bluuebunny/crossref_metadata_2025_split huggingface dataset:
120-OR: Diabetes-Related Quality of Life Assessment in Children following Total Pancreatectomy with Islet Autotransplantation
Authors: REDEL JACOB M. , HORNUNG LINDSEY , ELDER DEBORAH A. , NATHAN JAIMIE D. , ABU-EL-HAIJA MAISAM 
Published: June 2020

Total pancreatectomy with islet autotransplantation (TPIAT) can effectively improve pain and functional impairment associated with chronic pancreatitis (CP) in children. However, children undergoing this procedure usually develop post-pancreatectomy diabetes and require chronic insulin therapy. It can be difficult for providers and patients to conceptualize trading the symptoms of CP for the burden of diabetes. Therefore, we sought to evaluate diabetes-related quality of life (QOL) over time in children who underwent TPIAT, and compare QOL scores post-TPIAT with children who have type 1 diabetes (T1D). The Pediatric Quality of Life Inventory (PedsQL) 3.2 Diabetes Module was used to assess diabetes-related QOL. PedsQL scores were evaluated in 46 children (&lt;20 years old) who underwent TPIAT and completed at least one survey. PedsQL data was collected at 3, 6, 9, 12, 18, and 24 months post-TPIAT. Total and Subscale scores were analyzed for change over time. The TPIAT cohort PedsQL scores at 24 months (n=16) were then compared to PedsQL scores from a historical cohort of demographically similar (age, race, sex) patients 24 months after new onset T1D (n=58). Mean age at TPIAT was 12.6 ± 4.7 years and 67% were female. Mean age at T1D diagnosis was 11.2 ± 3.2 years and 69% were female. The Diabetes Symptoms subscale (p=0.03) and the Total Score (p=0.049) decreased (worsened) over 24 months post-TPIAT (Diabetes subscale: median 68 to 56; Total Score: median 75 to 68). The other subscales did not significantly change over that time. At 24 months after diabetes onset, no PedsQL subscales were different between the TPIAT cohort and T1D cohort (all p&gt;0.2). The Total PedsQL score, mostly attributable to the Diabetes Symptoms subscale, decreased over time in patients who underwent TPIAT. Additionally, diabetes-related QOL at 24 months was not significantly different from children with T1D. This data may be used to help counsel families who are considering TPIAT for treatment of CP.

Disclosure
J.M. Redel: None. L. Hornung: None. D.A. Elder: None. J.D. Nathan: None. M. Abu-El-Haija: None.

Funding
Cincinnati Children’s Hospital
1204-P: Patients’ Interpretation of Ambulatory Glucose Profile (AGP), CGM, and Pump Reports
Authors: MULLEN DEBORAH M. , BERGENSTAL RICHARD M. , JOHNSON MARY L. 
Published: June 2020

Aim: Determine how patients review CGM and insulin pump data simultaneously to determine self-treatment adjustments.
Methods: Subjects (n=21) verbally reported their interpretation/thoughts while examining an AGP (CGM + Insulin Pump) Report in a cognitive interview. Interviews lasted 45-90 minutes.
Results: Subjects overwhelmingly prefer phone/watch interfaces; 75% do not have computers at home. Users report looking at their phones/CGM readings on average 16-60 times a day (1-4 times/hour); with several reporting high frequency of 15-45 times/hour. All subjects prefer colored graphs rather than numerical data on a single page report, with heavy preference to focus on CGM data with only occasional review of insulin pump data. Subjects felt the AGP CGM + Pump Report was “helpful” (86%), yet only 57% felt it was easy to understand due to the basal vs. bolus graphs. When asked to identify glucose data patterns: 95% noted trends, 67% noted hypoglycemia, 95% noted hyperglycemia, and 100% identified “missed” opportunities to treat high daily glucose levels. Bolus insulin graph responses included: bolus dose times of day helpful (100%), average meal bolus helpful (71%), and 73% understood the graph after an explanation, but only 38% could teach back offering specific advice. Subjects felt basal insulin graph made sense (90%). Subject confidence using AGP report data for self-care was high (95%) and would allow independent decision making about their DM care including identifying treatment next steps and determining how insulin dosing affects glucose trends. Seventy percent would feel confident making changes to their care by themselves using this report including adjustment of their pump settings, while 90% felt it would help with basal rate adjustments.
Conclusion: CGM metrics and pattern visualization have recently been standardized in an AGP CGM report. Our patient interview reinforces that the same efforts are needed worldwide to standardize CGM and insulin dose (pump and connected pen) reporting.

