on a systematic basis. After at least 3 months of using FreeStyle Libre, HbA1c (primary outcome) was significantly reduced by 0.8±1.1% (mean±SD); p&lt;0.0001. Sub-group analysis by insulin administration method showed HbA1c significantly reduced for both people using multiple daily injections and CSII; with reductions of 0.7±1.1%, p&lt;0.0001 and 1.0±1.0% (mean±SD), p=0.0001, respectively. This real-world, chart review study concluded that people with T2DM on insulin therapy, using FreeStyle Libre for between 3 to 6 months significantly reduced HbA1c.

Disclosure
H. Hanaire: Research Support; Self; Abbott, Eli Lilly and Company, LifeScan, Inc., Novo Nordisk A/S. Other Relationship; Self; Eli Lilly and Company, Novo Nordisk A/S. P.Y. Benhamou: Board Member; Self; Eli Lilly and Company, Novo Nordisk Inc., Sanofi. Consultant; Self; Abbott. C. Bures: Employee; Self; Abbott Laboratories. Employee; Spouse/Partner; Alere Inc. S. Favre: None. S. Fendri: None. M. Joubert: Board Member; Self; Abbott, Air Liquide, AstraZeneca, Lilly Diabetes, Medtronic, Novo Nordisk A/S. Consultant; Self; Voluntis France. Research Support; Self; Boehringer Ingelheim International GmbH. Speaker’s Bureau; Self; Amgen Inc., LifeScan, Inc., Merck Sharp & Dohme Corp., Sanofi.
942-P: Caregivers of Children with Type 1 Diabetes Value Real-Time Functions of Continuous Glucose Monitoring
Authors: WONG JENISE C. , ABDULHUSSEIN FATEMA , YEUNG BRITTANY J. , VELAZQUEZ EDGAR J. 
Published: June 2019

Continuous glucose monitoring (CGM) improves glycemic outcomes in children with type 1 diabetes (T1D) and is recommended for regular use. However, it is unclear how families use CGM and if they are using it to its greatest potential. In this study, 193 caregivers of children with T1D using CGM (mean age 9.3±2.8 years, 44% female, 10% ethnic minority, 92% using insulin pump) were recruited throughout the United States by social media to complete a cross-sectional survey about their real-time CGM use. Many children (70%) wore the sensor “all of the time,” with 77% using CGM ≥22 of the last 30 days. Most caregivers (93%) had a CGM feature to see their child’s data remotely in real time; 87% of those who used this feature viewed their child’s data at least once a day when their child was not with them. Though nearly all knew about CGM alert functions, only 73% set alerts for hyperglycemia and 80% for hypoglycemia “all the time.” Frequent retrospective review of CGM data was less common, with only 64% uploading and reviewing data at least monthly. Since starting CGM, most caregivers reported a decrease in their child’s glycated hemoglobin (A1c) (64%) and reduced frequency and severity of hypoglycemia (78%) and hyperglycemia (72%). In regression analysis (adjusted for age, duration of T1D, gender, minority status, caregiver education, geographic region, and pump use), younger age was associated with decrease in A1c (OR 0.78, 95% CI 0.67, 0.92) and decrease in hyperglycemia (OR 0.70, 95% CI 0.58, 0.84). Longer duration of CGM use was associated with decrease in hypoglycemia (OR 2.0, 95% CI 1.0, 4.1). Seventy-two percent reported CGM is “essential,” and 53% felt the greatest benefit is seeing data in real time.
In summary, caregivers utilize real-time CGM functions (remote monitoring, alerts) more frequently than they retrospectively review data. Future studies should focus on how caregivers use real-time and retrospective CGM data to make T1D management decisions in order to optimize use of the technology.

Disclosure
J.C. Wong: Advisory Panel; Self; Tidepool Project. Research Support; Self; Dexcom, Inc. F. Abdulhussein: None. B.J. Yeung: None. E.J. Velazquez: None.

