bluuebunny/crossref_metadata_2025_split huggingface dataset:
1245-P: Heart Failure Biomarkers in Diabetes—A National Reference Laboratory Study
Authors: ALFEGO DAVID , VALCOUR ANDRE , SHAJANI-YI ZAHRA , YOUNG RANDOLPH M. , SULLIVAN RENEE M. 
Published: June 2023

Background: Recent guidelines1,2 recommend yearly biomarker screening (BNP, NT-proBNP or hs-cardiac troponin) of patients with diabetes at-risk for heart failure (HF) and team-based care with a cardiovascular specialist if elevated1-3.
Methods: Using de-identified laboratory results from Labcorp® patients (2015-2022), we studied diabetes and HF ICD incidence via HbA1c and subsequent BNP/NT-proBNP (in pg/mL). Patients were classified as A1c consistent with no diabetes, prediabetes, or diabetes and newly diagnosed HF if they had no HF-associated ICD on/before date of initial HF testing and assigned one on a later date. Distribution of HF by cohort was evaluated by chi squared and likelihood by odds ratios (OR).
Results: There were 805,512 unique patients with A1c and either BNP/NT-proBNP performed. Using published cutoffs1-3, new diagnosis of HF by ICD was significantly different among cohorts for all cutoffs (p&lt;0.001) and more likely in patients with diabetes compared to those without (OR 1.48 by BNP ≥ 35, 1.45 by BNP ≥ 50, 1.37 by NT-proBNP). As BNP cutoff increased, patients meeting criteria decreased. NT-proBNP &gt; 125 had similar proportional yield of HF diagnosis to BNP ≥ 35.
Conclusion: Patients with diabetes (by A1c) were more likely to have a new diagnosis of HF on subsequent testing than patients without diabetes. The BNP cutoff utilized has meaningful implications for the number of patients referred to team-based care.

Disclosure
D.Alfego: Employee; LabCorp. A.Valcour: Employee; LabCorp. Z.Shajani-yi: Employee; LabCorp. R.M.Young: Employee; LabCorp. R.M.Sullivan: Employee; LabCorp.
1246-P: Magnitude of Intentional Weight Reduction and Associated Clinical Outcomes
Authors: KAN HONGJUN , BENGTSON LINDSAY , AHMAD NADIA , BAE JAY P. , GRONROOS NOELLE , LANDIS CHRISTINA , CHINTHAMMIT CHANADDA , OWORA ARTHUR H. , GLETSU MILLER NANA A. , DUNN JULIA P. 
Published: June 2023

Purpose: To describe the association of BMI reduction with clinical outcomes (medication utilization, HbA1c, and blood pressure) in adults undergoing medical intervention for weight reduction.
Methods: Optum’s Market Clarity database (Study Period: 2007-2020) was used to identify adults with overweight/obesity with a medical intervention for weight reduction (surgery, procedure, anti-obesity medication, or lifestyle) whose weight after a 3-year period was less than or equal to their pre-intervention weight (date of weight: index). Patients were grouped by percent BMI change (Figure 1). Outcomes included change in 6-month pre-index versus 6-month follow-up (starting after the 3-year period) for HbA1c and blood pressure in patients with measures in both periods, and change in condition-specific pharmacy utilization for patients with the condition during pre-index.
Results: There were n=127,267 patients meeting study criteria. Mean Rx utilization during follow-up decreased (relative to pre-index) as BMI reduction increased, (p&lt;0.001; Figure 1a-1c) with groups achieving ≥15% BMI reduction having lower mean utilization in follow-up versus pre-index. Greater BMI reduction was also associated with improvements in HbA1c and blood pressure (p&lt;0.001; Figure 1d-1f).
Conclusions: Higher BMI reduction groups had greater mean improvements in clinical measures while mean medication utilization decreased.

