Novo Nordisk Inc Research Articles

2-OR: Impact of N Terminal Pro B-Type Natriuretic Peptide and High Sensitivity Cardiac Troponin on the Prediction of Death and Cardiovascular Events in High-Risk Patients with Type 2 Diabetes

We assessed the relative contributions of N-terminal pro-B-type natriuretic peptide (NTBNP) and high sensitivity cardiac troponin (hsTnT) to the prediction of death and cardiovascular (CV) events in 5597 (with complete data) of 8561 patients with type 2 diabetes (T2DM) and CV disease (CVD) and/or chronic kidney disease (CKD) enrolled in the Aliskiren Trial in Type 2 Diabetes Using Cardiorenal Endpoints (ALTITUDE). We analysed Harrell’s C-statistics (Cs) to estimate Cox model performance to predict death (n= 473) and a CV composite outcome (CVCO: CV death, resuscitated cardiac arrest, nonfatal myocardial infarction, stroke or heart failure hospitalization, n= 1129) after a median follow-up of 2.6 years, using a base model (BM) of 19 clinical baseline variables. The Cs for predicting death in the BM (0.724) was augmented by adding hsTnT (0.744, p= 0.002) which was further improved by NTBNP (0.779, p <0.001). Similarly, the BM for predicting CVCO Cs (0.716) was improved by hsTnT (0.732, p= 0.001) and enhanced further by including NTBNP in the model (0.763, p <0.001). Notably, NTBNP by itself was as predictive as BM plus hsTNT for predicting death (both 0.744, p= 1.0) and the CVCO (0.732 vs. 0.721, p= 0.27). In patients with T2DM and CVD or/and CKD, NTBNP was the major prognostic factor and should be considered for risk stratification. Disclosure M.V.B. Malachias: Speaker’s Bureau; Self; Biolab Sanus Farmaceutica, Libbs Farmaceutica. P. Jhund: Advisory Panel; Self; Cytokinetics Inc. Research Support; Self; Boehringer Ingelheim International GmbH. Speaker’s Bureau; Self; Novartis AG. Other Relationship; Self; AstraZeneca. B. Claggett: None. M.O. Wijkman: None. R. Bentley-Lewis: Consultant; Self; Novo Nordisk Inc. Research Support; Self; Janssen Pharmaceuticals, Inc. P.C. Brunel: Consultant; Self; Novartis AG. N. Chaturvedi: Consultant; Self; AstraZeneca. A.S. Desai: Consultant; Self; Abbott, Alnylam Pharmaceuticals, AstraZeneca, Biofourmis, Boehringer Ingelheim Pharmaceuticals, Inc., Boston Scientific, DalCor Pharmaceuticals, Merck & Co., Inc., Novartis Pharmaceuticals Corporation, Regeneron Pharmaceuticals, Relypsa, Inc. Research Support; Self; Alnylam Pharmaceuticals, AstraZeneca, Novartis Pharmaceuticals Corporation. S.M. Haffner: None. H.D. Parving: None. M.F. Prescott: Employee; Self; Novartis Pharmaceuticals Corporation. S. Solomon: Consultant; Self; AstraZeneca, Theracos, Inc. Research Support; Self; AstraZeneca, Theracos, Inc. D. de Zeeuw: Advisory Panel; Self; AbbVie Inc., Bayer AG, Boehringer Ingelheim International GmbH, Fresenius Medical Care, Janssen Pharmaceuticals, Inc., Mitsubishi Tanabe Pharma Corporation. J.J. McMurray: Other Relationship; Self; AbbVie Inc., Alnylam Pharmaceuticals, Amgen, AstraZeneca, Bayer Healthcare Pharmaceuticals Inc., Bristol-Myers Squibb, Cardurion, GlaxoSmithKline plc., Novartis Pharmaceuticals Corporation, Theracos, Inc. M.A. Pfeffer: Consultant; Self; AstraZeneca, CinCor, Correvio, Corvidia, DalCor Pharmaceuticals, GlaxoSmithKline plc., Innovative Science, Jazz Pharmaceuticals, MyoKardia, Inc., Novartis Pharmaceuticals Corporation, Novo Nordisk Inc., PharmaScience, Sanofi US, Servier, Takeda Development Center Americas, Inc. Research Support; Self; Novartis Pharmaceuticals Corporation. Funding Novartis Pharmaceuticals (NCT00549757)

1062-P: Real-World Effectiveness of Gliclazide MR vs. Sitagliptin as Second-Line Therapy in People with Type 2 Diabetes Uncontrolled on Metformin

