bluuebunny/crossref_metadata_2025_split huggingface dataset:
1321-P: A Machine-Learning Approach on Metabolomic Data to Predict Type 2 Diabetes Mellitus Incidence
Authors: LEIHERER ANDREAS , MUENDLEIN AXEL , SAELY CHRISTOPH H. , PLATTNER THOMAS , LARCHER BARBARA , MADER ARTHUR , VONBANK ALEXANDER , LAAKSONEN REIJO , FRAUNBERGER PETER , DREXEL HEINZ 
Published: June 2024

Metabolomics, with its wealth of data, offers a valuable avenue for enhancing predictions and decision-making in diabetes. This observational study, aimed to leverage machine learning (ML) algorithms to predict the 4-year risk of developing T2DM using targeted quantitative metabolomic data. A cohort of 279 cardiovascular risk patients, who underwent coronary angiography and who were initially free of T2DM according to ADA criteria, were followed for up to 4 years. During this time, 11.5% newly developed T2DM. Targeted metabolomics (Biocrates, AUSTRIA) was performed at baseline, using liquid chromatography (LC), - mass spectroscopy (MS), and flow injection analysis (FIA) - MS respectively. After preprocessing the metabolomics data set, 362 variables were used for ML, employing the caret package (CRAN, R). The dataset was divided into training and test sets (75:25 ratio), and we used an oversampling approach to address the classifier (T2DM incidence) imbalance. The Multilayer Perceptron (MLP) after size-tuning demonstrated the most promising predictive capabilities, exhibiting a sensitivity of 63%, a specificity of 79%, and an accuracy of 77%. The most important variables (top20, figure) were ceramides, bile acids, and hexoses.
In conclusion, ML analysis of large metabolomic data is a promising tool for identifying individuals at risk of developing T2DM and opens avenues for personalized and early intervention strategies.

Disclosure
A. Leiherer: None. A. Muendlein: None. C.H. Saely: None. T. Plattner: None. B. Larcher: None. A. Mader: None. A. Vonbank: None. R. Laaksonen: None. P. Fraunberger: None. H. Drexel: None.
1340-P: The Association of SGLT2i vs. DPP4i on Fracture—Cohort Study of Veterans with Diabetes
Authors: SNYDER KATHRYN D. , HACKSTADT AMBER J. , GRIFFIN KATHERINE E. , HORTON THOMAS G. , HOSSEIN JAVID AMIR , HUNG ADRIANA M. , GREEVY ROBERT A. , ROUMIE CHRISTIANNE 
Published: June 2024

Objective: Increased bone turnover is associated with SGLT2i use. Patients with diabetes have adverse effects on bone metabolism. Our aim was to evaluate if SGLT2i was associated with fractures versus DPP4i.
Methods: A retrospective cohort combined Veterans Administration, Medicare, and National Death Index databases. New users of SGLT2i with diabetes (87% empagliflozin; 10.2% canagliflozin; 2.6% dapagliflozin) or DPP4i (51% saxagliptin; 30% sitagliptin; 12% alogliptin) were followed from the prescription fill until a fracture event, death or study end. Fractures included: face/skull, spine, ribs, long bones, hand/feet/ digits, or hip. Fractures were identified based on a validated algorithm with PPV 91.3% (86.8, 94.4) compared to medical records. Cox models compared fractures between SGLT2i and DPP4i in a propensity score weighted cohort adjusted for clinical and lab data including vitamin D levels, smoking, and medications.
Results: The weighted cohort included 36253 SGLT2i vs 36189 DPP4i episodes. Median age was 69 years and diabetes duration 9.3 (5.7, 13.7) years. In matched weighted analyses, there were 468 and 549 fractures among SGLT2i and DPP4i users, respectively. There were no clinical differences in fractures per 1000 person years: 18.1 (16.6, 19.7) vs. 20.2 (19.1, 21.4) [aHR 0.89 (0.80, 0.99)].
Conclusions: SGLT2i use for diabetes was not associated with increased fracture outcomes compared to DPP4i

Disclosure
K.D. Snyder: None. A.J. Hackstadt: None. K.E. Griffin: None. T.G. Horton: None. A. Javid: None. A.M. Hung: None. R.A. Greevy: None. C. Roumie: None.