Funding
Dexcom, Inc.
945-P: The Characteristics of Patients with Intermittent Large Positive Spikes in the Morning Fasting Glucose (FG), “Hyper-Spikers”
Authors: KING ALLEN B. 
Published: June 2019

Basal insulin is titrated upward whenever the average of several days’ FG exceeds a goal. It is assumed that averaging better reflects the ‘true’ FG (Central Limit Theorem) but this is true only if they are normatively distributed. There are a large subgroup of patients with diabetes in which their day-to-day FG variation is not normative but characterized by intermittent large positive spikes, the “Hyper-Spikers,” and large coefficient of variability (CV). We report their prevalence and characteristics in a large clinical practice. From 2000+ clinic charts, the data from 200 charts were consecutively selected if the patients had T2DM and were on basal insulin ± non-insulin but no bolus insulin. Only those with ≥ 3 consecutive daily FG readings were selected. CV = (SD/mean)*100. Hyper-Spikers were arbitrarily defined as a day to day FG CV ≥ 20%. CV distribution of the FG sets for all patients was not normative distributed but positive skewed with a mean CV of 17.8% and median, 15.9%. CV sets were divided into those ≤ 10% (LoVar) vs. those, ≥20% (Hyper-Spikers), 29 and 32% of patients, respectively. Age, gender, DM duration and weight were not different between groups (p &gt; 0.20). The mean basal doses were 23.1 vs. 30.0 U/d (p=0.0157) and 0.247 vs. 0.327 U/kg (p=0.00153) yet the A1c was higher, 8.06 vs. 8.47% (p = 0.0951) in Hyper-Spikers. The correlation coefficient of all individual’s CV at baseline vs. a mean follow-up of 4.1 m was 0.197 (p = 0.0166). From these observations, the Hyper-Spikers are not significantly different in age, gender, diabetes duration and weight from LoVar. The Hyper-Spikers were treated to a significantly higher basal insulin dose yet had a more elevated A1c. We conclude that the traditional method of averaging FGs to determine dosage increase is misleading in a significant (1/3) portion of patients and may lead to excessive basal insulin. We recommend that Hyper-Spikers be identified and the cause of the spikes determined before the dosage is increased.

Disclosure
A.B. King: None.
95-LB: Utility of Continuous Glucose Monitoring in Pediatric Diabetic Ketoacidosis
Authors: POTT THOMAS R. , JIMENEZ VEGA JOSE M. , PARKER JESSICA L. , FITZGERALD ROBERT 
Published: June 2019

Continuous glucose monitoring (CGM) commonly used in the outpatient setting is yet to be implemented in the pediatric intensive care unit (PICU) setting. The purpose of this study was to evaluate the feasibility, reliability and accuracy of the system in pediatric patients with DKA.
Objective: Determine the accuracy of CGM Dexcom G6™ in the setting of pediatric DKA compared to point of care capillary (POC) and serum glucose testing. Secondly, determine if the degree of acidosis impacts CGM when compared to POC and serum glucose testing.
Methods: Single institution IRB approved prospective trial. PICU patients that met inclusion criteria receiving standard DKA therapy were enrolled. CGM Dexcom G6™ sensors was applied to the patient’s abdomen on admission. Hourly POC and every 6 hour serum basic metabolic panels were obtained. CGM data was obtained every 5 minutes and matched to the nearest POC capillary and serum glucose levels ± 3 minutes. Reliability and feasibility analysis included frequency of data display, data gaps and any reasons for sensor removal.
Results: 35 pediatric patients, 11.9 ± 4.1 years old were enrolled. 51.4% were known diabetics and were older compared to the new onset diabetics, mean age 13.9 vs. 9.7 years respectively (p= 0.001). Clark Error grid of serum glucose versus CGM reveals 95.6% of readings within zones A and B, the Clark Error grid for POC versus CGM reveals 95.4% of readings within A and B zones. There was a negative correlation (-0.27) between the serum glucose and CGM delta when compared to serum bicarbonate level (p=0.007), while a positive correlation (0.24) between the POC and CGM delta when compared to serum bicarbonate level (p = 0.056). There were no sensors removed or adverse events that occurred during the study.
Conclusion: CGM use in patients with DKA seems both feasible and accurate. Serum bicarbonate level does not appear to impact the accuracy of CGM in the setting of DKA. Further studies examining the use and cost effectiveness of CGM in treatment decisions in DKA are warranted.

Disclosure
T.R. Pott: None. J.M. Jimenez Vega: Consultant; Self; Dexcom, Inc. J.L. Parker: None. R. Fitzgerald: None.