bluuebunny/crossref_metadata_2025_split huggingface dataset:
13-OR: Trends in Life-Threatening Hyperglycemia-Related Complications among Commercially-Insured Diabetes Patients Before and After the 2010 Rise in Insulin Prices
Authors: MEIRI AMIR , CALLAWAY KATHERINE , WHARAM J. FRANK 
Published: June 2019

U.S. insulin pricing began increasing dramatically in 2010, possibly caused by rising artificial insulin production and market domination by several pharmaceutical companies. Studies over the last 20 years have shown that such high prices are associated with patient rationing of insulin. The commercially-insured population includes patients with both type 1 and 2 diabetes who have experienced increasing cost sharing over the last decade, often in the form of high deductible health plans. This rise in insulin pricing combined with higher cost sharing might increase life-threatening diabetes-related complications. We hypothesized that diabetic ketoacidosis (DKA) and hyperosmolar coma (HOC) would increase after the sharp rise in insulin prices that began in 2010. We applied an interrupted times series design, with 2010 used as the change point given previous research showing that insulin prices began rising sharply in this year. We studied a large commercially insured population with an average annual number of diabetes patients of 507,578 during 2005-2014. Patients with diabetes were identified using a standard algorithm based on ICD9 codes and oral antidiabetes medicines. We calculated annual emergency department visit rates for combined DKA and HOC in this population. We use a first-order autoregressive segmented regression model to determine if there was a change in the complication trend from before to after 2010. The estimated 2005 rate of DKA and HOC emergency department visits was 50.9 per 10,000 diabetes patients (p&lt;0.001), which decreased to 36.2 per 10,000 by 2009 (trend: -3.7 per 10,000 per year; p&lt;0.001). However, from 2010-2014 the complication rate rose by 5.2 per 10,000 per year (p=0.002) relative to the 2005-2009 trend.
In conclusion, life-threatening hyperglycemia-related complications among commercially-insured diabetes patients increased after the 2010 insulin price increase.

Disclosure
A. Meiri: None. K. Callaway: None. J. Wharam: None.

Funding
National Institutes of Health; Centers for Disease Control and Prevention
131-OR: Effects of Dapagliflozin, Metformin, or Exercise on Glucose Metabolism in Individuals with Prediabetes: The PRE-D Trial
Authors: FÆRCH KRISTINE , BLOND MARTIN B. , AMADID HANAN , NIELSEN LEA BRUHN , VISTISEN DORTE , CLEMMENSEN KIM K. , PEDERSEN CAMILLA HARTMANN , KARSTOFT KRISTIAN , RIED-LARSEN MATHIAS , JØRGENSEN MARIT E. 
Published: June 2019

Introduction: We assessed the effects of dapagliflozin, metformin or exercise on glucose metabolism in individuals with prediabetes.
Methods: 120 participants were randomized to 13 weeks of either: 1) dapagliflozin (DAP, 10 mg once daily); 2) metformin (MET, 1700 mg daily); 3) exercise (EXE, 5x30 min/week); or 4) control (CON, no treatment). Participants were tested at baseline and after 6 and 13 weeks of intervention with oral glucose tolerance tests with 0, 30, 60, 120 min samples performed at baseline and at 13 weeks. Treatments were stopped the day before the last visit (two days before in EXE). Intention-to-treat analyses were conducted (baseline-adjusted).
Results: 44% were men. At baseline, the median (Q1;Q3) age was 62 (54;68) years, BMI 30.8 (28.6;34.3) kg/m2, HbA1c 41 (39;43) mmol/mol (5.9 (5.7;6.1)%), fasting plasma glucose (FPG) 5.6 (5.2;5.8) mmol/L, and fasting serum insulin (FSI) 72 (47;99) pmol/L. HbA1c decreased in DAP at 6 weeks (Table 1). All groups showed reductions of around 1 mmol/mol at 13 weeks. MET, and to a lesser extend DAP, decreased FPG. FSI was reduced by 19-25% in all treatment groups, except for EXE at 13 weeks. The iAUCglucose increased by 66% in MET, and iAUCinsulin decreased somewhat in DAP and EXE.
Conclusion: All treatments slightly improved HbA1c and fasting measures. Only DAP and EXE showed signs of improvements in postprandial glucose metabolism.

