bluuebunny/crossref_metadata_2025 huggingface dataset:
1175-P: Racial Difference in Diabetes Medication Initiation
Authors: WINN AARON N. , KARTER ANDREW J. , STAAB ERIN M. , LIU JENNIFER , WAN WEN , SKANDARI REZA , KNITTER ALEXANDRA C. , MOFFET HOWARD H. , MILLER DONALD R. , PEEK MONICA E. , HUANG ELBERT , LAITEERAPONG NEDA
Published: June 2020

Objective: We examined how diabetes medication initiation after first diagnosis varied by race/ethnicity.

Method: We conducted a retrospective cohort study of 66,939 patients with newly diagnosed diabetes using data from a large integrated healthcare system. We classified patients into 12 race/ethnicity groups (see Table) and assessed their associations with diabetes medication initiation within 1, 12 and 18 months after diagnosis. We used a modified Poisson regression to estimate risk ratios adjusted for pre-diagnosis demographics and clinical characteristics.

Results: Medications were started in 30%, 43% and 48% of patients within 1, 12 and 18 months, respectively. Within 1 month of diagnosis, Chinese, Filipino, and Native Hawaiian/Pacific islander were less likely to initiate a medication compared to whites. Results were consistent at 12 and 18 months, except that Japanese and blacks/African Americans were less likely to initiate compared to whites and that there was no difference between Native Hawaiian/Pacific islanders and whites at 18 months.

Conclusions: We observed persistent racial differences between patients receiving any medication following initial diabetes diagnosis, with the largest differences for several Asian populations.

Disclosure

A.N. Winn: None. A.J. Karter: Research Support; Self; Dexcom, Inc. E.M. Staab: None. J. Liu: None. W. Wan: None. R. Skandari: None. A.C. Knitter: None. H.H. Moffet: None. D.R. Miller: None. M.E. Peek: Research Support; Self; Merck Foundation. E. Huang: None. N. Laiteerapong: None.
1177-P: Impact of Proactive Strategies by a Large Self-Insured Employer on Engagement in the Diabetes Prevention Program (DPP)
Authors: MCEWEN LAURA N. , JOINER KEVIN , BERGMANS RACHEL , HURST THOMAS E. , HERMAN WILLIAM H.
Published: June 2020

Since 2015, the University of Michigan has offered the DPP at no out-of-pocket cost to its employees, dependents, and retirees with prediabetes (pDM). We assessed the yield of 3 proactive engagement strategies. In strategy A, 6,734 adults with no previous diagnosis of diabetes (DM) but with a claims diagnosis of pDM or A1c 5.7-6.4% were identified and mailed letters encouraging them to enroll in a DPP. In strategy B, 5,219 adults with no previous diagnosis of DM or pDM who were at high-risk for pDM or DM based on age, sex, and claims data on obesity, hypertension, and dyslipidemia were identified and mailed letters encouraging them to get an A1c test. In strategy C, 29,878 employees not targeted by strategies A or B were sent emails encouraging them to take an online risk test and, if positive, to get an A1c test. In general, individuals identified by strategies A and B were older, had higher BMIs, and were more likely to have cardiovascular (CV) risk factors or CV disease than those identified by strategy C. Of those targeted by strategy A, 649 (10%) enrolled in a DPP. Those who enrolled were more likely to be older, female, and to have a higher BMI than those who did not enroll. Of those targeted by strategies B and C, 1,402 (27%) and 3,768 (13%), respectively, had A1c tests or received new diagnoses of pDM or DM within 1-year of receiving the letter/email. In general, those who had A1c tests or were diagnosed with pDM or DM were more likely to be female, non-White, to have a higher BMI, and to have more CV risk factors or CV disease than those not tested or diagnosed. Of individuals tested in response to strategies B and C, 561 (40%) and 583 (15%) were diagnosed with pDM and 68 (12%) and 5 (1%) enrolled in a DPP. Together, these 3 complimentary strategies to encourage engagement in a DPP had a yield of 9% among individuals with pDM, which is substantially greater than the ∼0.0001% yield observed when passive strategies are employed, but not high enough to have a substantial impact on the population incidence of DM.

Disclosure

L.N. McEwen: None. K. Joiner: None. R. Bergmans: None. T.E. Hurst: None. W.H. Herman: Consultant; Spouse/Partner; Nestlé. Other Relationship; Self; Merck Sharp & Dohme Corp.