Disclosure
H.Kan: Employee; Eli Lilly and Company, Stock/Shareholder; Eli Lilly and Company. J.P.Dunn: Employee; Eli Lilly and Company, Stock/Shareholder; Eli Lilly and Company. L.Bengtson: Other Relationship; Eli Lilly and Company. N.Ahmad: Employee; Eli Lilly and Company. J.P.Bae: None. N.Gronroos: Other Relationship; Eli Lilly and Company. C.Landis: Other Relationship; Eli Lilly and Company. C.Chinthammit: Employee; Eli Lilly and Company, Stock/Shareholder; Eli Lilly and Company. A.H.Owora: None. N.A.Gletsu miller: Research Support; Lilly.
1247-P: Mildly Elevated Triglyceride Levels Are Associated with Increased Risk for Major Adverse Cardiovascular Events in Statin-Naïve Rheumatoid Arthritis Patients—A Nationwide Cohort Study
Authors: CHOI WONSUK , KANG JI-HYOUN , YONG PARK JI , RAM HONG A. , YOON JEEHEE , KIM HEEKYUNG , KANG HO-CHEOL 
Published: June 2023

Objectives: To investigate the association between the four components of the lipid profile at baseline and major adverse cardiovascular events (MACEs) in statin-naïve rheumatoid arthritis (RA) patients with no previous history of cardiovascular events compared to non-RA controls.
Methods: This nationwide population-based cohort study was performed on a total of 15,216 statin-naïve RA patients and 60,864 non-RA controls. The end point was a composite of clinical events, including myocardial infarction (MI), stroke, coronary revascularization, and cardiovascular death. We compared the incidence of and risk for clinical events according to each lipid variable.
Results: During follow-up (median 4.70 years in RA group and 5.05 years in non-RA group), the incidence of MACE per 1000 person-years was 7.27 in the RA group and 7.16 in the non-RA group. Among the four lipid components, only higher baseline triglyceride (TG) levels were significantly associated with increased risk for MACE in the RA group. The risk for MACE was significantly higher in the third (adjusted hazard ratio (HR), 1.31 [95% confidence interval (CI), 1.00-1.71]) and highest quartiles (adjusted HR, 1.71 [95%CI, 1.30-2.23]) of baseline TG level versus the lowest quartile. In contrast, higher baseline total cholesterol, TG, and low-density lipoprotein cholesterol, and lower high-density lipoprotein cholesterol levels were significantly associated with increased MACE risk in the propensity score-matched non-RA group.
Conclusions: In statin-naïve RA patients, increased TG level is associated with increased risk for MACE. Therefore, screening and intervention for increased TG level may be clinically beneficial in this population.

Disclosure
W.Choi: None. J.Kang: None. J.Park: None. A.Hong: None. J.Yoon: None. H.Kim: None. H.Kang: None.

Funding
National Research Foundation of Korea (2022R1C1C1006021)
125-OR: Disparities in Access to Sodium–Glucose Cotransporter-2 Inhibitors (SGLT2i)
Authors: ZHANG DONGLAN S. , RAJAN ANAND , ISLAM SHAHIDUL , CHARYTAN DAVID M. , JACOBSON ALAN M. , DIVERS JASMIN 
Published: June 2023

SGLT2i are shown to improve diabetes control and delay the onset of diabetes-related complications. However, socioeconomic (SES) factors may influence access to SGLT2i. We assessed trends and differences in SGLT2i prescription rates by race, ethnicity, and insurance type at a large academic medical center (AMC). Data were extracted from the electronic health records at a large AMC from January 2014 to December 2021. The study outcome was SGLT2i prescription rates over time. Race and ethnicity were classified as Non-Hispanic White (NHW), NH Black (NHB), Hispanics, and Asian/Pacific Islanders (API), and insurance type as Private, Medicare, and Medicaid. Negative binomial regressions were used to estimate the prescription rates by year. Between 2014-2021, 30,030 type 2 diabetes patients received an SGLT2i prescription, and the prescription rates increased significantly from 0.25% to 11.47%, with the rates increasing fastest in Medicare patients. Privately-insured and Medicare patients were more likely to be prescribed SGLT2i than Medicaid patients (p&lt;0.001). NHB, and Hispanic patients were less likely to be prescribed SGLT2i than NHW and API patients (p&lt;0.001). Although SGLT2i prescription rates increased after FDA approval, substantial variations by race, ethnicity, and insurance type exist. Future studies are needed to explore how SES factors drive observed differences in access to SGLT2i.