Disclosure
K. Færch: Research Support; Self; Ascensia Diabetes Care, AstraZeneca, Unilever. Stock/Shareholder; Self; Novo Nordisk A/S. M.B. Blond: None. H. Amadid: None. L.B. Nielsen: None. D. Vistisen: Stock/Shareholder; Self; Novo Nordisk A/S. K.K. Clemmensen: None. C.H. Pedersen: None. K. Karstoft: Employee; Self; Novo Nordisk A/S. M. Ried-Larsen: Other Relationship; Self; Novo Nordisk A/S. M.E. Jørgensen: Research Support; Self; Amgen Inc., AstraZeneca, Danish Diabetes Association, Sanofi-Aventis. Stock/Shareholder; Self; Novo Nordisk A/S.

Funding
Novo Nordisk Foundation; AstraZeneca
1311-P: Machine Learning (ML) Application to Predict Patient Risk of Nonadherence in Type 2 Diabetes Management Using U.S. Claims Databases
Authors: CHEN XIN , FERNANDES GAIL , CHEN JIE , LIU ZHIWEN , BAUMGARTNER RICHARD 
Published: June 2019

Medication non-adherence is one of the common leading public health challenges facing the U.S. Poor medication adherence in patients with diabetes, especially type 2 diabetes mellitus (T2DM), may be associated with inadequate glycemic control, increased morbidity and mortality and lead to increased health services utilization and hospital admissions. The use of predictive models based on ML using “big” healthcare data can help identify and predict a subpopulation with high risk of nonadherence, thus providing a scope for improving value in health care and reducing the cost burden. In this study, we extracted 111,180 T2DM patients initiating metformin monotherapy (index date) from the Truven database to train the ML models and predict patients’ level of adherence to metformin monotherapy. Patients must have had at least 6 months of pre-index (baseline) and at least 2 years of post-index (follow-up) data available. Adherence was measured as proportion of days covered (PDC) for metformin in the second year after the index date with PDC &gt;= 0.8 labeled as high-adherence and &lt; 0.8 labeled as low-adherence. A total of 120 variables were extracted including patients’ demographic information, T2DM-related medication and procedure use, comorbidities, and metformin usage information. In the preliminary analysis, random forest classifiers with 80% random split training set and validated with the 20% test set has reached 0.73 accuracy and 0.73 sensitivity. Due to the high dimensionality and sparsity of the features, we will apply further feature engineering and additional non-linear ML models such as XGboosting, BART and super learner to compare with logistic regression model and to optimize the accuracy and sensitivity. A T2DM cohort from Optum claims database will be used for cross-validation to ensure the generalization of the model. This ML model could also be adapted for other therapeutic areas.

Disclosure
X. Chen: Employee; Self; Merck & Co., Inc. G. Fernandes: None. J. Chen: None. Z. Liu: Employee; Self; Merck & Co., Inc. R. Baumgartner: None.
1312-P: Admission Plasma Glucose and HbA1c in Emergency Hospital Admissions by Ethnicity
Authors: MANLEY SUSAN E. , SUSARLA RADHIKA , ROUND RACHEL A. , NIGHTINGALE PETER , WILLIAMS JOHN A. , STRATTON IRENE M. , WEBBER JONATHAN , GKOUTOS GEORGIOS , HANIF WASIM , ROBERTS GRAHAM , GHOSH SANDIP 
Published: June 2019

Introduction: As HbA1c is now widely used for the diagnosis of diabetes with WHO cut-off ≥ 48 mmol/mol/6.5%, it is debatable whether the value should vary by ethnicity.
Aim: This study compares plasma glucose and HbA1c in white European WE, South Asian SA, unknown/other U and Afro-Caribbean AC people admitted as an emergency.
Methods: Electronic patient records were interrogated over 1 year (2014/5) for a clinical audit, CARMS-12031R. Glucose was measured on wards with meters/gas machines or the laboratory along with HbA1c on Tosoh G8 HPLC analysers if haemoglobin normal.
Results: There were 30,664 people of whom 22,045 (72%) had glucose recorded and 2,083 (7%) HbA1c. 1,904 (6%) had both glycaemic markers and were aged 64 (50-78) years, median (IQ range); 839 (44%) female; 560 (29%) prior diabetes diagnosis; 1,405 (74%) WE, 296 (16%) SA, 112 (6%) U and 91 (5%) AC. Glucose was 7.4 (5.8-10.6), 8.6 (6.2-12.3), 8.1 (5.9-10.7), 7.0 (5.9-11.6) mmol/L and HbA1c 42 (37-55), 50 (41-70), 42 (38-60), 46 (39-70) mmol/mol/6.0 (5.5-7.2), 6.7 (5.9-8.6), 6.0 (5.6-7.6), 6.4 (5.7-8.6)%, respectively. HbA1c was higher relative to glucose in SA and AC compared to WE and U, p&lt;0.001.
Conclusions: Haematological differences related to red blood cell turnover may account for the variance; this should be recognised by those involved in producing protocols/guidelines for diagnosis. More research is required on using HbA1c to confirm undiagnosed diabetes in admissions.

