bluuebunny/crossref_metadata_2025_split huggingface dataset:
1913-LB: Observed Glycemic and Psychosocial Benefits in the Prospective Bigfoot Unity Real World Study (BURST)—A 6-Month Analysis
Authors: TILLMAN JOHN , BECK ROY , POLONSKY WILLIAM H. , CALHOUN PETER , MOUSE THOMAS J. , BAILEY RYAN , JACOBY JEANNE , NANDAN RAKESH , MALONE JAMES K. 
Published: June 2024

Introduction & Objective: The Bigfoot Unity® System is an FDA-cleared smart pen cap system incorporating CGM data (Abbott FreeStyle Libre 2), real-time alerts, and clinician-directed insulin dose recommendations. The objective was to analyze real world, 6-month data for System users.
Methods: We conducted a per-protocol 6-month analysis (N=102) from the prospective, BURST study (NCT05088265). Participants completed baseline, adverse event and patient reported outcome surveys electronically. A1C data were from a home kit or electronic medical record.
Results: Median age was 59 years, 87% had T2D, 42% used CGM previously, 62% were White non-Hispanic and 59% female. Mean A1C decreased from 9.1±1.7% at baseline to 8.0±1.2% at 6 months (mean difference -1.1%, 95%CI -1.4, -0.8; p&lt;0.001). Six severe hypoglycemia events in 4 participants (none System related) and no DKA occurred. Diabetes Distress Scale scores decreased (mean difference -0.7, 95%CI -0.9, -0.5; p&lt;0.001) and Hypoglycemia Confidence Scale scores increased (mean difference 0.4, 95%CI 0.2, 0.5; p&lt;0.001) with System use (Table).
Conclusion: Glycemic improvement along with reduced diabetes distress and increased hypoglycemia confidence occurred using Bigfoot Unity for 6 months. The reduction in A1C occurred while meeting established hypoglycemia targets of &lt;4 and &lt;1% for percent time below 70 and 54 mg/dL, respectively.

Disclosure
J. Tillman: Employee; Abbott. R. Beck: Consultant; Insulet Corporation. Research Support; Insulet Corporation. Consultant; Tandem Diabetes Care, Inc. Research Support; Tandem Diabetes Care, Inc. Consultant; Beta Bionics, Inc. Research Support; Beta Bionics, Inc., Dexcom, Inc., Bigfoot Biomedical, Inc. Consultant; Novo Nordisk. Research Support; Novo Nordisk, Eli Lilly and Company. Consultant; embecta, Vertex Pharmaceuticals Incorporated, Hagar, Ypsomed AG, Sanofi, Zucara Therapeutics, Sequel. W.H. Polonsky: Research Support; Abbott Diagnostics, Dexcom, Inc. Consultant; Eli Lilly and Company, Sanofi. Advisory Panel; embecta. Consultant; Vertex Pharmaceuticals Incorporated. Advisory Panel; 9am Health. P. Calhoun: None. T.J. Mouse: Research Support; Bigfoot Biomedical, Inc., MannKind Corporation. R. Bailey: None. J. Jacoby: Employee; Bigfoot Biomedical, Inc., Beta Bionics, Inc., Sequel Med Tech. R. Nandan: Employee; Abbott, Bigfoot Biomedical, Inc. J.K. Malone: Employee; Bigfoot Biomedical, Inc., Abbott.

Funding
Abbott
1921-LB: A Wavelet AI Algorithm to Identify Postprandial Glucose Responses from CGM Profiles
Authors: LIM WANSANG , BARUA SOUPTIK 
Published: June 2024

