bluuebunny/crossref_metadata_2025_split huggingface dataset:
135-LB: The Forgotten Populations: Real-World Patients with T2DM Not Meeting Eligibility Criteria of the Glargine 300 U/mL EDITION and BRIGHT RCTs
Authors: MAURICIO DIDAC , WESTERBACKA JUKKA , NICHOLLS CHARLIE , WU JASMANDA , GUPTA RISHAB , MENON ARJUN A. , ELIASSON BJORN 
Published: June 2019

RCTs are the gold standard for comparing therapies’ efficacy and safety but can have strict eligibility criteria and may not reflect real-life clinical practice. Electronic medical records such as those from the Predictive Health Intelligence Environment (PHIE) database may be used to assess clinical effectiveness in real-world populations missed by clinical trials. We describe here the proportion and characteristics of patients with T2DM who would have been excluded from RCTs using eligibility criteria adapted from the EDITION 1-3 and BRIGHT trials.
Records from people with T2DM, with a basal insulin prescription on the index date (1 March 2015) and ≥1 HbA1c value in the previous 12 months, were evaluated. Exclusion criteria included HbA1c &lt;7.0 %/&gt;10.0 %, systolic blood pressure &gt;180 mmHg and/or diastolic blood pressure &gt;95 mmHg, or key comorbidities (e.g., heart failure or stroke) in the previous 12 months.
Of 191,218 evaluated records, 157,873 (83%) met ≥1 exclusion criterion; only 33,345 (17%) could have been included in RCTs (Table). Excluded patients were older, with more previous hypoglycemia vs. included patients and were less likely to have HbA1c between 7 and 9 %.
This divergence in clinical characteristics and patient numbers highlights the need for real-world studies assessing clinical effectiveness in populations of interest typically excluded from RCTs.

Disclosure
D. Mauricio: Advisory Panel; Self; Merck Sharp & Dohme Corp., Sanofi. Speaker’s Bureau; Self; Almirall, S.A., Boehringer Ingelheim International GmbH, Lilly Diabetes, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Sanofi, Urgo Medical. J. Westerbacka: Employee; Self; Sanofi. Stock/Shareholder; Self; Sanofi. C. Nicholls: Employee; Self; Sanofi. J. Wu: Employee; Self; Sanofi US. R. Gupta: None. A.A. Menon: None. B. Eliasson: Advisory Panel; Self; Amgen Inc., AstraZeneca, Merck Sharp & Dohme Corp. Speaker’s Bureau; Self; Boehringer Ingelheim International GmbH. Other Relationship; Self; Eli Lilly and Company, Novo Nordisk A/S, Sanofi.

Funding
Sanofi
1355-P: HbA1c Trajectories from Time of Diagnosis in Youth with T1D
Authors: SHERR JENNIFER , FOSTER NICOLE C. , BETHIN KATHLEEN , FOX LARRY A. , MASTRANDREA LUCY D. , NATHAN BRANDON M. , REDONDO MARIA JOSE , SILVERSTEIN JANET , SIMMONS JILL , CLEMENTS MARK A. , TAMBORLANE WILLIAM V. , THRAILKILL KATHRYN M. , WONG JENISE C. , WOOD JAMIE 
Published: June 2019

Most individuals with type 1 diabetes (T1D) do not achieve glycemic targets, particularly in youth. This analysis examined HbA1c trajectories of youth newly diagnosed with T1D. T1D Exchange registry participants &lt;18 years with at least one HbA1c during the year of diagnosis and ≥3 duration-year aggregated HbA1c values over 10 years of follow-up were included. At diagnosis, the 4183 participants were 48% female, 81% Caucasian, age 6±4 years, and 77% privately insured. Suboptimal control was defined as HbA1c ≥9%. Group-based trajectory modelling was used to identify unique HbA1c trajectories over aggregated duration years. Five trajectories emerged (Figure). The majority of youth had stable trajectories within three distinct categories: those at (1) or above (3) glycemic target and those with suboptimal control (4). Two groups showed deterioration over time, one with suboptimal control from diagnosis (5) while the other had above target glycemia that worsened with time (2). Minority status was higher in groups with upward trend in HbA1c trajectory and suboptimal but stable control. Similar trends were seen for non-private insurance. Several distinct patterns of HbA1c progression exist in youth with T1D, partly dependent on HbA1c at diagnosis. Identifying characteristics of those with progressive deterioration in glycemic control and designing appropriate interventions for these groups is warranted.