Disclosure
S.E. Manley: None. R. Susarla: None. R.A. Round: None. P. Nightingale: None. J.A. Williams: None. I.M. Stratton: Consultant; Self; Novo Nordisk A/S. Research Support; Self; Bayer AG, Boehringer Ingelheim International GmbH. J. Webber: None. G. Gkoutos: None. W. Hanif: Advisory Panel; Self; Boehringer Ingelheim International GmbH. Consultant; Self; Novo Nordisk A/S. Research Support; Self; AstraZeneca, Janssen Diagnostics, Sanofi. Speaker's Bureau; Self; AstraZeneca, Novartis AG, Novo Nordisk A/S. G. Roberts: None. S. Ghosh: Advisory Panel; Self; Abbott. Other Relationship; Self; Mylan.
1315-P: A Novel Microsimulation Model for Evaluating CVD Risk Assessment with Coronary Artery Calcium in Diabetes
Authors: FERKET BART , HUNINK MYRIAM , MASHARANI UMESH , MAX WENDY , FLEISCHMANN KIRSTEN 
Published: June 2019

Background: Several studies including the Multi-Ethnic Study of Atherosclerosis (MESA) have demonstrated the value of coronary artery calcium (CAC) for CVD risk prediction. However, whether CAC can refine risk assessment for patients with diabetes to improve long-term outcomes at reasonable cost is uncertain. We therefore developed a microsimulation model and determined its internal validity.
Methods: We constructed a state-transition microsimulation model (R and TreeAge software) with Well, Post CVD, and Death states using data on 5,492 MESA participants (N=607 with diabetes at baseline, median follow-up 8.6 years). To generate individualized transition probabilities, we used Cox regression of coronary heart disease, heart failure, stroke, and competing death with age as time scale. Microsimulations were based on baseline risk factors (sex, ethnicity, smoking, diabetes, bp, lipids, BMI, CAC) with incident diabetes (N=610), CAC and CVD as transient states. We compared predicted with observed 9-year risks and calculated C-statistics.
Results: Our model showed good calibration and discriminative performance across the various outcomes in the MESA cohort at 9 years (Table).
Conclusion: We developed a new microsimulation model that will be used to evaluate long-term cost effectiveness of CAC-based risk assessment in diabetes. Validity will be further evaluated in independent external data.

Disclosure
B. Ferket: None. M. Hunink: None. U. Masharani: Research Support; Self; Clementia Pharmaceuticals. W. Max: None. K. Fleischmann: None.

Funding
American Diabetes Association (1-18-ICTS-041 to K.F.)
1316-P: Adiponectin-Related Genetic Variation and Dietary Pattern Associations with Metabolic Health in Children across Weight Status: From a Large Cohort Study
Authors: GAO SHAN , LI GE , WILLI STEVEN M. , GROUP BCAMS STUDY , LI MING 
Published: June 2019