Objective: AI algorithms can potentially identify postprandial glucose responses (PPGR) directly from continuous glucose monitoring (CGM) data, reducing the burden of manual meal logging and PPGR interpretation. However, no standard AI approach for this task currently exists.
Methods: We developed a wavelet AI algorithm to identify PPGRs using a public CGM dataset (Hall'18) from individuals without a prior diagnosis of diabetes (Fig 1). The dataset also included clinic-recorded meal timings on a subset of days. Briefly, the algorithm works by computationally finding the best match for a template shape (the wavelet) in a time series. The algorithm was trained using a 5-fold cross-validation approach, and evaluated using two measures: (i) the time difference between true and predicted PPGR start times, and (ii) the ratio of predicted to true 2-hr area under the PPGR curve (AUC).
Results: We tested our algorithm on 19 participants with 2±1 days of both CGM data and clinic-recorded meal timings. The wavelet algorithm predicted start time of PPGR to within a median 15 [10,26] minutes of true meal time. The median ratio of predicted to true 2-hr AUC PPGR was 1.01 [1.00,1.02], indicating the wavelet algorithm’s ability to faithfully capture the PPGR.
Conclusion: A wavelet AI algorithm accurately identified PPGRs from CGM data, providing a novel automated approach to evaluate the effect of different foods on an individual’s glycemia.

Disclosure
W. Lim: None. S. Barua: None.

Funding
Abramson-Stires award from NYUGSOM Department of Medicine
193-OR: Virtual Diabetes Optimization Program vs. Standard Endocrine Care for Veterans with Uncontrolled Diabetes
Authors: ADEL THOMAS , SHERMAN KATHERINE , HANSEN JILL M. , TAXMAN JILLIAN , REETZ-NORTON MEGHANN E. , JOHNSON CHRISTOPHER , WHITTLE JEFF , MENDEZ CARLOS E. 
Published: June 2024

Nearly 25% of veterans have diabetes and 78% are considered overweight or obese. At the Milwaukee VA, a virtual multidisciplinary diabetes optimization program (VDOP) is available to veterans referred to endocrine specialty care. Patients above 18 years-old and with A1c ≥ 8% are offered participation in VDOP, and those who decline, proceed with standard endocrine appointments. VDOP patients are seen by a combination of a pharmacist, dietitian, and occupational therapist in staggered weekly visits under the supervision of a physician diabetologist for 3-6 months. To assess the effectiveness of VDOP, glycemic control, weight, and insulin requirements of 39 program graduates were compared to the 62 veterans that met criteria but declined to join in the same time period. Table 1 shows no significant differences in demographic data between the two groups. VDOP participants had an average of 21 visits versus 6 visits for the comparison group. VDOP participants showed a significant greater decrease in A1c, weight, and total daily insulin dose for measurements taken closest to 6-month mark. Based on these results and when compared to conventional endocrine care, VDOP more effectively helped veterans improve glycemic control, while promoting weight loss and decreased insulin doses. As the program expands, next steps are to examine cost utilization, quality of life, and impact in other clinical outcomes.

Disclosure
T. Adel: None. K. Sherman: None. J.M. Hansen: None. J. Taxman: None. M.E. Reetz-Norton: None. C. Johnson: None. J. Whittle: Research Support; AstraZeneca. C.E. Mendez: Consultant; Siemens Healthcare Diagnostics.
1940-LB: Implementation of an Inpatient Glucose Management Program in a Large U.S. Health System
Authors: CLORE JOHN N. , CALUAG KRISTEN , TEMPLE RICHARD M. 
Published: June 2024

Introduction: Translation of inpatient glycemic recommendations has been slow to occur. The recent consolidation of two large healthcare systems provided a unique opportunity to harmonize all ordersets and examine the impact on glycemic control.
Methods: A comprehensive revision of glycemic management was accomplished across the health system. All individuals admitted to any of 48 facilities with glucose &gt; 200 mg/dl were included with metrics of glycemic control designed to assess progress across the health system. An extensive multidisciplinary educational program was developed to provide rationale and guidance for providers. Best practice alerts emphasized the use of weight-based basal insulin when not already in place. The present analysis compares annual metrics for the overall health system before (CY 2019) and after (CY 2023) implementation of the program. Target glucose was established as 140-180 mg/dl and hypoglycemia was defined as &lt; 70 mg/dl. Glucose values after achieving initial target were then analyzed for consistency and significance before and after implementation. Results are shown as mean ± SD.* p&lt;0.001.
Conclusion: Implementation of a comprehensive educational and informatics approach to glycemic control which emphasizes the primacy of basal insulin resulted in an increase in orderset use and a concomitant 18% decrease in hypoglycemia