Funding
VA Clinical Science research and Development investigator initiated grant CX000570-11 (Roumie)
1343-P: Association of SGLT2i on Amputation, Stent Placement, or Revascularization vs. DPP4—Cohort Study in Veterans
Authors: GRIFFIN KATHERINE E. , SNYDER KATHRYN D. , HOSSEIN JAVID AMIR , HACKSTADT AMBER J. , GREEVY ROBERT A. , GRIJALVA CARLOS G. , ROUMIE CHRISTIANNE 
Published: June 2024

Objective: The association between SGLT2i and peripheral artery disease (PAD) remains unclear for high-risk patients. The aim of this study was to test the hypothesis that SGLT2i is associated with a composite PAD outcome compared to DPP4i.
Methods: A retrospective cohort combined Veterans Administration, Medicare, and National Death Index databases. New users of SGLT2i or DPP4i were followed from the prescription fill until a composite PAD event, death, or end study. The PAD event was defined as the earliest surgery: amputation, peripheral stent placement, or revascularization. Covariate adjusted Cox models compared PAD event between SGLT2i users and DPP4i users in a propensity score weighted cohort allowing for events to occur up to 90 days or 360 days after stopping SGLT2i.
Results: The weighted cohort included 36,190 SGLT2i vs 36,254 DPP4i episodes. Median age was 69 years, HbA1c was 8.40 [7.60, 9.30] and diabetes duration 9.3 (5.7, 13.7) years. There were 319 and 286 PAD events among SGLT2i and DPP4i users, respectively, for an event rate of 12.3 (11.0, 13.6) and 10.4 (9.6, 11.4) per 1000 person-years (aHR 1.21 [1.05, 1.41]). When allowing for PAD events for 360 days after SGLT2i use ended, the aHR was 1.27 [1.13, 1.44]).
Conclusions: Use of SGLT2i for diabetes treatment was associated with increased amputation and revascularization surgery outcomes compared to DPP4i.

Disclosure
K.E. Griffin: None. K.D. Snyder: None. A. Javid: None. A.J. Hackstadt: None. R.A. Greevy: None. C.G. Grijalva: Advisory Panel; Merck Sharp & Dohme Corp. C. Roumie: None.

Funding
VA Clinical Science research and Development investigator initiated grant CX000570-12 (Roumie)
1346-P: Association between Chronic Constipation and All-Cause Mortality among Adult Women With and Without Type 2 Diabetes
Authors: VISARIA AAYUSH , SHAH NISHALI 
Published: June 2024

Introduction: Chronic constipation (CC) is common among women with type 2 diabetes (T2D), likely due to microvascular, neuropathic, and microbiome changes. It is unknown whether CC confers additional mortality risk. We determined the association between CC and risk of all-cause mortality in U.S. adult women with & without T2D.
Methods: We included non-pregnant women ≥20 years from the National Health and Nutrition Examination Survey 2005-2010 linked to the National Death Index through 2019. We excluded women taking insulin, with inflammatory bowel disease, prior bowel surgeries, or chronic diarrhea. T2D was defined as HbA1c ≥6.5%, fasting blood glucose ≥126 mg/dl, or self-reported diagnosis. CC was defined as bowel frequency &lt;4 BMs/week and bowel consistency using Bristol Stool Form Scale (BSFS) Type 1-2. The reference was women with &gt;3 BMs/week & BSFS Type 3-5. We used survey design-adjusted Cox regression with covariates determined a priori (demographics, smoking, exercise, diet, waist size, BP, HbA1c, T2D medication use, laxative use).
Results: Among 5,620 women (mean age 47y, 72% non-Hispanic White [NHW], 8.3% T2D), 154 (2.6%) had CC. Across a mean 11.4y (SD, 2.7y) of follow-up, 678 (10%) died. Women with CC were more likely to have lower income & education, poor self-reported health, and other T2D complications. Among women with T2D, CC had 2 times the risk of mortality (HR [95% CI]; unadjusted: 3.27 [1.62, 6.58], adjusted: 2.06 [1.11, 3.85]). Income & education most significantly attenuated risk estimates (34% change). There was no association between CC and mortality in women without T2D (unadjusted: 0.94 [0.51, 1.71], adjusted: 1.04 [0.62, 1.74]).
Conclusion: CC was present in nearly 3% of women. Only in women with T2D was CC associated with more than twice the risk of mortality, suggesting CC may be a symptom of T2D complication. Further longitudinal studies are needed to examine temporality of CC onset with other complications.