Adiponectin and related genetic variants are associated with adipose tissue function and cardio-metabolic risks. Moreover, dietary patterns affect metabolic health partly through modulating secretion of adiponectin from adipose tissue. We aimed to examine interactions between adiponectin related genetic variants and dietary patterns on metabolic health in different weight status. Childhood lifestyle factors, adiponectin and six related genetic variants (loci in/near ADIPOQ, CDH13, WDR11FGF, CMIP and PEPD) from GWAS were assessed in 3,482 children aged 6-18 years from BCAMS cohort in 2004. In 2015, 352 of these individuals completed an in-depth follow-up examination. Being metabolically unhealthy was defined as having any metabolic syndrome component or a HOMA-IR≥3.0. In multiple models, rs6773957 at ADIPOQ locus (OR=1.25, 95% CI=1.08-1.46, P =0.004) and rs4783244 at adiponectin receptor CDH13 locus (OR=0.83, 95% CI =0.70-0.98, P =0.025) were significantly correlated with metabolic risks independent of adiponectin levels and life-style factors in normal weight children, and these associations were less obvious in overweight/obesity group. Moreover, we observed a significant interaction effect between rs6773957 and dietary patterns (P =0.008) for metabolic health in normal weight children. The adiponectin-decreasing allele at rs6773957 locus was associated with greater metabolic risks in response to unfavorable dietary patterns, while no significant genotype effect was found in healthy dietary patterns. Similar interaction was found in the subgroup analysis using longitudinal data (P=0.033).
In conclusion, healthy dietary patterns might affect adiponectin gene expression, which may particularly improve adipose tissue function and metabolic health independently of weight change. ADIPOQ locus confers more metabolic risks in healthy dietary patterns when contrasted with adverse dietary patterns.

Disclosure
S. Gao: None. G. Li: None. S.M. Willi: Advisory Panel; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Roche Diagnostic USA. Research Support; Self; Jaeb Center for Health Research, National Institute of Allergy and Infectious Diseases, Sanofi-Aventis. Other Relationship; Self; National Institute of Diabetes and Digestive and Kidney Diseases. M. Li: None.

Funding
National Key Research and Development Program of China (2016YFC1304801); Key Program of Beijing Municipal Science & Technology Commission (D111100000611001, D111100000611002); Beijing Natural Science Foundation (7172169); Beijing Science & Technology Star Program (2004A027); Novo Nordisk (2011A002); National Key Program of Clinical Science (WBYZ2011-873); Chinese Academy of Medical Sciences (2017PT32020, 2018PT32001); Jingxi Scientific Program of Beijing Chaoyang Hospital (JXPY201606)
1324-P: Glucose Metabolism among Obese and Nonobese Children of Mothers with Gestational Diabetes
Authors: LU JUN , GU YUYING , WANG LEISHEN , LI WEIQIN , ZHANG SHUANG , LIU HUIKUN , LENG JUNHONG , LIU JIN , WANG SHUO , HOU LIFANG , BACCARELLI ANDREA , HU GANG 
Published: June 2019

Abdominal obesity is more closely associated with diabetes than general obesity in adults, however, it is unknown which kind of obesity is more closely associated with abnormal glucose metabolism in children. We recruited 973 children of mothers with prior gestational diabetes mellitus (GDM). Children’s height, weight, waist circumstance, fasting glucose and insulin were measured using standardized methods. Logistic regression models were used to assess the single and joint associations of general and abdominal obesity with the risks of hyperglycemia (the upper quartile of fasting glucose), insulin resistance (the upper quartile of HOMA-IR), and β-cell dysfunction (the lower quartile of HOMA-% β). Compared with normal weight children, children with general overweight/obesity had higher levels of HOMA-IR and HOMA-%β, higher odds ratios for hyperglycemia (1.56, 95% confidence intervals [CIs] 1.06-2.30) and insulin resistance (3.44, 95% CI 2.32-5.09), and a lower odds ratio for β-cell dysfunction (0.65, 95% CI 0.41-1.04). Children with abdominal obesity had increased insulin resistance (2.54, 95% CI 1.71-3.76) but not hyperglycemia and β-cell dysfunction compared with normal weight children. In the joint analyses, children with general overweight only or with both general and abdominal obesity but not with abdominal obesity only had increased hyperglycemia and insulin resistance compared with normal weight children. General obesity was more closely associated with major abnormal glucose metabolism than abdominal obesity in children of mothers with GDM.

Disclosure
J. Lu: None. Y. Gu: None. L. Wang: None. W. Li: None. S. Zhang: None. H. Liu: None. J. Leng: None. J. Liu: None. S. Wang: None. L. Hou: None. A. Baccarelli: None. G. Hu: None.