Disclosure
J. Sherr: Advisory Panel; Self; Bigfoot Biomedical, Eli Lilly and Company, Insulet Corporation. Consultant; Self; Lexicon Pharmaceuticals, Inc., Medtronic, Sanofi. Research Support; Self; Dexcom, Inc., Insulet Corporation. N.C. Foster: None. K. Bethin: Research Support; Self; Novo Nordisk Inc., Xeris Pharmaceuticals, Inc. L.A. Fox: None. L.D. Mastrandrea: Advisory Panel; Self; Pediatric Diabetes Consortium. Research Support; Self; AstraZeneca, JDRF, Novo Nordisk Inc., Sanofi-Aventis, T1D Exchange. Other Relationship; Self; Novo Nordisk Inc. B.M. Nathan: None. M.J. Redondo: None. J. Silverstein: None. J. Simmons: None. M.A. Clements: Advisory Panel; Self; Glooko, Inc. Consultant; Self; Eli Lilly and Company. Speaker's Bureau; Self; Medtronic. W.V. Tamborlane: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Medtronic MiniMed, Inc., Novo Nordisk Inc., Sanofi, Takeda Pharmaceutical Company Limited. K.M. Thrailkill: None. J.C. Wong: Advisory Panel; Self; Tidepool Project. Research Support; Self; Dexcom, Inc. J. Wood: Research Support; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Novo Nordisk Inc.
1357-P: Real-World Glycemic Profiles and Insulin Use Patterns of 9,914 Pediatric and Adolescent Patients with Type 1 Diabetes Using the Omnipod® Insulin Management System with Cloud-Based Data Management
Authors: LAYNE JENNIFER E. , ZHENG YIBIN , HE JIALUN , JANTZ JAY , BENJAMIN ERIC , LY TRANG T. 
Published: June 2019

This observational study characterized glycemic profiles and treatment patterns of a large cohort of pediatric and adolescent patients with T1D using the Omnipod® Insulin Management System (Insulet Corp., Acton, MA) with integrated BG meter (Abbott Diabetes Care Inc., Alameda, CA) and data management system (Glooko, Mountain View, CA). From January 2015 through September 2018, usage data from the pump system were uploaded to the data management system and matched via device serial number to a second database of self-reported demographic data and de-identified. BG and insulin data from ≥3 months of system use per patient were analyzed. Demographics, glycemic profiles and insulin use of pediatric and adolescent patients with T1D (n=9,914) stratified by age group &lt;6 y (n=499), 6 to &lt;12 y (n=3,560) and 12 to &lt;18 y (n=5,855) are reported in the Table. Mean glucose was 192±32, 190±31 and 201±39 mg/dL and bolus frequency per day was 7.5±2.8, 6.4±2.2 and 5.3±2.1 in the &lt;6 y, 6 to &lt;12 y and 12 to &lt;18 y groups, respectively. These real-world data from a large cohort of youth with T1D demonstrate that use of a tubeless insulin pump was associated with BG levels that compare favorably to large registries including the T1D Exchange. These data also highlight important management patterns including frequent bolusing with Omnipod® System use.

Disclosure
J.E. Layne: Employee; Self; Insulet Corporation. Y. Zheng: Employee; Self; Insulet Corporation. Stock/Shareholder; Self; Insulet Corporation. J. He: Employee; Self; Insulet Corporation. J. Jantz: Employee; Self; Insulet Corporation. Employee; Spouse/Partner; Insulet Corporation. E. Benjamin: Employee; Self; Insulet Corporation. T.T. Ly: Employee; Self; Insulet Corporation.