Background: International guidelines recommend metformin as first-line therapy in people with type 2 diabetes (T2D). Many patients will eventually need dual therapy; sulfonylureas (SUs) and dipeptidyl-peptidase 4 inhibitors (DPP-4i) remain the most commonly prescribed second-line therapies. Available evidence, mostly from RCTs, generally indicates greater HbA1c reductions with SUs. No real-world comparative effectiveness studies have compared gliclazide MR, a later generation SU, and sitagliptin, the most commonly used DPP-4i. Aim: To investigate the effectiveness of gliclazide MR vs. sitagliptin as second-line therapies in people with T2D uncontrolled on metformin monotherapy. Methods: New users of gliclazide MR or sitagliptin were identified (1:1 high-dimensional propensity score matching) in the UK Clinical Practice Research Datalink (CPRD) database between 1/1/2010 and 21/10/2019, from a cohort of adults with T2D. A Cox model was used to estimate time to HbA1c <7.0% (primary outcome); secondary outcomes included time to HbA1c ≤6.5%. Results: A total of 2346 patients (59.3% men; mean age 63 years, HbA1c 8.5%, diabetes duration 4.3 years) were included. Patients were 28% more likely to reach HbA1c <7% (HR [95% CI]: 1.28 [1.10-1.49]) and 50% more likely to reach HbA1c ≤6.5% (1.50 [1.19-1.93]) with gliclazide MR vs. sitagliptin. The difference in favour of gliclazide MR was maintained across patients’ characteristics (ethnicity, cardiorenal disease, age, diabetes duration, baseline HbA1c). Durability (time until switch or an add-on of a new drug or a stop) and persistence (duration of index drug) were similar. There was no significant difference in severe and nonsevere hypoglycaemic events. Conclusion: These results demonstrate greater real-world effectiveness of gliclazide MR vs. sitagliptin as second-line therapy after metformin, with a similar persistence, durability and rate of hypoglycaemia. Disclosure F. Zaccardi: Speaker’s Bureau; Self; Napp Pharmaceuticals. V. Cortese: Employee; Self; Servier. E. Jacquot: Employee; Self; Servier. F. Tyrer: None. S. Seidu: Advisory Panel; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Servier. Board Member; Self; Novartis Pharmaceuticals Corporation, Novo Nordisk Inc. Research Support; Self; AstraZeneca, Janssen Pharmaceuticals, Inc., Sanofi-Aventis. Speaker’s Bureau; Self; Amgen, Lilly Diabetes, Merck Sharp & Dohme Corp. M.J. Davies: Advisory Panel; Self; Boehringer Ingelheim International GmbH, Novo Nordisk A/S, Sanofi, Sanofi US. Speaker’s Bureau; Self; Boehringer Ingelheim International GmbH, Napp Pharmaceuticals, Novo Nordisk A/S, Sanofi. Other Relationship; Self; Ingeus UK. K. Khunti: Advisory Panel; Self; Amgen, AstraZeneca, Bayer AG, Berlin-Chemie AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Menarini Group, Merck Sharp & Dohme Corp., Napp Pharmaceuticals, Novartis AG, Novo Nordisk A/S, Roche Pharma, Sanofi-Aventis, Servier. Board Member; Self; AstraZeneca, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Sanofi-Aventis. Consultant; Self; Amgen, AstraZeneca, Bayer AG, Berlin-Chemie AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Menarini Group, Merck Sharp & Dohme Corp., Napp Pharmaceuticals, Novartis AG, Novo Nordisk A/S, Roche Pharma, Sanofi-Aventis, Servier. Research Support; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novartis AG, Novo Nordisk A/S, Pfizer Inc., Sanofi-Aventis, Servier. Speaker’s Bureau; Self; Amgen, AstraZeneca, Bayer AG, Berlin-Chemie AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Menarini Group, Merck Sharp & Dohme Corp., Napp Pharmaceuticals, Novartis AG, Novo Nordisk A/S, Roche Pharma, Sanofi-Aventis, Servier.

1792-P: Measures of ß-Cell Function from Two-Step Hyperglycemic Clamps: Relation to Glycemia