Disclosure
D.S.Zhang: None. A.Rajan: None. S.Islam: None. D.M.Charytan: Advisory Panel; Merck & Co., Inc., CSL Behring, GlaxoSmithKline plc., Consultant; Novo Nordisk, Gilead Sciences, Inc., AstraZeneca, Other Relationship; Boehringer Ingelheim and Eli Lilly Alliance, zogenix, medtronic, Research Support; Amgen Inc. A.M.Jacobson: None. J.Divers: None.

Funding
Doucette Innovation Fund
1253-P: Differences in Screening-Detected Type 2 Diabetes—Evidence from Two Campaign Setups in Denmark
Authors: CAYUELAS MATEU NURIA , THYBO TANJA 
Published: June 2023

Background: Early detection of type 2 diabetes mellitus (T2DM) increases life expectancy of T2DM patients and reduces societal health care costs. Targeted screening campaigns are used for early detection of T2DM, but different campaign setups may yield different detection results.
Methods: Between June and November 2022, the Danish Diabetes Association offered free capillary A1c tests to individuals at high risk of developing diabetes based on the Leicester’s Risk Score questionnaire (score ≥ 16 points). Two campaign setups were applied: a) an event-based community screening campaign in 20 of the largest Danish cities using a portable Point of Care Testing analyzer and b) a social media campaign offering at-home self-sampling tests using mailed Hemoglobin Capillary Collection System.
Results: A total of 1,337 and 2,655 individuals at high risk were tested through the community and the social media setup, respectively. The proportion of men and women in both setups were evenly balanced across all age groups. However, compared to the social media setup, in the community setup the proportion of individuals aged below 60 years was 14 percentage points lower, while the proportion of individuals aged 70 years or older was 14 percentage point higher. While 2.6% of the participants in both setups had A1c values ≥ 48 mmol/mol, 8.8% in the community setup and 15.6% in the social media setup had A1c values of 42-47 mmol/mol. The relative difference in the proportion of participants with A1c values of 42-47 mmol/mol was balanced across all age groups.
Conclusions: Targeted community and social media screening campaigns are complementary. While older individuals (70 years or above) tend to participate in the community screening campaign, younger individuals (below 60) tend to participate in social media screening campaign. However, social media campaigns for at-home self-sampling prove highly efficient in detecting individuals with A1c values of 42-47 mmol/mol compared to community campaigns.

Disclosure
N.Cayuelas mateu: Other Relationship; Abbott Diagnostics. T.Thybo: Other Relationship; Abbott Diagnostics.
1255-P: Prevalence Trends of Diabetes Subgroups in Mexico—A Data-Driven Analysis of Nationally Representative Surveys Spanning 2016–2021
Authors: EDUARDO ANTONIO VILLA NEFTALI , YAXMEHEN BELLO-CHAVOLLA OMAR , RAMÍREZ-GARCÍA DANIEL , FERMIN CARLOS , VARGAS-VÁZQUEZ ARSENIO , BASILE-ALVAREZ MARTÍN R. , NUÑEZ ALEJANDRA , PAZ CABRERA CÉSAR D. , FERNÁNDEZ CHIRINO LUISA , ENRIQUE CABALLERO A. , SEIGLIE JACQUELINE A. 
Published: June 2023

Background: Diabetes subgroups are a promising framework for characterizing diabetes heterogeneity but data on the epidemiology and sociodemographic profile of these subgroups in the Mexican population are sparse.
Methods: We conducted a serial cross-sectional analysis of the National Health and Nutrition Survey in Mexico (2016-2021). Diabetes subgroups (obesity related [MOD], severe-insulin deficient [SIID], severe-insulin resistant [SIRD], and age-related [MARD]) were classified using self-normalizing neural networks using HbA1c, time since diabetes diagnosis, HOMA2-IR, HOMA2-B, and BMI. Sociodemographic inequalities were proxied with the social lag index, which captures state-level social disadvantage.
Results: Diabetes prevalence in Mexico increased from 13.3% (95%CI 11.5-15.1) in 2016 to 15.8% (95%CI 13.6-17.9) in 2021, with the highest increases in the Northern-Pacific, Central-Pacific, and Center regions. SIDD was the most prevalent diabetes subgroup in Mexico, followed by MOD, MARD, and SIRD. Increases in diabetes prevalence were primarily attributed to MOD and SIRD. SIID had higher aggregation in states with higher social lag (Fig. 1).
Conclusion: Diabetes subgroups in the Mexican population display geographic and sociodemographic differences, which may help identify populations at higher risk of health disparities and adverse outcomes.