Disclosure
D.M. Mullen: Consultant; Self; International Diabetes Center DBA HealthPartners Institute. R.M. Bergenstal: Consultant; Self; Ascensia Diabetes Care, Johnson & Johnson. Other Relationship; Self; Abbott, Dexcom, Inc., Hygieia, Lilly Diabetes, Medtronic, Novo Nordisk A/S, Onduo, Roche Diabetes Care, Sanofi, UnitedHealth Group. M.L. Johnson: Consultant; Self; Jaeb Center for Health Research. Research Support; Self; Abbott, Dexcom, Inc., Insulet Corporation, JDRF, Lilly Diabetes, Medtronic, National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk Inc.

Funding
National Institute of Diabetes and Digestive and Kidney Diseases (3UC4DK10861101S1)
1212-P: Real-World Prescribing of GLP-1RA in a Safety Net Health System
Authors: MCNULTY JACQUELINE N. , GUNASEKARAN UMA , LINGVAY ILDIKO , MENEGHINI LUIGI 
Published: June 2020

There is considerable excitement regarding the benefits of using GLP-1RA in high risk populations (prior ASCVD), however translating evidence into practice is often delayed. We sought to assess within our safety net health system the use of GLP-1RA in type 2 diabetes in high-risk patients in order to inform future quality improvement (QI) initiatives. From Sep 2016 to Oct 2019, we identified a total of 4594 patients with diabetes and a diagnosis of ASCVD. Of these, a total of 101 patients (2%) were prescribed a GLP-1RA, while the majority (N=4493) were not. Patients prescribed a GLP-1RA were on average 60±9 years old, 44% were female, 40% Hispanic. Common co-morbidities and characteristics of patients with ASCVD who did, or did not, receive a GLP-1RA prescription are detailed in the Table. Most GLP-1RA prescriptions were generated by Primary Care (57%), Endocrinology (29%), and Cardiology (6%). The large majority of these patients (42%) received charity care from the health system. Patients receiving a GLP-1RA (compared to those that did not) were more often obese and with a diagnosis of nephropathy. Of note is that the ICD diagnoses identifying ASCVD in the medical records are substantially under-reported. Appropriate use of GLP-1RA in patients with documented ASCVD remains very low. This baseline data will guide our QI efforts and focus on implementing evidence-based use of GLP-1RA at the primary care level.

Disclosure
J.N. McNulty: None. U. Gunasekaran: None. I. Lingvay: Consultant; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Intarcia Therapeutics, Janssen Pharmaceuticals, Inc., MannKind Corporation, Novo Nordisk A/S, Sanofi, TARGET PharmaSolutions, Valeritas, Inc. Other Relationship; Self; Novo Nordisk A/S. L. Meneghini: Advisory Panel; Self; Novo Nordisk Inc., Sanofi US. Consultant; Self; Applied Therapeutics, Sanofi US.
1213-P: Utilizing Lean Six Sigma and Quality Improvement (QI) Tools to Improve Hemoglobin A1c Control in Persons with Diabetes
Authors: ALI SADIA , KOLLIPARA USHA 
Published: June 2020

Aim: Using lean six sigma QI tools, Define-Measure-Analyze-Improve-Control (DMAIC), design and implement best practices to reduce percentage of patients with hgbA1c &gt;9.0% from baseline of 26% in May 2018 to 21% by July 2019 in our endocrinology clinic.
Methods: We used institution’s diabetes registry to capture hgbA1c values and patient visits to endocrinology clinic. DMAIC data driven improvement cycle was used for identifying care gaps, problem solving and interventions to improve workflow processes. At the end of the DMAIC implementation, Plan-Do-Study-Act (PDSA) cycles were implemented for 6 months for control of the new processes. During Analyze phase, main care gaps identified were missing hgbA1c values, appointment cancellations and low participation in self-management diabetes education. We implemented pre visit planning, standardization of hgbA1c ordering process, standing medical orders for both hgbA1c testing and self-management diabetes education classes. DMAIC phases were completed over five months, and the process was monitored for next six months.
Results: 3016 persons were seen for diabetes management during the measurement period. Percent in poor control improved from 26% in May 2018 to 18% by July 2019.
Conclusion: Quality improvement tools can be successfully applied to improve and sustain clinical outcomes such as hgbA1c control in persons with diabetes.