Funding
Insulet Corporation
1365-P: Metabolic Control Three Years after Diagnosis in Children with T1D: Is DKA at Onset or HbA1c at Onset Closer Associated with Third Year HbA1c? Data from the International Pediatric Diabetes Registry SWEET
Authors: PICCINI BARBARA , SCHWANDT ANKE , ARSLANOGLU ILKNUR , CARDONA-HERNANDEZ ROQUE , COUTANT REGIS , JEFFERIES CRAIG A. , KIM JAE HYUN , KORDONOURI OLGA , LIMBERT CATARINA , PREIKSA ROMUALDAS TOMAS , LYCKÅ AUSTE PUNDZIUTE , RAMI-MERHAR BIRGIT , RICHMOND ERICK , SAVOVA RADKA , TODOROVIC SLADJANA , VEEZE HENDRIK J. , TONI SONIA ,   FOR THE SWEET REGISTRY
Published: June 2019

Objective: To establish if DKA at onset or HbA1c at onset is closer associated with metabolic control three years after diagnosis in a large, heterogeneous, international T1D cohort.
Methods: Data were collected from the international diabetes registry SWEET. 1420 T1D children (54% boys; 994 from Northern Europe, 341 from Southern Europe, 85 from America/Canada), diagnosed before 18 years, with documented clinical presentation and HbA1c at onset and follow-up data available were included. Patients were grouped according to presentation at onset: DKA with coma, DKA without coma and no DKA; and HbA1c at onset: low (HbA1c &lt;10%), medium (10-&lt;12%) and high (≥12%). To adjust for age at onset, gender and region, linear regression models were applied (adjusted means with 95% CI). Vuong test was employed to compare the association between third year HbA1c and both HbA1c at onset and presentation at onset.
Results: Median age at T1D onset was 9.1 [Q1; Q3: 5.8; 12.2] years. DKA with coma was present in 6% of children, DKA without coma in 37% and no DKA in 57%. No significant differences were found in third year HbA1c between DKA with coma 7.7 (7.4;8.0)%, DKA without coma 7.5 (7.4;7.6)% and no DKA group 7.6 (7.5;7.7)% [adjusted means (95% CI)]. Third year HbA1c was lower (7.4 (7.3;7.5)%) in low HbA1c compared to high HbA1c at onset group (7.7 (7.6;7.8)%, p&lt;0.01). In the medium HbA1c group, third year HbA1c was 7.5 (7.4;7.6)% (no differences). Comparing the model with HbA1c at onset groups vs. the model with presentation at onset groups, the model with HbA1c at onset was closer associated with the third year HbA1c (p=0.02).
Conclusions The high percentage of DKA at T1D onset is still a concern worldwide. The level of HbA1c at onset was more closely associated with long term T1D control than the DKA at onset. Early T1D diagnosis, preventing high HbA1c at onset as well as DKA at onset, is important for long term metabolic control.

Disclosure
B. Piccini: None. A. Schwandt: None. I. Arslanoglu: None. R. Cardona-Hernandez: None. R. Coutant: None. C.A. Jefferies: None. J. Kim: None. O. Kordonouri: None. C. Limbert: None. R. Preiksa: None. A. Pundziute Lyckå: None. B. Rami-Merhar: Speaker's Bureau; Self; Eli Lilly and Company, Medtronic, Menarini Group, Roche Diabetes Care. E. Richmond: None. R. Savova: None. S. Todorovic: None. H.J. Veeze: Consultant; Self; Medtronic MiniMed, Inc. S. Toni: None.
1366-P: Effect of Substance Use on Type 1 Diabetes (T1D) Pancreas Histopathology
Authors: BRUGGEMAN BRITTANY S. , CAMPBELL-THOMPSON MARTHA , POSGAI AMANDA L. , ATKINSON MARK A. , SCHATZ DESMOND , JACOBSEN LAURA M. 
Published: June 2019