Disclosure
J.N. Clore: None. K. Caluag: None.
1941-LB: Effect of the Community-Based Multicomponent Strategy for Diabetes Self-Care
Authors: SONG YOUNGSHIN , SHIN HYUNKYUNG 
Published: June 2024

Introduction & Objective: Although there are many studies to confirm the effectiveness of single interventions for diabetes self-care, but patients’ real world experiences are complex, including education, counseling, and access to mHealth. The purpose of this study is to identify the effect of multicomponent self-care strategy among various interventions applied to patients with diabetes in community.
Methods: A matched sample study design was conducted. Participants were recruited at the Diabetes Registration and Education Center of Public Health Center in S-City of Korea. Three different A, B, C interventions (A: non-face to face health literacy education & tailored counseling, B: mHealth & motivational telephone counseling, C: conventional group education & telephone checkup) were applied to groups of 109 patients with diabetes in community for 3 months each. Diabetes self-care behaviors, knowledge, and self-efficacy were measured as outcome variables. Descriptive statistics, χ2-test, and F-test were used to analyze the differences between groups.
Results: Homogeneity for demographics was confirmed among groups. The difference in diabetes self-care scores before and after intervention was significantly highest in group A, followed by groups B and C. In terms of knowledge, group A had the largest difference in scores before and after intervention, but not significant. In diabetes self-efficacy, the difference in scores before and after the intervention was larger in group B than in group A.
Conclusion: Non-face to face health literacy education & counseling were most effective in community setting. Based on this, it is necessary to develop strategies that can be used in reality.

Disclosure
Y. Song: None. H. Shin: None.
1948-LB: Effect of N-Acetyl Cysteine on Thrombo-inflammation in Children with Metabolic Dysfunction–Associated Steatotic Liver Disease
Authors: GURNURKAR SHILPA , MCGOOGAN KATHERINE , SHAH CHETAN C. , UPPAL VIKAS , JOBAYER HOSSAIN MD , BALAGOPAL BABU 
Published: June 2024

Background: Obesity (OB)-related pro-thrombo-inflammatory state sets the basis for cardiometabolic disease including type 2 diabetes (T2D) and metabolic dysfunction-associated steatotic liver disease (MASLD) in children. The aims were to explore in children with OB and MASLD (i) the role of gamma prime (γ′) fibrinogen (GPF), a novel marker of thrombo-inflammation, and selected metabolic parameters and (ii) the effect of N-acetyl cysteine (NAC) on GPF and metabolic parameters.
Methods: 16-week randomized, double-blind, placebo-controlled trial of oral NAC treatment. Participants (n=13) with OB (BMI-percentile&gt;95) and MASLD (NAS Score &gt;2) were randomized to one of the two groups of NAC (600mg NAC/day or 1200mg NAC/day) and placebo. GPF, leptin, spexin, glucose, insulin and body composition were measured. Data on high-sensitivity c-reactive protein (hs-CRP), interleukin-6 (IL-6), liver enzymes, liver fat fraction (LFF) and liver stiffness (LS) were previously reported. Because of the small sample size and that the response to both doses of NAC was similar, merged data of the two intervention groups were used for statistical analysis, which included 2-sample t-test and analysis of covariance (ANCOVA).
Results: GPF was elevated (p=0.01) in those with MASLD vs normal weight (NW) and OB [GPF data from age and sex matched children with NW and OB from our previous study]. Leptin was higher and spexin lower in MASLD. GPF and leptin decreased (p=0.01 and 0.03) and spexin increased (p=0.02) in response to NAC treatment. Substantial decrease in liver enzymes, LFF, and LS were previously reported.
Conclusion: 16-week NAC treatment led to improvements in the pro-thrombo-inflammatory state present in children with OB and MASLD along with beneficial liver outcomes. Further investigation on the role of thrombo-inflammation in children with MASLD, particularly in those with T2D is warranted because of the higher incidence and severity of MASLD in those with T2D.