Disclosure
S. Ali: None. U. Kollipara: None.
1217-P: Improvement of Metabolic Control in Type 1 Diabetes after Transition Is Independent from Referral Center and Insulin Regimen
Authors: PIERALICE SILVIA , MADDALONI ERNESTO , MORETTI CHIARA , MAURIZI ANNA RITA , MIGNOGNA CARMEN , DINATALE STEFANO , POZZILLI PAOLO , BUZZETTI RAFFAELLA 
Published: June 2020

Background and Aim: Our previous data showed that transition from pediatric to an adult care center (ACC) improves glycaemic control in youth with type 1 diabetes (T1D). However, factors that might impact the success of transition are still unclear. In this study we aimed to evaluated whether metabolic control after transition differs by different ACC, insulin regimens and age at transition.
Methods: In this retrospective observational study we evaluated data from 178 patients with T1D moving from two pediatric clinics to two different ACC in Rome. The transition process was performed according to the American Diabetes Association Standard of Care. A1c was reassessed three and six months after transition and compared to baseline values by within-subjects analysis of variance, fitting interaction terms with referral center, baseline insulin regimen (multiple daily insulin injection [MDI] and continuous subcutaneous insulin infusion [CSII]) and age.
Results: At baseline, mean ± SD age was 28.4 ± 6.7 years, disease duration was 18.6 ± 8 years and A1c was 7.9 % ± 1.3. Mean transition gap was 8.0 ± 6.2 months. A1c values significantly improved both three (ΔA1c: -0.2%, p &lt;0.001), and six months (ΔA1c: -0.4 %, p &lt;0.001) after transitioning. At 6 months, ΔA1c was similar in the two centers (-0.4±1.0% and -0.4±0.7, p-value for interaction: 0.58) and in subjects on MDI or CSII at baseline (-0.5±1.0% and -0.4±0.6%, p-value for interaction: 0.37). No interaction between age at baseline and time was found (p-value: 0.22) The number of subjects on CSII increased from 46 (26.9%) at baseline to 64 (37.4%) after 6 months. There was no difference in A1c improvement between subjects changing compared to those not changing insulin regimen (p-value: 0.71).
Conclusion: This study shows a rapid improvement of metabolic control in T1D after transition, regardless of referral center, insulin regimen and age at transition. Further analysis evaluating different educational programs are needed.

Disclosure
S. Pieralice: None. E. Maddaloni: Consultant; Self; Merck KGaA. Speaker’s Bureau; Self; Abbott, AstraZeneca, Pikdare. C. Moretti: None. A. Maurizi: Employee; Self; AstraZeneca. C. Mignogna: Research Support; Self; Eli Lilly and Company. Other Relationship; Self; AstraZeneca. S. Dinatale: None. P. Pozzilli: Advisory Panel; Self; Abbott, AstraZeneca, Eli Lilly and Company. Research Support; Self; Medtronic, Sanofi. R. Buzzetti: Advisory Panel; Self; Sanofi. Speaker’s Bureau; Self; AstraZeneca, Lilly Diabetes, Merck Sharp & Dohme Corp.
122-LB: The Simplici-T1 Trial: Glucokinase Activator TTP399 Improves Glycemic Control in Patients with Type 1 Diabetes
Authors: BUSE JOHN B. , KLEIN KLARA , FREEMAN JENNIFER L. , DUNN IMOGENE , VALCARCE CARMEN 
Published: June 2020

Identification of adjunctive, oral pharmacotherapies to treat type 1 diabetes (T1D) has been limited by hypoglycemia and ketoacidosis. TTP399 is a liver-selective oral glucokinase activator. In type 2 diabetes (n=190), TTP399 was shown to reduce A1C vs. placebo (PL) -0.9% (p&lt;0.01) without hypoglycemia or ketosis.
The Simplici-T1 trial (NCT03335371) is an adaptive three-part Phase 1b/2 Proof of Concept study of TTP399 as adjunctive therapy for T1D treatment. Safety, pharmacokinetics, and pharmacodynamics were established in a sentinel phase (n=5). In Part 1 (n=19), TTP399 reduced A1C (-0.7%, p=0.03), improved time in range 70-180 mg/dl (TIR; 12%, p=0.04), and reduced bolus insulin vs. PL in patients on insulin pump therapy and continuous glucose monitoring.
In Part 2 (n=85), these data were examined in a broader T1D population. Insulin dose was optimized prior to randomization and throughout the 12 wk double-blind treatment period with specified pre- and post-meal targets. Participants received TTP399 800 mg or matched PL. A1C at randomization was 7.6% (SD 0.6). TTP399 significantly reduced A1C (trial product estimand: -0.32%, 95%CI -0.50, -0.13, p&lt;0.01; ITT: -0.20, 95%CI -0.38, -0.02, p=0.03). A responder analysis (improved A1C; without severe hypoglycemia or increase in insulin dose; nor abnormal beta-hydroxybutyrate or lactic acid) revealed 42% TTP399 responders vs. 12% PL (ITT: p&lt;0.01, hierarchically controlled [HC]). Daytime TIR improved (ITT: 7.81%, 95%CI 0.93, 14.68, p&lt;0.05, HC). Treatment-emergent adverse events were numerically lower with TTP399. No safety signals were identified.
These data suggest that further development of TTP399 as adjunctive therapy in T1D is warranted.