Disclosure
N.Antonio villa: None. A.Caballero: None. J.A.Seiglie: Consultant; BDMT Global, Techspert Expert Network. O.Bello-chavolla: None. D.Ramírez-garcía: None. C.Fermin: None. A.Vargas-vázquez: None. M.R.Basile-alvarez: None. A.Nuñez: None. C.D.Paz cabrera: None. L.Fernández chirino: None.
1262-P: Circulating Lysophosphatidic Acid Levels Suggest a Metabolic Pathway in T3cDM and Distinguish It from T2DM
Authors: KETAVARAPU VIJAYASARATHY , ASLAM MOHSIN , TALUKDAR RUPJYOTI , AMANCHY RAMARS , SRIPADI PRABHAKAR , POWERS ALVIN C. , VENKAT NARAYAN K.M. , COATE KATIE C. , STAIMEZ LISA R. , JAGANNATHAN RAM , REDDY D NAGESHWAR , SASIKALA MITNALA 
Published: June 2023

Introduction: Diabetes associated with chronic pancreatitis (T3cDM) has distinct clinical features. We investigated metabolomics signature to distinguish T3cDM from T2DM.
Methods: Study participants (n=200); treatment naïve nonalcoholic calcific chronic pancreatitis [CP] patients (n=106, age 34.4±11.1 years, BMI 20.9±2.8), T2DM patients (n=68, age 46±10.7 years BMI 27.0±5.8), healthy controls (n=26, age 31.0±5.3 years, BMI 25.0±2.8) were recruited prospectively. OGTT was performed to define diabetes (ADA criteria) with 60% CP patients being normoglycemic, 19% having prediabetes and 21% with diabetes. Metabolomics was done on fasting plasma samples using liquid chromatography/mass spectrometry and quantifications were measured on tandem mass spectrometry. Student’s t-test, PLS-DA, ROCs were used to compare and compute to assess the performance of identified metabolites in distinguishing diabetes subtypes (T3cDM and T2DM). Regression analysis was employed to develop a prediction model.
Results: A total of 5493 and 4104 metabolites were detected in T3cDM and T2DM respectively. Untargeted metabolome profiling identified significant differences in fatty acid conjugates in CP. Fatty acid conjugates were 28% in normoglycemic CP, 60% in prediabetic CP, 13% in T3cDM as compared to 42% in controls. Among them, 57 fatty acid conjugates showed increased peak intensities. Comparison of absolute quantifications identified higher lysophosphatidic acid (LPA) in T3cDM 40.50±6.55, T2DM 21.65 ± 1.75; p=0.01 in comparison to controls 16.20±3.4 ng/ml. Sensitivity and specificity for LPA were 81.8%, 78.6% with AUC 80% (p&lt;0.0001), 95% CI (70.6-87.8). Prediction model (null and full model p&lt;0.0001) and its performance (Hosmer-Lemeshow test p=0.9) indicated high accuracy (AUC 87%; 95% CI, 77.8-92.7).
Conclusion: Increased Lysophosphatidic acid levels implicate glycerolipid pathway in the pathogenesis of T3cDM and can be used to distinguish T3cDM from T2DM.

Disclosure
V. Ketavarapu: None. M. Aslam: None. R. Talukdar: None. R. Amanchy: None. P. Sripadi: None. A.C. Powers: None. K. Narayan: None. K.C. Coate: None. L.R. Staimez: None. R. Jagannathan: None. N. D: None. M. Sasikala: None.

Funding
Science and Engineering Research Board, India Project (CRG/2019/005125)
1266-P: Validation of a Predictive Model of Diabetes in People with Overweight and Obesity
Authors: TURCHIN ALEXANDER , SHUBINA MARIA , MORRISON FRITHA J. , AHMAD NADIA , NEFF LISA M. , KAN HONGJUN 
Published: June 2023