Disclosure
K. McGoogan: Research Support; AbbVie Inc., Pfizer Inc. Advisory Panel; Mirum Pharmaceuticals. Research Support; Retrophin. V. Uppal: None. M. Hossain: None. B. Balagopal: None.

Funding
American Diabetes Association (1-14-CE-04)
1950-LB: Real-World Use of Tirzepatide among People without Type 2 Diabetes—Results from Optum’s Deidentified Clinformatics Data Mart Database
Authors: HUNTER GIBBLE THERESA , CHINTHAMMIT CHANADDA , MEEKS ALEXANDRA , LIAO BIRONG , WARD JENNIFER , HANKOSKY EMILY R. 
Published: June 2024

Objective: Tirzepatide is a once-weekly glucose-dependent insulinotropic polypeptide and glucagonlike peptide-1 (GLP-1) receptor agonist (RA) approved for treatment of adults with type 2 diabetes (T2D) and obesity. This study aimed to understand the real-world use of tirzepatide among people without T2D.
Methods: This retrospective, claims-based study was conducted using Optum’s de-identified Clinformatics® Data Mart Database. The index date was the first observed claim of tirzepatide (NDC for Mounjaro™) during the index period (May 13, 2022-March 31, 2023). Adults without a T2D diagnosis during the 12-month (mo) pre index period and with continuous medical and pharmacy enrollment (12 mo pre index and 6 mo post index) were included. Tirzepatide was only approved for the treatment of T2D during the index period, therefore any use of tirzepatide by individuals without T2D during this time was off-label and solely at the discretion of their prescribing physician. Baseline demographic and clinical characteristics and post-index treatment patterns were assessed using descriptive analyses.
Results: 1,756 people without T2D diagnosis codes initiated tirzepatide. Mean age was 53.4 yrs, and 68.6% were female. Top prescribing providers were primary care physicians (77.5%). Dyslipidemia (46.6%), hypertension (46.1%), and prediabetes (31.2%) were the most common comorbidities, and 74.0% had ≥1 obesity-related comorbidity (ORC). During the 12-mo pre-index period, 1.4% had ≥1 claim for an anti-obesity medication (AOM). Additionally, 21.3% had ≥1 claim for metformin, while 14.5% had ≥1 claim for a non-AOM GLP-1 RA. Of 1,756 people initiating tirzepatide, 77.9% were persistent (treatment discontinuation was considered as &gt;60 untreated days on tirzepatide for ≥6 mo).
Conclusion: Most people initiating tirzepatide without T2D diagnosis codes had ≥1 ORC, were naïve to AOMs and non-AOM GLP-1 RAs and were persistent on tirzepatide at 6 mo post index.

Disclosure
T. Gibble: Employee; Eli Lilly and Company. Stock/Shareholder; Eli Lilly and Company. C. Chinthammit: Employee; Eli Lilly and Company. Stock/Shareholder; Eli Lilly and Company. A. Meeks: Employee; Eli Lilly and Company. B. Liao: Employee; Eli Lilly and Company. J. Ward: Employee; Eli Lilly and Company. E.R. Hankosky: Employee; Eli Lilly and Company. Stock/Shareholder; Eli Lilly and Company.
1953-LB: Assessing Continuous Glucose Monitor Accuracy for Diabetes Management in Hospitalized Children
Authors: GARG NEHA , LEWIS KAMRYN R. , WHITE PERRIN C. , ADHIKARI SOUMYA 
Published: June 2024