Disclosure
A. Visaria: None. N. Shah: None.
1378-P: The Association between Baseline Hemoglobin A1c (A1C) and Risk of Progression from Prediabetes to Diabetes across Adult Age Groups
Authors: FAZLI GHAZAL S. , LIPSCOMBE LORRAINE , THIRUCHELVAM DEVA , KENASZCHUK CHRIS , SHAH BAIJU R. , KE CALVIN , ALI FATEMA M. , ROSELLA LAURA , BOOTH GILLIAN L. 
Published: June 2024

Introduction & Objectives: While A1c is a strong predictor of conversion from prediabetes to type 2 diabetes, it is unclear whether A1c values within the prediabetes range confer the same risk of conversion to type 2 diabetes within different adult age groups.
Methods: Using linked population-based administrative health databases, we investigated the progression from prediabetes to diabetes among adults (≥20 years) with laboratory criteria for prediabetes living in Ontario, Canada between 2012-2022. New diabetes cases were captured using a well-validated administrative data algorithm. Competing risk and Cox proportional hazards models were used to assess the association between A1c increments (~0.2%) within the prediabetes range (5.70-6.49%, vs &lt;5.7%) and diabetes incidence in different decades.
Results: Among 3,022,169 individuals with prediabetes, 139,450 (4.6%; mean age 54.1 ± 15.8 yrs) progressed to diabetes over a mean follow up of 4.78 years. The cumulative incidence of diabetes was greatest among those with baseline A1C levels of 6.30-6.49% in both younger (20-29 yrs: 34.5%) and older adults (≥70 yrs: 19.2%). Increased A1c conferred a far greater relative risk of progression to diabetes in adults aged 20-29 and 30-39 (A1c 6.30-6.49%: HR 51.7, 95% CI 45.0-59.3 and HR 41.3, 38.8-44.0, respectively). Relative conversion rates were more modest in adults aged ≥70 years across all A1c categories (A1c 6.30-6.49%: HR 9.7, 9.3-10.1).
Conclusion: Baseline A1c was a stronger predictor of conversion from prediabetes to diabetes among younger adults, suggesting that diabetes prevention efforts should consider baseline A1C and age to reduce future risk of progression.

Disclosure
G.S. Fazli: None. L. Lipscombe: Other Relationship; Novo Nordisk Canada Inc. D. Thiruchelvam: None. C. Kenaszchuk: None. B.R. Shah: None. C. Ke: Advisory Panel; Sanofi. Speaker's Bureau; AstraZeneca. F.M. Ali: None. L. Rosella: None. G.L. Booth: None.
1400-P: Hepatic Effectiveness of SGLT2 Inhibitors in Patients with Nonalcoholic Fatty Liver Disease and Type 2 Diabetes
Authors: BEA SUNGHO , YEON KO HWA , SHIN JU-YOUNG 
Published: June 2024