Funding

National Institutes of Heath (1R01DK109995)
118-OR: HLA Matching and Clinical Outcomes in Islet Transplantation
Authors: FUENMAYOR VIRGINIA , CHAVEZ CARMEN , BAIDAL DAVID , ALVAREZ ANA M. , PADILLA NATHALIA , RICORDI CAMILLO , ALEJANDRO RODOLFO
Published: June 2020

Islet cell transplantation (ITx) is a treatment option for selected patients with type 1 diabetes mellitus (T1D) affected by severe hypoglycemia. In whole organ transplantation, HLA mismatching has been shown to negatively impact transplant outcomes. However, this has not been studied in ITx and currently, HLA matching is not a criteria for donor selection. The aim of this study was to determine whether HLA matching has an impact on islet allograft survival. We evaluated 50 ITx recipients at the Diabetes Research Institute, University of Miami, who have been followed from 2000 to 2019. Out of the 50 subjects, 7 underwent islet after kidney transplantation and 43 islet transplantation alone. Subjects received an average of 2 islet infusions from 1 to 5 donors. We evaluated whether the number of HLA-A, -B, and -DR matches were associated with Graft Dysfunction and Graft Failure events using Kaplan-Meier Analysis, including log-rank and Wilcoxon tests statistics. Analyses did not show a significant association between HLA matching and allograft survival (p>0.05). Nevertheless, our study is limited by the small sample size, use of multiple donors as well as differences in immunosuppression regimens and use of GLP-1 analogs and DPP-4 inhibitors which may have affected outcomes. HLA mismatching did not affect ITx outcomes in our study cohort. Further studies are necessary to determine if HLA matching plays a significant role in ITx graft survival.

Disclosure

V. Fuenmayor: None. C. Chavez: None. D. Baidal: None. A.M. Alvarez: None. N. Padilla: None. C. Ricordi: None. R. Alejandro: None.

Funding

Diabetes Research Institute Foundation; The Leona M. and Harry B. Helmsley Charitable Trust; University of Miami Clinical and Translational Science Institute
1181-P: Glycemic Relapse: Major Threat to Ongoing Improvement in Diabetes Care
Authors: SPERL-HILLEN JOANN M. , VAZQUEZ-BENITEZ GABRIELA , HAAPALA JACOB , DESILVA MALINI B. , O’CONNOR PATRICK J.
Published: June 2020

Purpose: Adequate glycemic control is a cornerstone of high quality diabetes care. Improvement in glycemic control is the net of two vectors: the number of patients who newly achieve glycemic control (improvement vector), minus the number of patients who relapse from adequate to inadequate glycemic control (relapse vector). The purpose of this analysis s to quantify the improvement and relapse vector in a single large care delivery system.

Methods: We identified all T2D patients having at least one visit and A1c between 1/1/2017 and 5/31/2018. We selected as the index date the first visit with an A1c < 8% for the controlled cohort; and the first visit with an A1c ≥ 8% for the uncontrolled cohort. We followed patients for 12 months after the index date and selected the first A1c that shifted their glucose status.

Results: Although the percent of patients with base A1c >=8% who improved (59%) far exceeded the percent of those with baseline A1c <8% who relapsed (20%), the absolute number of patients relapsing (5,109) exceeded the number improving (4,132), with a 30 per 1,000 episodes net worsening in quality of diabetes control (Table 1).

Conclusions: In this high-performing care system the relapse vector now exceeds the improvement vector, accounting for recent overall deterioration in population levels of glucose control. Strategies to proactively identify and manage patients at high risk for glycemic relapse are urgently needed.

Disclosure

J.M. Sperl-Hillen: None. G. Vazquez-Benitez: None. J. Haapala: None. M.B. DeSilva: None. P.J. O’Connor: None.

Funding

National Institute of Diabetes and Digestive and Kidney Diseases (U01DK098246)
1184-P: Factors Associated with HbA1c of Less Than 8% among Patients Initiated with Metformin and SGLT2 Inhibitor Dual Therapy in the United States
Authors: LAUTSCH DOMINIK , YANG LINGFENG , RAJPATHAK SWAPNIL , BANSAL NEHA , KATHE NIRANJAN
Published: June 2020

Background: Metformin is the first line treatment for type 2 diabetes mellitus. Sodium glucose cotransporter 2 inhibitors (SGLT2i) are a novel class of oral antidiabetic agents. We aimed to understand factors associated with attaining the HbA1c threshold of <8% in the United States.