Funding
Tianjin Women’s and Children’s Health Center; Tianjin Public Health Bureau; European Foundation for the Study of Diabetes/Chinese Diabetes Society; Lilly Program for Collaborative Research between China and Europe; National Institute of Diabetes and Digestive and Kidney Diseases (R01DK100790 to G.H.); National Institute of General Medical Sciences (U54GM104940 to G.H.)
1339-P: Ratio of Visceral-to-Subcutaneous Fat Area Is Different between Simple Obesity and Type 2 Diabetes in Adolescents
Authors: ABE YURIKO , URAKAMI TATSUHIKO , YOSHIDA KEI , AOKI MASAKO , HARA MITSUHIKO , MORIOKA ICHIRO 
Published: June 2019

Background: Visceral fat accumulation is strongly associated with type 2 diabetes (T2DM). In contrast to visceral fat, subcutaneous fat might even be beneficial against metabolic abnormalities.
Objective: To investigate the association between simple obesity or T2DM and the ratio of visceral fat area (VFA) to subcutaneous fat area (SFA) (V/S ratio) in Japanese adolescents.
Design/Methods: An age- and sex-matched retrospective study was conducted in Tokyo Metropolitan Hiroo Hospital, Nihon University Hospital, and Nihon University Itabashi Hospital with ethics approval. Sixty-one adolescents with simple obesity or T2DM aged 10 to 15 years who have been visiting in these outpatient clinics between 2002 and 2018 were enrolled in this study. Simple obesity was defined as BMI ≥95%ile but without T2DM. VFA and SFA were investigated using CT at the umbilical levels. Subjects were classified into 2 groups: simple obesity group (n=38) and T2DM group (n=23).
Results: Comparisons between the 2 groups are shown in Table 1. In simple obesity group, ALT, TC, HDLC or non-HDLC levels were significantly different that those in T2DM group. SFA and V/S ratio in simple obesity group were significantly higher and lower than those in T2DM group, respectively.
Conclusion: V/S ratio is different between simple obesity and T2DM in Japanese adolescents. V/S ratio is the most useful predicter of T2DM in adolescents.

Disclosure
Y. Abe: None. T. Urakami: None. K. Yoshida: None. M. Aoki: None. M. Hara: None. I. Morioka: None.
134-OR: Effects of Tirzepatide (TZP), a Novel Dual GIP and GLP-1 Receptor Agonist, on Biomarkers of Nonalcoholic Steatohepatitis (NASH) in Patients with T2D
Authors: HARTMAN MARK L. , SANYAL ARUN , LOOMBA ROHIT , WILSON JONATHAN M. , BRAY ROSS , NIKOOIENEJAD AMIR , DUFFIN KEVIN L. , ROBINS DEBORAH A. , HAUPT AXEL 
Published: June 2019

Nonalcoholic fatty liver disease (NAFLD) is common in T2D patients and increases the risk of NASH and cirrhosis. In a Phase 2 trial, TZP significantly reduced HbA1c and body weight at 26 weeks (≥ 37% achieved 10% weight loss at 2 highest doses). Patients with T2D were randomly assigned (1:1:1:1:1:1) to receive either once-weekly sc TZP (1, 5, 10, or 15 mg), dulaglutide (1.5 mg), or placebo for 26 weeks. Because of the overlap of T2D and NAFLD populations, we measured several NASH related biomarkers to explore whether TZP may have potential efficacy in NASH. These included: ALT, AST, Keratin-18 M30 fragment (K-18, apoptosis marker; Peviva), Pro-C3 (fibrosis marker, a fragment of the NH2-terminal propeptide of type III procollagen; Nordic Bioscience), and adiponectin (adipokine that protects liver from inflammation and fibrosis; Pacific Biomarkers). Results (Table) were analyzed in a modified intent-to-treat population using a mixed model for repeated measures. Significant (p&lt;0.05) decreases from baseline with TZP occurred in ALT (all doses), AST (1, 5, 15 mg), K-18 (5, 10, 15 mg) and Pro-C3 (15 mg); decreases were significant for TZP vs. placebo in K-18 (10 mg) and Pro-C3 (15 mg), and for TZP vs. dulaglutide in ALT (10, 15 mg). Increases in adiponectin with TZP were significant compared to placebo for 10 and 15 mg. Further evaluation of TZP in patients with NASH is warranted.