Obesity is the most common chronic disease in the U.S. A substantial subset of people with obesity are at high risk for type 2 diabetes mellitus (T2DM) and many of their risk factors for T2DM are modifiable. It is important to identify this at-risk subset to appropriately direct treatment and resources for earlier intervention and the prevention of T2DM. The original model was developed using EMR data of 338,653 adults &lt; 65 years old with BMI ≥ 25 kg/m2 and without baseline T2DM between 2000 and 2019. Variables were selected from a literature-based pool of risk factors for T2DM using LASSO penalized Cox regression. A Cox model (adjusted for the competing risk of death) was developed using an 80% training dataset with selected variables and internally validated on a held-out 20% dataset of EMR data. This model was then externally validated on a dataset of 103,419 participants of the Nurses’ Health Study (NHS) and Health Professionals Follow-Up Study (HPFS). Over a mean of 7.0 years of follow-up, 30,100 (8.9%) patients in the EMR dataset developed T2DM (1.3% annual incidence). The predictive model included BMI (HR 1.47 for 5 kg/m2; 95% CI 1.46 - 1.49), age, history of hypertension, systolic blood pressure and family history of diabetes. The model achieved a Harrell’s C-statistic of 0.76 on the held-out EMR dataset and the calibration slope for 10-year estimates was 1.09. In the NHS-HPFS external validation dataset, 12,402 (12.0%) individuals developed T2DM over a mean 14.2 years of follow-up (0.85% annual incidence). On this dataset, the model achieved Harrell’s C-statistic of 0.72 and the calibration slope for 10-year estimates of 0.78. It is feasible to use predictive modeling to identify people with overweight and obesity at high risk of T2DM. This approach could be utilized to guide population management and clinical treatment decisions.

Disclosure
A.Turchin: Consultant; Proteomics International, Covance, Research Support; AstraZeneca, Edwards Lifesciences Corporation, Eli Lilly and Company, Novo Nordisk, Stock/Shareholder; Brio Systems. M.Shubina: None. F.J.Morrison: None. N.Ahmad: Employee; Eli Lilly and Company. L.M.Neff: Employee; Eli Lilly and Company, Research Support; Aegerion Pharmaceuticals, Stock/Shareholder; Eli Lilly and Company. H.Kan: Employee; Eli Lilly and Company, Stock/Shareholder; Eli Lilly and Company.

Funding
Eli Lilly and Company
1270-P: A Neural Network Model for the Prediction of Comorbid Cardiometabolic Diseases—Proof of Concept Using UK Primary Care Data
Authors: KRENTZ ANDREW , BRUNSCHWIG LUCAS S. , DIBNER YARON , MICHEL HUGO , JAUN ANDRÉ 
Published: June 2023

Background and Aims: Cardiometabolic comorbidities frequently develop in individuals with hypertension, type 2 diabetes, or hypercholesterolemia. When present in combination, the risks of vascular disease are additively increased.
Methods: We created an artificial intelligence neural network to forecast the development of additional comorbidities when a single cardiometabolic disorder was present. The neural network was first taught diagnostic criteria to reproduce current clinical guidelines with 95% accuracy and, in a second step, trained on the outcome of anonymized electronic medical records of 48225 adults from South London primary care clinics, where 6127 had hypertension, 3001 had type 2 diabetes, and 5630 were treated for hypercholesterolemia. Among these cohorts, 2142, 1482 and 724 developed a second morbidity within a 3 year follow up period.
Results: Prediction of an initial comorbidity had a sensitivity of 0.94±0.14, 0.85±0.32, 0.83±0.36 and specificity of 0.87±0.24, 0.90±0.19, 0.93±0.14 up to 1, 2 and 3 years prior to the diagnosis respectively. A second comorbidity was then predicted with a sensitivity of 0.63±0.1, 0.63±0.1, 0.52±0.21 for patients with hypertension who developed type 2 diabetes and 0.76±0.09, 0.70±0.08, 0.85±0.13 for patients with type 2 diabetes who developed hypertension.
Interpretation: This proof-of-concept analysis demonstrates the utility of a neural network to predict the development of one or more comorbidities based on data routinely collected in primary care. At the level of individual patients knowledge of the probability of acquiring additional comorbidities could provide opportunities for prevention. Non-pharmacological and specific pharmacological interventions could be directed at avoiding or postponing additional cardiometabolic risk factors.