Introduction & Objectives: The adoption of continuous glucose monitors (CGM) in inpatient settings in the pediatric population has remained slow due to a scarcity of data on their reliability in hospitalized children.
Methods: We retrospectively reviewed the accuracy of the Dexcom G6 CGM system in pediatric patients with diabetes admitted to our academic children’s hospital from March 2018-September 2023. We cross referenced our institutional Dexcom Clarity database against an internal database of inpatient admissions to identify all children admitted to the hospital with CGM data. We then recorded sensor glucose readings from Clarity and values for blood glucose (BG), blood urea nitrogen, and pH from the electronic medical record.
Results: There were 3,200 admissions of children with diabetes in this period, of which 295 (from 211 patients 2-18 years old) had associated CGM data. A total of 3,952 paired CGM and BG measurements (serum and point-of-care, POC) (40-400 mg/dl) were compared resulting in a mean absolute relative difference (MARD) of 15.6%, with 96.5% of the values in zones A+B of Clarke error grid analysis. The MARD for POC BG vs CGM (n=3,518 pairs) was 15.5%, and for serum BG vs CGM (n=434 pairs), 17%. MARD varied by degree of hyperglycemia (Glucose 70-180 mg/dL: n=1866 pairs, MARD 16.4%; Glucose 181-250: n=1023, MARD 13.2%; Glucose 251-400: n=831, MARD 12.7%, p &lt;0.0001), but not by degree of acidosis (pH 7.3-7.5: n=611, MARD 15.8%, pH 7.1-7.3: n=330, MARD 16.1%, pH &lt;7.1: n=12, MARD 14.8%). We performed linear regression, and pH, sodium, and BUN had no impact on CGM accuracy.
Conclusion: Based on our retrospective data, CGMs demonstrated high clinical reliability in hospitalized children with diabetes.

Disclosure
N. Garg: None. P.C. White: Consultant; Provention Bio, Inc. Research Support; MannKind Corporation, National Institute of Diabetes and Digestive and Kidney Diseases. S. Adhikari: None.
196-OR: A Scalable Application of Artificial Intelligence (AI) to Transform Type 2 Diabetes Management in Clinical Practice
Authors: WARREN MARK L. , BERGENSTAL RICHARD M. , HAGER MATTHEW , BASHAN ERAN , HODISH ISRAEL 
Published: June 2024

Introduction: Despite new pharmacotherapy, most patients with long-term type 2 diabetes are still hyperglycemic. This could have been solved by insulin with its unlimited potential efficacy, but its dynamic physiology demands frequent titrations which are overdemanding. This report provides a real-life account for a scalable transformation of diabetes care in a community-based endocrinology center by harnessing AI-based autonomous insulin titration.
Methods: The center embedded the d-Nav® technology and its dedicated clinical support. Reported outcomes include treatment efficacy/safety in the first 600 patients and use of cardiorenal-risk reduction pharmacotherapy.
Results: Patients used d-Nav for 8.2±3.0 months with 82% retention. Age-67.1±11.5 years and duration of diabetes-19.8±11.0 years. See Figure for HbA1c dynamics during the 3-years prior d-Nav, and on d-Nav. In 21% of the patients, insulin doses initially decreased to prevent hypoglycemia. GLP1/GLP1+GIPag were prescribed in about a half of the patients and SGLT2i in a third. The frequency of hypoglycemia (&lt;54mg/dl) was 0.4±0.6/month and severe hypoglycemia 1.7/100-patient-years.
Conclusions: The use of d-Nav allowed for scalable improvement in overall diabetes management with appropriate use of both insulin and non-insulin pharmacologic agents.

Disclosure
M.L. Warren: Research Support; Novo Nordisk, Insulet Corporation. Speaker's Bureau; Lilly Diabetes. Advisory Panel; Lilly Diabetes. Research Support; AstraZeneca, Bayer Inc. Speaker's Bureau; Bayer Inc. Research Support; AbbVie Inc., Medtronic, Ascendis Pharma A/S, Amolyt. Speaker's Bureau; Ascendis Pharma A/S, Amgen Inc. Research Support; AstraZeneca. Advisory Panel; Hygieia. R.M. Bergenstal: Other Relationship; Abbott. Research Support; Arkray Marketing. Consultant; Ascensia Diabetes Care, Bigfoot Biomedical, Inc., CeQur. Other Relationship; Dexcom, Inc., Eli Lilly and Company. Consultant; embecta, Hygieia. Research Support; Insulet Corporation. Consultant; MannKind Corporation. Other Relationship; Medtronic, Novo Nordisk. Consultant; Onduo LLC, Roche Diabetes Care. Other Relationship; Sanofi. Research Support; Tandem Diabetes Care, Inc. Other Relationship; UnitedHealth Group. Consultant; Vertex Pharmaceuticals Incorporated, Zealand Pharma A/S. M. Hager: Other Relationship; Hygieia. E. Bashan: Board Member; Hygieia. Employee; Hygieia. Stock/Shareholder; Hygieia. I. Hodish: Stock/Shareholder; Hygieia.
1963-LB: Prenatal Treatment of Glucagon-Like Peptide 1 Agonist Mitigates Cognitive Deficits in Offspring of Mothers with Diabetes by Modulating Placental Development Mediated by ADGRL3
Authors: ITO MARIKO , SUGAI KEIJI , SASAKI JUNKO , SUZUKI RYO , ODAWARA MASATO , TORII MASAAKI , HASHIMOTO-TORII KAZUE 
Published: June 2024