Disclosure
M.L. Hartman: Employee; Self; Eli Lilly and Company. A. Sanyal: Consultant; Self; Ardelyx, Boehringer Ingelheim Pharmaceuticals, Inc., Exhalenz, Gilead Sciences, Inc., Hemoshear, Intercept Pharmaceuticals, Inc., Lilly, Mallinckrodt Pharmaceuticals, Nimbus Therapeutics, Nitto Denko, Novartis Pharmaceuticals Corporation, Pfizer Inc. Employee; Self; Sanyal Bio. Research Support; Self; Bristol-Myers Squibb Company, Conatus Pharmaceuticals Inc., Echosens, Galectin Therapeutics Inc., Immuron Ltd, Merck & Co., Inc., Salix Pharmaceuticals, Sequanna. Stock/Shareholder; Self; Akarna Therapeutics, GENFIT, Natural Shield, NewCo LLC, Tiziana. Other Relationship; Self; Elsevier, UpToDate. R. Loomba: Consultant; Self; Eli Lilly and Company, Novo Nordisk Inc. J.M. Wilson: Employee; Self; Eli Lilly and Company. R. Bray: Employee; Self; Eli Lilly and Company. A. Nikooienejad: Research Support; Self; Eli Lilly and Company. K.L. Duffin: Employee; Self; Eli Lilly and Company. Stock/Shareholder; Self; Pfizer Inc. D.A. Robins: Employee; Self; Eli Lilly and Company. A. Haupt: Employee; Self; Lilly Diabetes. Stock/Shareholder; Self; Lilly Diabetes.

Funding
Eli Lilly and Company
1343-P: A Comparison of C-Peptide and Glucose Responses between Children and Adolescents Who Progress to Type 1 Diabetes (T1D)
Authors: ISMAIL HEBA M. , NATHAN BRANDON M. , PALMER JERRY P. , DIMEGLIO LINDA , SOSENKO JAY M. 
Published: June 2019

Type 1 diabetes is a heterogeneous disease with differences in β-cell dysfunction and rates of progression. We thus assessed whether there are differences in C-peptide and glucose responses during 2-hour oral (OGTTs) and intravenous (IVGTTs) glucose tolerance tests between children and adolescents at high risk for T1D. Data from the Diabetes Prevention Trial-type 1 (DPT-1) study participants who progressed to T1D was used for the analysis. We compared C-peptide and glucose responses between children (&lt;10.0 years old; 7.1±1.9 years; n=125) and adolescents (10.0 years to &lt;18.0 years old; 12.8±2.2 years; n=94). The risks for T1D were similar between the children and adolescents (mean 3-year T1D estimates from DPT-1 Risk Score: 63% and 56% respectively), as was the time to diagnosis (2.4±2.1 years vs. 2.5±2.2 years, respectively). Adolescents had higher OGTT derived AUC C-peptide levels (3.8±1.5 ng/ml vs. 1.9±1.4 ng/ml; p&lt;0.001 with BMIZ adjustment), whereas their AUC glucose levels were similar to children (138.6±25.1 mg/dl vs. 139.6±22.8 mg/dl). The 0 to 30 minute C-peptide response from baseline OGTTs was significantly higher among adolescents compared to children (2.6±1.6 vs. 2.1±1.2, p=0.004 with BMIZ adjustment). However, C-peptide and glucose changes for each subsequent 30-minute OGTT interval were nearly identical between the children and adolescents. Similar to the 0 to 30 minute C-peptide response, the first-phase insulin response from baseline IVGTTs was higher in adolescents (114.1±74.0 µU/ml vs. 88.6±59.9 µU/ml; p&lt;0.001 with BMIZ adjustment).
In conclusion, the findings showed that despite a lower early insulin response in children, OGTT glucose levels were not higher. This suggests increased insulin sensitivity. The findings also showed that despite the lower early insulin response, the time to diagnosis did not differ. Other aspects of insulin responsiveness, and perhaps sensitivity, appear to also determine the progression rate to T1D.

Disclosure
H.M. Ismail: None. B.M. Nathan: None. J.P. Palmer: None. L. DiMeglio: Research Support; Self; Amgen Inc., Caladrius Biosciences, Inc., Janssen Research & Development, Medtronic, Sanofi. Other Relationship; Self; Dexcom, Inc. J.M. Sosenko: None.

Funding
National Institutes of Health