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) have demonstrated promising effects on liver outcomes. However, comprehensive evidence regarding liver outcomes in direct comparison with thiazolidinediones (TZD) and glucagon-like peptide-1 receptor agonists (GLP1RA), which are recommended in guidelines for patients with non-alcoholic fatty liver disease (NAFLD) and type 2 diabetes (T2D), is still lacking. Using health insurance claims data from South Korea, we established two pairwise 1:1 propensity score (PS)-matched cohorts who initiated SGLT2i, GLP1 RA (cohort #1, median age=57 years, 60% male), or TZD (cohort #2, median age=57 years, 72% male) between January 2014 and December 2022. The primary outcome was a composite of hepatic decompensation events, including ascites, esophageal varices with bleeding, hepatic failure, or liver transplant. Hazard ratios (HR) with 95% confidence intervals (CI) were calculated. In cohort #1, compared to GLP1RA, SGLT2i showed a similar risk of hepatic decompensation events (HR 0.92, 95% CI 0.76-1.12). In cohort #2, compared to TZD, SGLT2i demonstrated a reduced risk of hepatic decompensation events (HR 0.77, 95% CI 0.72-0.82). In this nationwide cohort study, SGLT2i was associated with a reduced risk of hepatic decompensation events in patients with NAFLD and T2D compared to TZDs, showing similar effectiveness to GLP1RA.

Disclosure
S. Bea: None. H. Ko: None. J. Shin: Research Support; Pfizer Inc., Celltrion, SK Bioscience, GlaxoSmithKline plc.

Funding
This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: RS-2023-00273553)
1406-P: Accessibility of Diabetes Prevention Programs in Historically Redlined Areas of the U.S.
Authors: ROY DARIUS J. , CHANTARAT TONGTAN , JIANG DAVID H. , GOLDEN SHERITA , DAVIS ESA , DING MARISSA L. , HUANG SHUO J. , MCCOY ROZALINA G. 
Published: June 2024

Introduction & Objective: Prior research demonstrated an association between historical redlining practices and diabetes-related mortality. The National DPP is an evidence-based, cost-effective, structured lifestyle change intervention to prevent type 2 diabetes (T2D). Whether historical redlining practices drive the present-day availability of DPP programs across the US is unknown.
Methods: In person and hybrid DPPs across the US and their addresses were identified from the CDC. Walking distance accessibility was defined as a 0.8 km radius. Redlining was assessed using the 1930s federal Home Owners’ Loan Corporation (HOLC) maps by intersect spatial join onto 2020 census tracts. HOLC areas are classified into 4 grades: A (best), B (still desirable), C (declining), and D (hazardous). We examined the association between grade D vs. A-C tracts and the number of DPPs using a negative binomial mixed-effects model with random intercepts by geographic level and controlling for tract-level population, proportion uninsured people, and &lt;150% of federal poverty line (FPL).
Results: Of 1730 DPPs, 347 were within walking access of a HOLC-graded tract centroid in 38 states. Nationally, after controlling for tract-level characteristics, grade D tracts and tracts with greater proportion &lt;150% of FPL were associated with greater number of DPPs, while tracts with greater proportion of uninsured were associated with fewer DPPs within walking distance. In state-specific analyses for 7 of 33 examined states, there was statistically significant greater than expected DPP availability in grade D tracts. There was no difference in 20 states, while remaining 11 states could not be examined due to lack of HOLC data, model diagnostics, data sparsity, or convergence failure.
Conclusion: While availability of walking distance DPPs is higher in historically redlined areas in 7 states, there was no such enrichment in 20 states. Future research needs to examine DPP utilization by residents in these communities.

Disclosure
D.J. Roy: None. T. Chantarat: None. D.H. Jiang: None. S. Golden: None. E. Davis: None. M.L. Ding: None. S.J. Huang: None. R.G. McCoy: Research Support; American Diabetes Association. Other Relationship; American Diabetes Association. Consultant; Wolters Kluwer Health. Research Support; National Institutes of Health, Patient-Centered Outcomes Research Institute. Consultant; Yale New Haven Health System.