Recent efforts addressing the pathogenesis of T1D have benefited greatly from access to transplant-quality human pancreas samples obtained from organ donors. While alcohol use is linked to pancreatitis clinically, the effect of alcohol and other illicit substances on pancreatic histopathology in T1D is not known. Hence, we determined the influence of alcohol, marijuana, tobacco, cocaine, and other controlled substances in T1D pancreata. In total, 140 T1D organ donor pancreata [median age at T1D onset=11 (range 0-36) years, duration=12 (0-84) years, 47% female] were recovered through the Network for Pancreatic Organ donors with Diabetes (nPOD) program. Paraffin sections were stained and reviewed for insulin positivity, insulitis (≥6 CD3+ cells adjacent/within the islet in ≥3 islets/section), amyloid staining, acute (acinar cell loss, mononuclear cell infiltrate, fat necrosis, and hemorrhage) and chronic pancreatitis (acinar cell loss, mononuclear cell infiltrate, and fibrosis) as well as chronic exocrine changes (acinar atrophy, fibrosis, fatty infiltration, or periductal fibrosis). Terminal hospital records were reviewed for a history of alcohol, tobacco, marijuana, and any illicit substance use. Of 140 T1D donors, 51% had a history of alcohol use, 40% tobacco use, 29% marijuana, and 20% other illicit substances. Urine drug screening on admission was available for 74 donors with 36 positive (49%). Alcohol use was associated with histopathological features of acute pancreatitis (p&lt;0.05) and islet amyloid deposition (p&lt;0.05). History of cocaine use (p&lt;0.05) as well as a positive urine drug screen (p&lt;0.05) were associated with chronic exocrine changes. To conclude, in T1D donor pancreata, alcohol use was associated with acute pancreatitis and islet amyloid deposition while a history of cocaine use and a positive urine drug screen were associated with chronic exocrine changes. These findings should be given consideration in studies aimed at interpreting histopathologic changes in T1D pancreata.

Disclosure
B.S. Bruggeman: None. M. Campbell-Thompson: None. A.L. Posgai: None. M.A. Atkinson: None. D. Schatz: None. L.M. Jacobsen: None.

Funding
JDRF
1372-P: Impact of Distance to Pediatric Diabetes Center on Outcomes in Youth with Type 1 Diabetes
Authors: WATSON SARA , JAWAD KAHIR S. , RODRIGUEZ LUNA MANUEL A. , WINTERGERST KUPPER A. 
Published: June 2019

Background: The burden of T1D includes multiple visits to an endocrinologist each year, often requiring significant travel. Youth with T1D are especially impacted as pediatric endocrinologists are primarily concentrated at academic centers in urban areas.
Objectives: To assess the impact of distance to the diabetes treatment center on diabetes outcome measures. And to determine if the prevalence of technology use for the management of diabetes differs among youth with T1D living in urban versus rural communities.
Methods: Retrospective data was collected for youth ≤ 18 years of age, with a diagnosis of T1D for ≥ 6 months, seen at the Wendy Novak Diabetes Care Center. GIS mapping was used to analyze outcome measures by distance to the treatment center. Rural-Urban Commuting Area (RUCA) Codes were assigned to identify those living in metropolitan (RUCA 1-3), micropolitan (RUCA 4-6), and rural communities (RUCA 7-10).
Results: Inclusion criteria were met by 823 youth. Of these, 710 (86.3%) were white. Current CGM use was identified for 288 (35%), and pump use by 385 (46.8%). The mean distance traveled to the center was 18 miles (S.D. 8.8-52.2). Those traveling farther distances attended fewer clinic visits (p=0.0033). Those using a CGM or an insulin pump had more visits per year (p &lt; 0.0001 and p=0.01, respectively). Among white youth, those traveling &lt;20 miles used CGM 1.4 times more often than those traveling ≥20 miles (p=0.0196). Those living in metropolitan areas were more likely to use a CGM than those living in micropolitan or rural areas (p=0.0383).
Conclusions: Those with a greater burden of travel to receive specialty care attended fewer visits and were less likely to use CGM technology that has important benefits in improving blood glucose management and safety for those living with T1DM. This will be important to consider when developing strategies to improve access and support for this technology.