Methods: Observational, retrospective cohort study in adult type 2 diabetes mellitus patients from IQVIA EMR database. Observation period was June 2015 to June 2018. Patients needed to initiate SGLT2i and metformin without other antihyperglycemic agents. The impact of sociodemographic factors on achievement of HbA1c <8% was tested using multivariable logistic regression with backward stepwise selection using SAS 9.4.

Results: Of 3491 patients in the final cohort, 2176 (62.3%) achieved HbA1c <8%. The remaining patients had a median distance to goal of 1.1% (IQR 0.5-2.3%). Mean age was 56.5 year. 52.6% were male. Black patients had lower odds to attain HbA1c <8% than white patients [OR 0.69 (0.57, 0.85)], while patients <65 years of age had non relevant higher odds [OR 1.01 (1.01, 1.02)], Table 1.

Conclusion: In the real world in the U.S., 62% of patients treated with metformin and an SGLT2i had an HbA1c <8%. Black patients had lower odds to attain this threshold.

Disclosure

D. Lautsch: Employee; Self; Merck & Co., Inc. L. Yang: Employee; Self; Merck & Co., Inc. S. Rajpathak: Employee; Self; Menarini Group. N. Bansal: None. N. Kathe: None.

Funding

Merck & Co., Inc.
1186-P: Effectiveness of a Community-Based Approach Towards the Treatment and Prevention of Diabetes Mellitus in Rural India
Authors: SHAH SHIVESH , PRASAD KRANTHI , SABOO BANSHI D. , SHAH SHAILIN , HASNANI DHRUVI , CHAVDA VIPUL , HCB KALACHAR , MERUVA RAVI K.
Published: June 2020

Background: High rates of diabetes have been reported throughout urban India, though limited data exists concerning the prevalence of diabetes in rural areas, where 70% of the population resides. Socioeconomic and cultural differences may necessitate a different approach towards the treatment and prevention of diabetes in rural as opposed to urban areas.

Objective: The aim of this study was to evaluate the efficacy of a novel, community-centered model in rural villages of Hyderabad, India over the course of 6 months and compare results to traditional methods currently used by rural clinics in Ahmedabad, India.

Methods: As opposed to traditional methods that rely on direct patient-provider interaction, our community-centered method relied on a four-tier system consisting of providers, leaders of each village, “ambassadors” within each village, and patients. A total of 1,013 individuals aged ≥ 25 years (mean age 47.2 years) were sampled at random gender and age from 12 villages in Hyderabad and Ahmedabad. Vitals were taken and blood glucose was measured in all participants using a GlucoSpark glucometer. Baseline statistics were similar for both populations.

Results: In villages surrounding Hyderabad, the prevalence of diabetes was 9.6% (95% CI 7.2-11.9), of which 6.2% (5.1-7.3) were known cases and 3.4% (2.2-4.6) had not previously been diagnosed. The prevalence of diabetes in Ahmedabad was determined to be 12.9% (10.8-15.1), with 5.2% (3.8-6.6) diagnosed and 7.7% (6.2-8.2) previously undiagnosed. Notably, average glucose levels in the Hyderabad population were significantly lower than in the Ahmedabad population after 6 months (t=3.3, p<0.001).

Conclusion: While this study is not representative of rural India as a whole, it highlights the importance of community-centered health in rural settings. Findings suggest that approaches towards diabetes treatment, prevention, and education should vary with patient populations and be considered carefully.

Disclosure

S. Shah: None. K. Prasad: None. B.D. Saboo: None. S. Shah: None. D. Hasnani: None. V. Chavda: None. K. Hcb: None. R.K. Meruva: None.
119-LB: Metformin Prescriptions in Chronic Kidney Disease Patients after the Revised FDA Recommendations in 2016
Authors: MIN JEA YOUNG , WU XIAN , ORLOFF JEREMY , MUSHLIN ALVIN I. , FLORY JAMES
Published: June 2020

Background: In 2016, metformin’s prescribing label was revised to permit it to be started with estimated glomerular filtration rate (eGFR) 45-60 ml/min and continued with eGFR 30-44 ml/min. We examined whether subsequent metformin prescribing in these groups increased.