We derived β-cell measures compensating for insulin resistance (disposition indices [DI]) from two-step hyperglycemic clamps with arginine stimulation, and examined their associations with glycemia cross-sectionally and longitudinally after treatment. Data included 355 adults (age 23-66 y; 51% female) and 89 youth (age 10-19 y; 71% female) from the RISE Consortium studies. Clamps were done at baseline and after 12 mo treatment with medications or gastric banding. Insulin sensitivity was quanitfied as M/I. β-cell responses included acute insulin (AIRg) and C-peptide (ACPRg) responses to glucose; steady-state C-peptide (SSCP) at glucose ∼11.1 mmol/L; and maximum insulin (AIRmax) or C-peptide (ACPRmax) responses to arginine at glucose >25 mmol/L. DIs were calculated from M/I and β-cell responses as [responses x (M/I)-b ]. The Table shows the correlations between each DI and glucose at baseline, and changes after treatment. The correlations were higher in youth than adults, except for changes in AIRmax or ACPRmax and 2-hour glucose. The correlations for ACPRg and AIRg were generally higher, followed by SSCP and then maximal responses. Thus, in the RISE cohorts, measures of early β-cell response were more strongly associated with glycemia than were late responses, with stronger correlations in youth. This underscores different contributions of early and late insulin secretion in the regulation of glycemia. Disclosure A. Xiang: None. T.S. Hannon: None. K.J. Mather: Research Support; Self; Abbott, Merck & Co., Inc., Novo Nordisk Inc., Sanofi. E. Barengolts: None. M. Cree-Green: Advisory Panel; Self; Novo Nordisk Inc. K.J. Nadeau: None. S. Sam: None. S.E. Kahn: Advisory Panel; Self; Boehringer Ingelheim International GmbH, Eli Lilly and Company, Intarcia Therapeutics, Janssen Scientific Affairs, LLC., Merck & Co., Inc., Novo Nordisk A/S, Pfizer Inc. T.A. Buchanan: None. T. Consortium: None. Funding American Diabetes Association (1-14-RISE-01 to S.E.K.); National Institute of Diabetes and Digestive and Kidney Diseases

977-P: Alleviating Carbohydrate Counting with a FiASP-and-Pramlintide Artificial Pancreas: A Randomized Pilot Study

Objective: The aim of this pilot study was to assess if a FiASP-and-pramlintide artificial pancreas (AP) could alleviate the need for CHO counting by using a simple meal announcement system (pressing a button, no CHO counting) without degrading glycemic control. Methods: We conducted a 24-hour inpatient, randomized, crossover, non-inferiority, pilot study to compare (i) FiASP AP with full CHO counting (FCC) and CHO-matched boluses with (ii) FiASP-and-pramlintide AP with simple meal announcement (SMA). Pramlintide and FiASP were delivered in a basal-bolus manner using a fixed ratio (1U: 10µg). Results: Seven participants (age 26.2±16, HbA1c 8.4±0.8%) were included in the analysis. The time in range (3.9-10 mmol/L) was 85.7% (IQR: [72-93]) in the FCC arm and 87.3% [75-95] in the SMA arm (p=0.21). Time spent >10mmol/L did not differ between interventions (FCC: 11.4% [0.9-22], SMA: 10.1% [3.1-25], p=0.38). Time <3.9mmol/L was lower in the SMA arm (2.1% vs. 4.1%, p=0.02). One participant experienced persistent GI symptoms in the SMA arm. Conclusions: The FiASP-and-pramlintide SMA system has the potential of reducing the burden of CHO counting without degrading glucose control. Outpatient studies are warranted. Disclosure M. Tsoukas: Advisory Panel; Self; Eli Lilly and Company, Novo Nordisk Inc. Speaker’s Bureau; Self; Boehringer Ingelheim (Canada) Ltd., Janssen Scientific Affairs, LLC. E. Palisaitis: None. J. Rutkowski: None. J.E. von Oettingen: None. L. Legault: Advisory Panel; Self; Dexcom, Inc., Lilly Diabetes. Research Support; Self; AstraZeneca K.K., Merck & Co., Inc., Sanofi-Aventis. Other Relationship; Self; Lilly Diabetes. J. Yale: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim (Canada) Ltd., Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Novo Nordisk A/S, Sanofi. Board Member; Self; Diagnos. Research Support; Self; Bayer Inc., Novo Nordisk A/S, Sanofi. Speaker’s Bureau; Self; Abbott, AstraZeneca, Boehringer Ingelheim (Canada) Ltd., Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Medtronic, Novo Nordisk A/S, Sanofi. A. Haidar: Consultant; Self; Eli Lilly and Company. Research Support; Self; Dexcom, Inc., Eli Lilly and Company. Funding JDRF (2-SRA-2018-654-M-B)

1782-P: Impact of Treatment with Medication vs. Laparoscopic Gastric Banding (GB) on ß-Cell Function in Adults with Impaired Glucose Tolerance (IGT) or Type 2 Diabetes (T2D) in the Restoring Insulin Secretion (RISE) Study