Hyperglycemia during pregnancy is associated with increased neurobehavioral risks in offspring, even with insulin control. We hypothesized that prenatal administration of Glucagon-like peptide 1 (GLP-1) agonist to diabetic mothers could alleviate cognitive deficits in offspring. A pregestational diabetes model was made with 8-week-old C57BL/6J female mice using streptozotocin (STZ). Offspring were used for behavior test and the tissues underwent immunohistochemistry, single-cell RNA sequencing, and qRT-PCR analyses. In vitro studies utilized HTR8/SVneo cells for mass spectrometry and cAMP assays by shRNA mediated knocking down, and HEK293 cells for the SRE assay by ADGRL3 overexpression. Offspring of the dam with diabetes showed learning deficits and prenatal treatment of GLP-1 agonist starting mid-gestation mitigated the deficits. Immunohistochemical analysis found GLP-1 agonist in placental trophoblasts, without distribution in fetal brain. In placenta from STZ model, trophoblast invasion was inhibited, but improved by GLP-1 agonist treatment. qRT-PCR of human placental tissue mirrored mouse findings; genes related to trophoblast inveation were altered in placenta from mother with pregestational diabetes. In HTR8/SVneo cells that lacks GLP-1 receptor, another class B GPCRs, ADGRL3, was determined as a GLP-1 binding receptor in immunoprecipitation-mass spec analysis. Functional assays showed that ADGRL3 mediates GLP-1 signaling via G alpha s and G alpha q proteins. Altogether, our study demonstrates that prenatal GLP-1 RA treatment mitigates cognitive deficits of offspring from STZ-exposed dams by affecting ADGRL3 mediated GLP-1 signaling in placental trophoblasts.

Disclosure
M. Ito: None. K. Sugai: None. J. Sasaki: None. R. Suzuki: Speaker's Bureau; Novo Nordisk Pharma, Sanofi, Sumitomo Dainippon Pharma Co., Ltd., Astellas Pharma Inc., Kowa Company, Ltd., MSD, Eli Lilly and Company, Mitsubishi Tanabe Pharma Corporation, Teijin Pharma Limited. Research Support; Sumitomo Dainippon Pharma Co., Ltd. M. Odawara: Speaker's Bureau; Sumitomo Dainippon Pharma Co., Ltd., Taisho Pharmaceutical Holdings Co., Ltd., Novartis Pharmaceuticals Corporation, Eli Lilly and Company, Astellas Pharma Inc., Ono Pharmaceutical Co., Ltd., Kyowa Kirin Co., Ltd., Daiichi Sankyo, Takeda Pharmaceutical Company Limited, Mitsubishi Tanabe Pharma Corporation, Boehringer-Ingelheim, MSD Life Science Foundation, AstraZeneca, Kowa Company, Ltd. Research Support; Sumitomo Dainippon Pharma Co., Ltd., Eli Lilly and Company. Other Relationship; Astellas Pharma Inc., Ono Pharmaceutical Co., Ltd., Kyowa Kirin Co., Ltd., Daiichi Sankyo, Takeda Pharmaceutical Company Limited, Mitsubishi Tanabe Pharma Corporation, Boehringer-Ingelheim. M. Torii: None. K. Hashimoto-Torii: None.

Funding
National Institutes of Health (A12BC345678)