Methods: We conducted an interrupted time series study using data from the New York City Clinical Data Research Network. We identified episodes from 2014-2017 in which adult patients with HbA1c ≥6.5% received outpatient antidiabetic prescriptions ≤7 days after an eGFR measurement. Trends in the proportion of episodes that included metformin were examined using linear regression in 4 eGFR subgroups: ≥60 (reference), 45-59, 30-44, and <30 ml/min. Sensitivity analysis examined episodes with no antidiabetic prescription in the prior 180 days.

Results: We identified 10,608 prescribing episodes among 6,505 patients. Lower eGFR was associated with less metformin prescribing. In the eGFR 30-44 ml/min group, there were significant increases in metformin prescribing after the label change (p<0.001). In sensitivity analysis, an increasing trend in metformin prescriptions in the 45-59 ml/min eGFR group started before the label change (p=0.04) and leveled off.

Conclusion: Metformin prescribing for patients with eGFR 30-60 ml/min was increasing prior to the label change. Rates of metformin use at eGFR 30-45 ml/min remain relatively low.

Disclosure

J. Min: None. X. Wu: None. J. Orloff: None. A.I. Mushlin: None. J. Flory: None.

Funding

Patient-Centered Outcomes Research Institute (CER-9230)
1194-P: Unbinding Constraints on Clinical Inertia and Improving Practices: A Novel Comprehensive Primary Care Approach that Grew a Single Practice of 2,000 Patients to 40,000 Patients in Less than 4 Years
Authors: AGUILAR RICHARD B. , OSORIO MERLIN , MCGOOHAN JOHN , HERNANDEZ MARLOW , HERMAN MARY , MILLER EDEN , CONGER MORGAN
Published: June 2020

Background: Cano Health (CH) employs a full risk model for their Medicare Advantage (MA) enrollees. In 2014, CH deployed a multipronged practice care management processes (CM) devised to overcome clinical inertia, streamline administration of care, and, standardize performance.

Description and Outcomes: CH approach builds on supporting physicians through decision aids, protocols. and larger coordination enabled through technology. Selected components and metrics and ’hard’ outcomes of CH’s approach is detailed in [Table 1].

Conclusions/Lessons Learned: Stand-out results were attained with strategic e-medicine and human resource processes and touchpoints. CH providers were enabled to expeditiously intensify care where clinical inertia persists.

CH model has proven reproducible, enduring and scalable; CH met or surpassed U.S. averages for metrics and ’hard’ endpoints for MA enrollees for management of diabetes and other conditions, growing CH from 1 to 52 PC facilities, 14 to 135 MDs, and, 2k to 40k patients in <4Y.

Disclosure

R.B. Aguilar: None. M. Osorio: None. J. McGoohan: None. M. Hernandez: None. M. Herman: None. E. Miller: None. M. Conger: None.
12-OR: Participation in a Virtual Diabetes Clinic and Reduced Diabetes-Related Distress in Individuals with Type 2 Diabetes
Authors: POLONSKY WILLIAM H. , LAYNE JENNIFER E. , PARKIN CHRISTOPHER G. , KUSIAK COCO , BARLEEN NATHAN A. , MILLER DAVID P. , ZISSER HOWARD , DIXON RONALD F.
Published: June 2020

Diabetes-related distress affects a significant proportion of adults with type 2 diabetes (T2D) and is associated with poor glycemic control and more problematic self-management. The Onduo Virtual Diabetes Clinic (VDC) is a telehealth program for people with T2D that combines mobile App technology, remote personalized lifestyle coaching, connected BG meters, real-time continuous glucose monitoring (rtCGM) devices and clinical support from board-certified endocrinologists.

This exploratory analysis evaluated change in diabetes distress among 228 program participants who reported moderate distress (score 2.0-2.9) or severe distress (score ≥3.0) on the diabetes distress scale (DDS17) at enrollment. Change in diabetes-related distress was also compared for rtCGM vs. non-rtCGM user groups. Participants were age 51.8±9.5 years, 73.2% female and 39.5% were on insulin. During program participation, 94.7% used a connected BG meter and 33.8%, deemed to be high risk, used rtCGM intermittently. Participants reported significant reductions in overall DDS17 score, from 3.0±0.8 at baseline to 2.5± 0.9 (p<0.001) at an average of 6 months follow-up. Significant reductions in all DDS subscale scores were observed; most notable were reductions in the regimen-related and emotional distress subscales (-0.9 and -0.4, respectively; both p<0.001). Diabetes-related distress improved significantly in both CGM and non-rtCGM users. However, greater reductions in overall DDS17 score, -0.7 ± 0.8 vs. -0.4±0.9 (p=0.012), and regimen-related distress, -1.3±1.2 vs. -0.7±1.3 (p<0.001), were reported by participants who were prescribed and used intermittent rtCGM (n=77) vs. non-users (n=151).