Disclosure
J.B. Buse: Consultant; Self; Cirius Therapeutics, CSL Behring, Neurimmune. Research Support; Self; American Diabetes Association, National Institutes of Health, Novo Nordisk A/S, Patient-Centered Outcomes Research Institute, Sanofi, Tolerion, Inc., vTv Therapeutics. Stock/Shareholder; Self; Mellitus Health, Pendulum Therapeutics, PhaseBio Pharmaceuticals, Inc., Stability Health. Other Relationship; Self; ADOCIA, AstraZeneca, Dance Biopharm Holdings, Inc., Eli Lilly and Company, MannKind Corporation, NovaTarg Therapeutics, Novo Nordisk A/S, Senseonics, Inc, vTv Therapeutics, Zafgen, Inc. K. Klein: None. J.L. Freeman: Employee; Self; vTv Therapeutics. Stock/Shareholder; Self; vTv Therapeutics. Stock/Shareholder; Spouse/Partner; vTv Therapeutics. I. Dunn: None. C. Valcarce: Employee; Self; vTv Therapeutics.

Funding
JDRF; vTv Therapeutics; National Institutes of Health (UL1TR002489)
122-OR: Profile of Type 2 Diabetes (T2D) Donors in the Integrated Islet Distribution Program (IIDP)
Authors: OLACK BARBARA J. , KILBURN JULIE , CHUANG JIA-NING J. , CRAVENS JAMES , NILAND JOYCE C. 
Published: June 2020

The IIDP has been supplying isolated human islets and corresponding data from nondiabetic (ND) donors to diabetes researchers for &gt; 15 years. Since 2010 IIDP also has offered islets from T2D donors, with up to 68% of IIDP researchers interested in receiving them. From 2010-19, this unique desirable resource comprised 7.3% of IIDP isolations (98/1,333). Analysis of ND vs. T2D donor demographics showed similar trends (p=0.94) by sex (M/F ratio 1.37 vs. 1.39, respectively). Donor race/ethnicity differed significantly (p&lt;0.001), with a higher rate of Hispanic in T2D (White: ND 64.0%, T2D 43.9%; Hispanic: ND 20.5%, T2D 40.8%; Black: ND 11.1%, T2D 13.3%; Other [Asian, Hawaiian, Native American]: ND 4.4%, T2D 2.0%). This finding is in line with CDC data that Hispanics are more likely to develop T2D. Median donor age differed significantly (p&lt;0.001), with a median of 46 yrs in ND (range: 4-73) vs. 53 yrs in T2D (range: 26-69). Body Mass Index (BMI) was significantly higher for T2D donors (p&lt;0.001), with ND median of 29.2 (range: 11.8- 64.8) vs. 32.5 for T2D (range: 20.7-50.0). Cause of Death (COD) also differed significantly (p=0.003), with a higher rate of stroke for T2D (50.1% for ND vs. 68.4% in T2D), and higher head trauma in ND (31.2% ND vs. 13.3% T2D); other COD was 18% for both donor types. This difference is likely due to higher cardiovascular disease among T2D Americans. While median total islet equivalents (IEQ) yield was significantly higher (p=0.017) for ND donors (ND median IEQ: 278,792, range 35,000-1,015,455 vs. T2D median IEQ: 221,734, range 50,000-1,032,212), this difference was not as great as expected. A previous IIDP publication showed COD and BMI can affect islet yield. Evaluating the difference in yield between ND and T2D remained significant (p=0.02) after adjusting for these factors, with BMI category being a significant covariate, while COD was not significant in this relatively small sample. Perhaps as our sample of these unique donors grows additional associations with islet yield may emerge.

Disclosure
B.J. Olack: None. J. Kilburn: None. J.J. Chuang: None. J. Cravens: None. J.C. Niland: None.