Disclosure
S. Watson: None. K.S. Jawad: None. M.A. Rodriguez Luna: None. K.A. Wintergerst: None.

Funding
Jaeb Center for Health Research
138-LB: Digital-Tool-Supported Basal Insulin (BI) Titration: Real-World Effectiveness of My Dose Coach in India
Authors: MODI K. D. , JHA SUJEET , PANDA MANJU , RASKAR VIVEK , MITTAL DIWAKAR , GHOSH ROMIK , GRIFFEN STEVE , ABUBUCKER SAHAR , SALEH MILENA 
Published: June 2019

Appropriate insulin titration is critical in helping people with T2DM meet glycemic targets, but rates of successful self-adjustment are low, highlighting a need for additional support. My Dose Coach (MDC) is an FDA-approved digital tool that combines a smartphone app for people with T2D and a web portal for healthcare professionals (HCPs). HCPs define an individualized long-acting BI dose plan, which MDC uses to give dose recommendations based on the user’s fasting blood glucose (FBG) readings and hypoglycemic event data. MDC was introduced in India in 2018.
We evaluated real-world outcomes from people with T2D in India who were registered for MDC between Sep 1 and Dec 31, 2018. FBG and BI dose were logged directly by users in the MDC app. Users who reached goal were defined as those who logged three consecutive FBG measurements within their prescribed target range during their care plan.
There were 337 people who were registered with MDC and had logged &gt;1 FBG reading; 113 (34%) reached their FBG goal, 27 (8%) were still titrating and 197 (58%) were no longer actively using MDC (discontinued without reaching goal). Mean (SD) time to FBG target in the ‘at goal’ cohort was 25 (26.9) days. In this cohort, mean (95% CI) FBG at baseline was 165.8 (156.4, 175.1) mg/dL, which decreased to 108.0 (106.7, 109.2) mg/dL at goal (p&lt;0.001). Mean (95% CI) BI dose increased from 16.2 (15.1, 17.4) units at baseline to 19.4 (17.6, 21.2) units at goal (p=0.012). Over the entire observation period, 35% of participants in the ‘at goal’ group experienced hypoglycemia (FBG &lt;70 mg/dL or below individual HCP-defined cut-off of at least 70 mg/dL); mean 0.62 events.
Most participants who continuously used MDC were able to successfully titrate BI and achieve target FBG. These data are very encouraging, showing the potential for simple digital titration tools, in appropriately selected people with T2D, to engage users in their own care, decrease the HCP burden and accelerate FBG target achievement in a resource-limited setting.

Disclosure
K.D. Modi: None. S. Jha: None. M. Panda: None. V. Raskar: Advisory Panel; Self; Sanofi. Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Novartis Pharmaceuticals Corporation, Novo Nordisk A/S, Sanofi. D. Mittal: None. R. Ghosh: Employee; Self; Sanofi. S. Griffen: Employee; Self; Sanofi. S. Abubucker: None. M. Saleh: Employee; Self; Sanofi-Aventis Deutschland GmbH.

Funding
Sanofi
1380-P: Multiplex Detection of T1D-Associated Autoantibodies by High-Quantum-Efficiency FRET
Authors: METZ ANGELINA A. , ARSHAM ANDREW M. , LASER DANIEL J. , DROITCOUR AMY D. 
Published: June 2019

We have developed a homogeneous time-resolved Förster Resonance Energy Transfer (TR-FRET) assay for rapid, no-wash multiplexed detection of T1D-associated autoantibodies from small volumes (5-10 μL) of patient plasma or serum. In our assay, separate pools of recombinant antigen are labelled with either a long-lived high-quantum-efficiency terbium cryptate FRET donor or a small-molecule flurophore FRET acceptor, generating potent FRET pairs. With the mean distance between the tips of the two epitope binding regions approximately 12-13 nm and the distance between the edges of each epitope binding arm on the order of 3.5 nm, the pairs are brought into signaling proximity when the twin binding arms of immunoglobulin bind a donor and an acceptor. We used terbium’s tightly banded multi-peak luminescence with large stokes shift and long millisecond-scale lifetime under 350 nm excitation to engineer the assay for detection of four T1D targets at clinically relevant concentrations—GAD 65, IA-2, ZnT8 and insulin—along with a fifth pair as an internal control. We report on the assay’s impressive performance with clinical samples, including the development and implementation of a high-performance crosstalk correction algorithm. The assay described here functions identically in both commercial plate readers and in point-of-care systems, a key feature for highly consistent test results.