These findings suggest that the VDC program, which includes ongoing individualized lifestyle, clinical support and use of connected devices, may be an effective approach to support individuals with T2D and clinically relevant diabetes distress.

Disclosure

W.H. Polonsky: Advisory Panel; Self; Intarcia Therapeutics, Roche Diabetes Care. Consultant; Self; Abbott, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Novo Nordisk Inc., Onduo, Sanofi US, Xeris Pharmaceuticals, Inc. J.E. Layne: Employee; Self; Onduo. C.G. Parkin: Consultant; Self; Abbott, CeQur Corporation, Dexcom, Inc., DreaMed Diabetes, Novo Nordisk Inc., Onduo, Roche Diabetes Care, Valeritas, Inc. C. Kusiak: Employee; Self; Verily Life Sciences LLC. Stock/Shareholder; Self; Verily Life Sciences LLC. N.A. Barleen: Employee; Self; Onduo. D.P. Miller: Employee; Self; Verily Life Sciences LLC. Stock/Shareholder; Self; Verily Life Sciences LLC. H. Zisser: Employee; Self; Verily Life Sciences LLC. Stock/Shareholder; Self; Verily Life Sciences LLC. R.F. Dixon: Employee; Self; Onduo.
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 (<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>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 >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 <0.001), and six months (ΔA1c: -0.4 %, p <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<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<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<0.01, hierarchically controlled [HC]). Daytime TIR improved (ITT: 7.81%, 95%CI 0.93, 14.68, p<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 > 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<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<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<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<0.001) participants. Insulin pump and continuous glucose monitor use was lowest in NHB participants (p<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.
1229-P: Clinical Characteristics and Hospital Care among Patients with Diabetic Ketoacidosis
Authors: LIU AIQUN , CARMICHAEL KIM , SCHALLOM MARILYN , ARROYO CASSANDRA
Published: June 2020

Although the mortality rate associated with DKA has significantly reduced, hospitalizations for DKA are increasing. Identifying contributing factors for DKA admission could help target prevention efforts.

Aims: To explore risk factors for DKA admissions, investigate clinical characteristics of DKA among hospitalized patients, and describe inpatient DKA management and discharge plan.

Methods: We performed a retrospective analysis of adult patients’ medical records for DKA admissions from April-December 2017. Admission records from the year prior to 2017 review time period were also reviewed.

Results: Of 200 patients, 79 (39.5%) had pre-existing T1D, 94 (47%) had pre-existing T2D, 12 (6%) had new-onset DM, and 15 (7.5%) had other type of diabetes. Metabolic acidosis was more severe in patients with T1D than in those with T2D. Most patients (61.8%) were admitted to ICU. Mean ICU stay was 1.6±3.1 days, and mean hospital stay was 5.4±9.0 days. Insulin (93%) and fluid (95%) infusion were used for initial DKA treatment. Sixty-four (35%) had ≥1 hypoglycemic event, and 29 (14.5%) had a recurrent DKA event during hospitalization. Mortality rate was 2.5% (n=5); 1 patient death (0.5%) was directly related to DKA. Prior DKA admission was observed in 62 (31%) with mean of 2.1±3.9 admissions and were more common in African Americans, patients 18-39 years of age, and those with a history of bipolar disorder or pancreatitis. Nonadherence to home insulin regimen was the predominant precipitating cause of prior DKA admissions. Majority of patients (84.5%) were discharged to home, of whom 41% received medication delivery, 64.2% had a scheduled follow-up appointment, and 21% had a home healthcare referral.

Conclusions: Although patients with T1D had more severe acidosis, DKA admission in patients with T2D is as common as in those with T1D. Nonadherence is the leading precipitating factor of DKA readmissions. Future efforts should focus on reducing DKA recurrence and admission among vulnerable populations.