Funding
2UC4DK098085-02
1220-P: Inequities in Health Outcomes among Patients in the T1DX-QI Collaborative
Authors: MAJIDI SHIDEH , EBEKOZIEN OSAGIE , NOOR NUDRAT , RIOLES NICOLE , FEGAN-BOHM KELLY , MCDONOUGH RYAN , GANDHI KAJAL , BUNKER CASSANDRA , JONES NANA-HAWA 
Published: June 2020

Inequities in health care delivery and outcomes continue to exist in the field of medicine, despite increased awareness of racial and ethnic inequities. To inform future research on the barriers to care and potential interventions to improve diabetes care for individuals from all backgrounds, it is important to use large cohorts to identify these disparities. T1D Exchange QI (T1DX-QI) is a population-based cohort with twelve national clinics engaged in data sharing and quality improvement (QI) methods to drive system changes. Over 22,000 pediatric and adult patient demographic and diabetes characteristics data were combined and analyzed from seven T1DX-QI clinics. Characteristics of the patient population are available in Table 1. The cohort included 75% non-Hispanic White (NHW), 7% non-Hispanic Black (NHB), 3% Hispanic and 15% Other. Mean A1C was highest in NHB (9.9%) and Hispanic (9.3%; p&lt;0.001) participants. Insulin pump and continuous glucose monitor use was lowest in NHB participants (p&lt;0.001). The T1DX-QI cohort is the largest population to date available to investigate health inequities in T1D. Differences in A1C and technology use still persist, particularly in the NHB population. These results highlight the critical need to study barriers to care in individuals from various backgrounds in order to provide adequate and optimal care to everyone with T1D.

Disclosure
S. Majidi: Advisory Panel; Self; Companion Medical. O. Ebekozien: None. N. Noor: None. N. Rioles: None. K. Fegan-Bohm: None. R. McDonough: None. K. Gandhi: None. C. Bunker: None. N. Jones: None.
1221-P: Reducing Waste for Patients Dispensed an Insulin Pen Using the "Special Limited Community Permit"
Authors: HIERS PAUL 
Published: June 2020

Problem: Historically, an institutional class II pharmacy could not legally dispense multi-dose medications from the inpatient supply. Therefore, bulk medications such as insulin pens were disposed after hospital discharge. This resulted in unnecessary medical waste. Through the 2014 amendment of Florida Administrative Rule 64B16-28-810, the University of Florida Pharmacy obtained a “special limited community permit” to legally dispense used inpatient insulin pens. Starting in July 2016, this project aimed to utilize this permit for patients with diabetes (picture #1).
Methods: Pediatric patients receiving insulin from July 2016 to July 2019 were included in the analysis. Inpatient insulin usage was tracked. The amount of insulin units remaining (total dispensed minus total administered) was calculated as the total potential waste per patient.
Results: 220 unique insulin pens were dispensed in 128 different patient encounters. The total amount of insulin saved was 55,920 units, the equivalent of 186 insulin pens. At an average cost of $85 per insulin pen, 186 insulin pens is approximately $15,735 of cost savings to the health care system.
Conclusions: The “special permit” has reduced waste for the hospital and provided patients with needed medications. Ideally, this process would be disseminated to other institutions, helping more patients with diabetes and reducing insulin waste.

Disclosure
P. Hiers: None.
1223-P: Diabetes in Pregnancy in the Caribbean: A Systems Enablement Approach to Universal Access, Screening, and Treatment
Authors: TEELUCKSINGH SURUJPAL , CHOW HYACINTH , LUTCHMANSINGH FALLON K. , RAMSEWAK SAMUEL 
Published: June 2020

In Trinidad and Tobago there is a high background prevalence of diabetes in women of reproductive age and wide variability of screening practices for diabetes in pregnancy (DiP). A systems enablement approach was implemented to achieve national consensus on clinical guidelines and facilitate universal screening. A secure ICT solution (app) for real-time communication of blood glucose results was designed and piloted to standardize reporting systems and integrate services for pregnancy care. National consensus was achieved through consultations with healthcare professionals and followed up with training on the standardized guidelines for DIP and continuous medical education for over 300 in the field to improve adoption. The app facilitated a system of data capture, storage and retrieval among antenatal caregivers, patients and health administrators. The app is scalable and can integrate with other standards-based ICT health systems. The app was pilot tested and 658 pregnant women, 7 lab technologists and 24 doctors were trained registered users. All pregnant women registered on the app were screened using a standard 75g 2-hour OGTT after an overnight fast. Gestational diabetes prevalence was 14.1%. The high GDM prevalence justifies a need for systems change and universal screening for diabetes in pregnancy in Trinidad and Tobago. The app facilitates timely delivery of results to patient and healthcare provider. Training healthcare teams in diagnosis and management of diabetes in pregnancy using ICT simultaneously provides the platform to enhance patient self-management.

Disclosure
S. Teelucksingh: None. H. Chow: None. F.K. Lutchmansingh: None. S. Ramsewak: None.