Disclosure
A.A. Metz: Employee; Self; Wave 80 Biosciences, Inc. A.M. Arsham: Consultant; Self; Wave 80 Biosciences. D.J. Laser: Board Member; Self; Wave 80 Biosciences. A.D. Droitcour: Employee; Self; Wave 80 Biosciences.

Funding
Type 1 Diabetes Foundation
139-LB: Haptoglobin Phenotype and Levels in Type 2 Diabetes and Effects of Fenofibrate
Authors: JANUSZEWSKI ANDRZEJ S. , YOUNG HAYDEN K. , LI LIPING , OCONNELL RACHEL L. , LYONS TIMOTHY , KELLY CLARE B. , SULLIVAN DAVID , SCOTT RUSSELL , KEECH ANTHONY C. , JENKINS ALICIA 
Published: June 2019

Background: Haptoglobin (Hp) is a plasma protein with anti-oxidant, anti-inflammatory and pro-angiogenic properties. Based on the Hp gene alleles there are three Hp phenotypes (1-1, 2-1 and 2-2). In diabetes, Hp-2 is associated with substantially increased risk of cardiac and renal damage relative to Hp-1. AIMS: To evaluate 1) associations between Hp phenotype and levels; and 2) effects of fenofibrate vs. placebo on Hp levels.
Methods: A substudy of 180 adults with type 2 diabetes (T2D) (50% females) from the FIELD trial. Average age was 60±6 years, BMI 30.4±5.1 kg/m2 and HbA1c 6.8±1.3%. Plasma (citrate) samples were evaluated at baseline, after 6-weeks daily 200 mg co-micronised fenofibrate (end of active run-in) and 2-years after randomisation to fenofibrate or placebo.
Results: Hp phenotype 1-1 was detected in 19%, Hp 2-1 in 48% and Hp 2-2 in 33% subjects. Hp levels at baseline were 1.44±1.10, 1.31±0.49 and 0.99±0.46 mg/mL in type 1-1, 2-1 and 2-2 respectively (all p&lt;0.0001). In Hp type 2-2 baseline Hp levels correlated with HbA1c (r=0.35, p=0.005), BMI (r=0.30, p=0.02) and HDL-C (r=0.29, p=0.02). No such correlations were observed for Hp type 1-1 and 2-1. After 6-weeks fenofibrate Hp levels dropped by 22.3, 19.9 and 17.7% in type 1-1. 2-1 and 2-2 respectively (all p&lt;0.0001; difference between types p=ns.). After 2-years of fenofibrate vs. placebo Hp levels in the placebo group had increased back to baseline values whereas Hp levels in the fenofibrate group remained reduced similar to 6-weeks levels. In Hp 1-1 subjects Hp levels dropped after 6-weeks fenofibrate in 94% of subjects, in Hp 2-1 - in 92% and in Hp 2-2 only in 73% of subjects (difference between phenotypes: p=0.002).
Conclusions: Hp levels differ by Hp phenotype in T2D adults. Fenofibrate lowers Hp levels in all phenotypes, however the effect is significantly attenuated in Hp 2-2.

Disclosure
A.S. Januszewski: None. H.K. Young: Other Relationship; Self; Medtronic. L. Li: None. R.L. OConnell: None. T. Lyons: None. C.B. Kelly: None. D. Sullivan: None. R. Scott: None. A.C. Keech: None. A. 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.

Funding
Sydney Medical School Foundation; National Health and Medical Research Council of Australia