Disclosure

A. Liu: None. K. Carmichael: None. M. Schallom: None. C. Arroyo: None.
1233-P: Prediction of Type 2 Diabetes Occurrence Using Machine Learning Model
Authors: DEBERNEH HENOCK M. , KIM INTAEK , PARK JAE HYUN , CHA EUNSEOK , JOUNG KYONG HYE , LEE JONG SEON , LIM DONG SEOK
Published: June 2020

Prediction of type 2 diabetes (T2D) occurrence allows a person at risk to take preventive actions that can prevent or delay the progression of the disease. In this study, we aim to develop a machine learning (ML) model to predict T2D occurrence in the year Y+1 using the variables in the year Y. The dataset was collected from electronic health records between 2013 and 2018 at a medical agency. We utilized 169,024 instances from 80,692 patients with longitudinal data to build the ML model. Each instance has 1,444 variables. To construct a prediction model, key variables or features were first selected using ANOVA and chi-square tests, and the recursive feature elimination methods. Then we employed random forest (RF) and XGBoost algorithms based on these variables to predict the outcome as normal, prediabetes or diabetes. Selected variables were fasting plasma glucose (FPG), HbA1c, triglycerides, body mass index (BMI), r-GTP, gender, age, uric acid, smoking, drinking, physical activity and family history. The accuracy of the RF classifier in predicting the occurrence in next year was 73.3% while that of the XGBoost classifier was 73.8%. The proposed prediction model using ML can provide both clinicians and patients with valuable information on the immediate incident of T2D. In addition to traditional predictors of T2D (FPG, HbA1c, BMI, family history), it should also be noted that variables such as r-GTP, uric acid, triglycerides, and lifestyle factors in the year Y increased the accuracy up to 3% in predicting T2D occurrence in the year Y+1.

Disclosure

H.M. Deberneh: Consultant; Self; Health connect. I. Kim: Consultant; Self; Health Connect. J. Park: Employee; Self; health connect. E. Cha: None. K. Joung: None. J. Lee: Employee; Self; health connect. D. Lim: Employee; Self; health connect.
1234-P: Utility of Sliding Scale Insulin on Inpatient Glycemic Care of Type 2 Diabetes Mellitus
Authors: ARAO KEVIN A. , EBADI FARHA N. , CAPISTRANO MARIA CHRISTINA VICTORIA M. , CHEN KENNETH K.
Published: June 2020

Background: According to the American Diabetes Association (ADA), sliding scale insulin (SSI) monotherapy as inpatient diabetes management is strongly discouraged. The focus of our study is to determine the use of SSI on patients with type 2 diabetes mellitus (T2DM) on oral agents admitted to the general medical floor in a community hospital.

Methodology: A chart review was performed on patients with T2DM on oral agents admitted as an inpatient to our community hospital, from July 1, 2018 to July 1, 2019, that had SSI ordered. Patients were excluded if they were admitted to the ICU or had surgical intervention. Diabetes management was determined which can include additional basal and prandial insulin or continuation of home oral medication. Other data obtained included demographics, blood glucose levels, hypoglycemia (<70 mg/dl), recent hemoglobin A1c level (HbA1c), and length of hospital stay.

Results: After 242 patient charts were reviewed, a total of 105 patients met exclusion criteria. In the 137 included patients, the mean age was 72.4 years, mean HbA1c level of 7.5%, and 55.4% were men. The mean length of hospital stay was 5.9 days. Most of the patients received SSI alone (n=108, 78.8%) followed by SSI with home oral medications (n=27, 19.7%), and lastly SSI with basal insulin (n=2, 1.5%). Mean blood glucose level was elevated in patients who had SSI with basal insulin (193.5mg/dL) and SSI alone (182.8mg/dL). On all included patients, six had hypoglycemia and all of them received SSI alone. Of the two patients who received basal insulin, they were provided with less basal insulin dose compared to weight-based calculation.

Conclusion: SSI is commonly used as monotherapy for inpatient diabetes management despite having recommendations against its use. SSI monotherapy is associated with increased rates of hypoglycemia episodes and poor glycemic control. Quality improvement interventions will be initiated among providers with regard to the appropriate inpatient diabetic care to improve patient care.

Disclosure

K.A. Arao: None. F.N. Ebadi: None. M.M. Capistrano: None. K.K. Chen: None.