Funding
National Institute of Diabetes and Digestive and Kidney Diseases (K23DK114497)
1418-P: Prevalence of Self-Reported Diagnosed Diabetes among U.S. Adults According to Metropolitan Residence and Region, United States 2019–2022
Authors: ONUFRAK STEPHEN J. , KOYAMA ALAIN , MIYAMOTO YOSHIHISA , SAELEE RYAN , XU FANG , BULLARD KAI M. , IMPERATORE GIUSEPPINA , PAVKOV MEDA E. 
Published: June 2024

Background: Previous research suggests that rural/urban disparities in diabetes mortality, hospitalization, and incidence rates may manifest differently across US regions. However, no studies have examined disparities in diabetes prevalence by metropolitan residence and region.
Methods: Using data from the 2019-2022 National Health Interview Survey (NHIS), diabetes status, socioeconomic characteristics, and weight status were compared among adults within each Census region (Northeast, Midwest, South, West) according to county metropolitan status of residence (large central metro, large fringe metro, small/medium metro, and non-metro) using Chi-squared tests. Logistic regression models were fit to assess the association of metropolitan residence and diabetes prevalence within each region.
Results: Diabetes prevalence ranged from 7.0% in large fringe metro counties in the Northeast to 14.8% in non-metro counties in the South. Compared to adults from large central metro counties, those from small/medium metro counties had significantly higher odds of diabetes in the Midwest (age, sex, and race/ethnicity adjusted odds ratio [OR]=1.24; 95% confidence interval [CI]: 1.06-1.45) and South (OR=1.15; 95% CI: 1.02-1.30). Non-metro residence was also associated with diabetes in the South (OR=1.62 vs large central metro; 95% CI: 1.43-1.84). After further adjustment for socioeconomic and body weight status, small/medium metro associations with diabetes became attenuated and nonsignificant but non-metro residence in the South remained significantly associated with diabetes (OR=1.22; 95% CI: 1.07-1.39).
Conclusion: The association between metropolitan residence and diabetes prevalence differs across regions of the United States. These findings can help to guide efforts in areas where diabetes prevention and care resources may be better directed.

Disclosure
S.J. Onufrak: None. A. Koyama: None. Y. Miyamoto: None. R. Saelee: None. F. Xu: None. K.M. Bullard: None. G. Imperatore: None. M.E. Pavkov: None.
1422-P: Understanding COVID-19 Impacts among Underserved Adults with Diabetes Using the Social-Ecological Model
Authors: MAIZEL JENNIFER , ATTANTI RITHWIK , PRASANNA CHENNURI KEERTHI , SMITH RILEY , FILIPP STEPHANIE L. , HECHAVARRIA MELANIE , HALLER MICHAEL J. , WESTEN SARAH , DIXON BRITTNEY , MAAHS DAVID M. , LAL RAYHAN , ADDALA ANANTA , WALKER ASHBY F. 
Published: June 2024

Introduction & Objective: People with diabetes reported disparate health, psychosocial, and financial outcomes from COVID-19. This study aimed to understand experiences of underserved adults with diabetes during the COVID-19 pandemic.
Methods: A survey assessing COVID-19 impacts was administered to adults with insulin-requiring diabetes (n=450) at federally qualified health centers in CA and FL between Nov. 2021-Jul. 2022. This qualitative study analyzed responses to an open-ended question asking patients to describe the pandemic’s impact on their lives (n=263, mean age=53.5 ± 14.3 years, 60.5% T2D). Responses were coded via a thematic analysis guided by CDC’s Social-Ecological Model (SEM), which asserts that health occurs at and is affected by 4 levels: Individual, Relationship, Community, and Societal. Descriptive statistics (n, %) determined the frequency of impacts reported; some patients noted multiple impacts.
Results: A total of 546 codes were identified; 490 reported COVID-19 impacts (89.7%); 56 noted no impact (10.3%). Among reported impacts, most were Individual-level (n=208, 42.5%), e.g., diagnoses of COVID-19 or other illnesses, mental health issues, higher blood glucose, and weight gain. Societal impacts (n=158, 32.2%) included concerns regarding COVID-19 information, income loss, and challenges scheduling medical appointments, ordering diabetes supplies, and accessing healthy foods. Relationship impacts (n=65, 13.3%) included social isolation and reduced family/peer interactions. Community impacts (n=44, 9.0%) included occupational changes, extra precautions in high-risk areas, and challenges with local transportation and housing. The remainder were unspecific (n=15, 3.1%).
Conclusion: COVID-19 impacts among underserved adults with diabetes stem from factors across the SEM. Multi-level interventions are needed to improve patients’ healthcare, promote social support, enhance local preventive efforts, and reduce inequities.