Disclosure
A.Krentz: None. L.S.Brunschwig: Employee; Metadvice SA. Y.Dibner: Employee; Metadvice. H.Michel: None. A.Jaun: Board Member; Metadvice.
1271-P: Associations of Combined Socioeconomic, Behavioral, and Metabolic Factors with Undiagnosed Diabetes and Prediabetes among Different Racial and Ethnic Groups
Authors: DING QINGLAN , LU YUAN , HERRIN JEPH , ZHANG TIANYI , MARRERO DAVID G. 
Published: June 2023

Background: The study aimed to utilize socioeconomic, behavioral, and metabolic factors to classify adults without diagnosed diabetes into distinct cardiometabolic risk clusters. Racial/ethnic differences in the associations between clusters and undiagnosed diabetes and prediabetes were also explored.
Methods: Data were obtained from the National Health and Nutrition Examination Survey (1999-2018). The k-prototypes clustering algorithm was used to identify clusters using 21 factors. Logistic regression was used to assess differences in the associations between clusters and undiagnosed diabetes or prediabetes by race/ethnicity.
Results: Among 38,476 adults without diagnosed diabetes, we identified 3 clusters. Cluster 1 contained the highest proportions of alcohol consumers, had shortest sleep duration and poorest diet quality. Cluster 2 comprised healthy younger adults with lowest income, and lowest rates of healthcare access. Cluster 3 was mostly older males with chronic conditions; they were least physically active, and more likely to have healthcare access. Regardless of race/ethnicity, the adjusted undiagnosed diabetes risk was 14.9 times higher (95% CI 10.9, 20.2) in Cluster 3 and 3.7 times (95% CI 2.8, 4.8) higher in Cluster 1 (vs. Cluster 2). An elevated prediabetes risk was observed for Clusters 3 and 1 among non-Hispanic Whites, non-Hispanic Blacks, and Hispanic. Among other races/ethnicities, there were no significant differences in prediabetes risk between Clusters 3 and 2.
Conclusion: Clustering analysis using a large number of socioeconomic, behavioral, and metabolic factors revealed three distinct groups of adults, with substantially different risks of undiagnosed diabetes and prediabetes. Incorporating socioeconomic and behavioral factors into traditional clinical risk measures may lead to better identification of subgroups at higher risk for undiagnosed diabetes and prediabetes.

Disclosure
Q.Ding: None. Y.Lu: None. J.Herrin: Consultant; Johnson & Johnson Medical Devices Companies. T.Zhang: None. D.G.Marrero: None.

Funding
Clifford B. Kinley Trust
1275-P: Incident Diabetes Before and During the COVID-19 Pandemic among Youth in Kaiser Permanente Southern California
Authors: MEFFORD MATTHEW T. , WEI RONG , LUSTIGOVA EVA , MARTIN JOHN P. , REYNOLDS KRISTI 
Published: June 2023

Background: Prior research found increases in type 1 and type 2 diabetes (T1D/T2D) among youth during the COVID-19 pandemic but did not focus on age, sex, or race/ethnicity variation. We examined incidence rates from 2016-2021 in Kaiser Permanente Southern California (KPSC), a large, integrated healthcare delivery system.
Methods: KPSC members &lt;20 years old, with no diabetes prior to their incidence year were followed using electronic health records for diabetes defined using diagnoses, labs, and diabetes medications. We calculated age- and sex-standardized incidence rates per 100,000 person-years (PY) for T1D and T2D between 2016-2021 overall and by age, sex, and race/ethnicity. We used Poisson regression to calculate incidence rate ratios (IRR) comparing 2020-2021 to 2016-2019.
Results: Incidence of T1D increased from 18.5/100,000 PY in 2016-2019 to 22.4/100,000 PY in 2020-2021 with increased IRR among 10-19-year-olds, both sexes, and Hispanic individuals. (Table) Incidence of T2D increased from 14.8/100,000 PY in 2016-2019 to 24.7/100,000 PY in 2020-2021 with increased IRR among 10-19-year-olds, both sexes, and those with non-Hispanic Black, Hispanic, and other/unknown race/ethnicity.
Conclusion: Incidence of both T1D and T2D increased following the start of the pandemic. Future research to understand potential underlying physiologic and behavioral risk factors is warranted.

Disclosure
M.T.Mefford: None. R.Wei: None. E.Lustigova: None. J.P.Martin: None. K.Reynolds: Research Support; Novartis Pharmaceuticals Corporation.