Disclosure
J. Maizel: None. R. Attanti: None. K. Chennuri: None. R. Smith: None. S.L. Filipp: None. M. Hechavarria: None. M.J. Haller: Consultant; Sanofi. Advisory Panel; SAB Biotherapeutics, Inc. Consultant; MannKind Corporation. S. Westen: None. B. Dixon: None. D.M. Maahs: Advisory Panel; Medtronic. Consultant; Abbott, LifeScan Diabetes Institute, Sanofi, Provention Bio, Inc., Bayer Inc., Kriya Therapeutics, BioSpex. R. Lal: Consultant; Abbott, Adaptyx Biosciences, Biolinq, Capillary Biomedical, Inc., Deep Valley Labs, Gluroo, PhysioLogic Devices, Portal Insulin, Tidepool. Advisory Panel; Lilly Diabetes. A. Addala: None. A.F. Walker: None.

Funding
The Leona M. and Harry B. Helmsley Charitable Trust (G-2005-03934)
1447-P: Metabolic Heterogeneity of Antibody-Positive Individuals (Ab+I) with Impaired Glucose Tolerance (IGT) according to Glucose Fractions
Authors: NATHAN BRANDON M. , CUTHBERTSON DAVID D. , ISMAIL HEBA M. , JACOBSEN LAURA M. , SIMS EMILY K. , SOSENKO JAY 
Published: June 2024

Introduction and Objective: Among Ab+I, we examined the metabolic heterogeneity of IGT, a marker of progression toward stage 3 type 1 diabetes (T1D), using glucose fractions dependent or independent of insulin secretion.
Methods: Data from Ab+I with baseline OGTTs meeting IGT criteria (2-hr glucose ≥140 to &lt;200 mg/dl, n=1103) enrolled in TrialNet Pathway to Prevention were analyzed. AUC glucose was divided into fractions dependent (dAUCGLU) or independent (iAUCGLU) of insulin secretion, defined by the linear regression of AUC glucose vs. Index60 (as an insulin secretion proxy). dAUCGLU was the AUC glucose value predicted by Index60, while iAUCGLU was the AUC glucose residual value above or below the regression slope.
Results: AUC C-peptide decreased as dAUCGLU quartiles increased, whereas AUC C-peptide increased as iAUCGLU quartiles increased (Figure). AUC C-peptide was inversely correlated with dAUCGLU (r=-0.84) and positively correlated with iAUCGLU (r=0.62) (p&lt;0.0001 for both). AUC C-peptide trended little with unfractionated AUC glucose quartiles.
Conclusion: Opposite associations of AUC C-peptide with dAUCGLU and iAUCGLU indicate that AUC C-peptide was not only attributable to insulin secretion, but also to other factors (e.g. insulin resistance). It appears that among Ab+I, IGT is a heterogeneous metabolic state that may not be an optimal marker for T1D.

Disclosure
B.M. Nathan: None. D.D. Cuthbertson: None. H.M. Ismail: Consultant; Sanofi, Rise Therapeutics. L.M. Jacobsen: Advisory Panel; Insulet Corporation. E.K. Sims: Consultant; Sanofi. Board Member; American Diabetes Association. Other Relationship; American Diabetes Association, Medscape. Consultant; DRI. J. Sosenko: None.

Funding
National Institutes of Health (U01 DK061010, U01 DK061034, U01 DK061042, U01 DK061058, U01 DK085461, U01 DK085465, U01 DK085466, U01 DK085476, U01 DK085499, U01 DK085509, U01 DK103180, U01 DK103153, U01 DK103266, U01 DK103282, U01 DK106984, U01 DK106994, U01 DK107013, U01 DK107014, UC4 DK106993, UC4 DK117009)JDRF