The RISE Consortium conducted a study in adults with IGT or recently diagnosed T2D to determine if β-cell function can be conserved or improved. Participants were randomized to GB, metformin, liraglutide + metformin (L+M), or placebo. β-cell function was assessed at baseline (BAS) and at 12 mo (12M) on therapy. Hyperglycemic clamp measures of β-cell function were: acute C-peptide (CP) response to glucose (ACPRg), steady-state CP (SSCP) at a plasma glucose of 11.1 mmol/L and maximal CP response to arginine, a non-glucose secretogogue, at a plasma glucose >25 mmol/L (ACPRmax). At BAS, BMI, ACPRg, SSCP, and ACPRmax were similar across groups. BMI was lower at 12M in all treatment groups and unchanged in those on placebo (Table). Analyses were adjusted for age, sex, and race. Participants randomized to L+M had significant increases in ACPRg and SSCP. There was also a modest but significant attenuation in ACPRmax in the L+M group. In contrast, participants who received GB or metformin alone had no change in β-cell function. Liraglutide appears to result in increased acute and steady-state responses, but greater β-cell “exhaustion” evidenced by a relative reduction in the CP response to arginine. Mechanisms responsible for this finding and its long-term implications are needed. Disclosure D.A. Ehrmann: None. S. Edelstein: None. A. Xiang: None. T.A. Buchanan: None. S.A. Arslanian: Research Support; Self; National Institutes of Health. Other Relationship; Self; AstraZeneca, Eli Lilly and Company, Novo Nordisk Inc. S. Caprio: None. K.J. Mather: Research Support; Self; Abbott, Merck & Co., Inc., Novo Nordisk Inc., Sanofi. K.J. Nadeau: None. S.E. Kahn: Advisory Panel; Self; Boehringer Ingelheim International GmbH, Eli Lilly and Company, Intarcia Therapeutics, Janssen Scientific Affairs, LLC., Merck & Co., Inc., Novo Nordisk A/S, Pfizer Inc. T. Consortium: None. Funding American Diabetes Association (1-14-RISE-01 to S.E.K.); National Institute of Diabetes and Digestive and Kidney Diseases

1239-P: University of California Diabetes Initiative: A Multi-institution Collaboration to Improve Diabetes Care

Background: In Spring 2019, the University of California (UC) health system launched a UC Wide Diabetes Initiative. In response to the growing population of people with diabetes, as well as significant heterogeneity in diabetes care across five UC campuses, the UC Health Diabetes Initiative aims to increase alignment in methods of diabetes care delivery, and to improve clinical outcomes. Methods: The UC Diabetes Initiative joins five financially and operationally independent academic medical campuses - UC Davis, UC San Francisco, UC Los Angeles, UC Irvine, and UC San Diego. Endocrinologists, primary care physicians, pharmacists, and program managers represent each campus, with data scientists and program leaders from the UC Office of the President. Powered by a central EHR data warehouse, we built a Diabetes Dashboard to show demographics, outcome (e.g., A1c) and process measures (e.g., eye exam) for more than 45,000 adults with diabetes cared for by more than 2,000 providers across the UC system. Current Work: Our collaborative identified three focus domains for improvement: 1) Medical Neighborhood 2) Patient Education and 3) Pharmaceutical Use. Within each of these domains, we used a semi-structured approach based on local expertise and experience to narrow our focus. Specific interventions were selected based on potential impact, feasibility, and key stakeholder feedback. We focus on designing and delivering three UC-wide interventions to 1) increase use of A1c point-of-care testing 2) increase reach of diabetes education and 3) utilize a “UC-way” diabetes pharmaceutical algorithm. Implementation will begin in Summer 2020; our ongoing work will be the focus of subsequent evaluation. Conclusions: The UC Health Diabetes Initiative provides a unique model of multi-institution collaboration joining independent health systems around a common mission, and using population-based real-world data to select, implement and measure best practices in diabetes care delivery. Disclosure T. Kompala: None. M. Clark: None. S. Kim: None. L. Kroon: None. T.A. Peterson: None. R.M. Mowers: None. P. Surampudi: None. M. Freeby: Research Support; Self; Abbott, Novo Nordisk Inc. M. Han: None. S. Lambrechts: None. T.M. Offer: None. M. Christian: None. L. Dahm: None. L. Gibbs: None. J. Bouw: None. K. Medders: Advisory Panel; Self; Lilly Diabetes. C. Morn: None. A. Patel: None. R. Sak: None. M. Cabrera: None. A.B. Neinstein: Consultant; Self; Steady Health.

196-LB: Synergetic and Distinct Roles in the Control of Food Intake and Energy Balance for Subpopulations of NTS Neurons

To understand hindbrain pathways involved in the control of food intake, we initially defined markers for distinct subsets of nucleus tractus solitarius (NTS) neurons that respond to food intake, including those that express calcitonin receptor (Calcr), leptin receptor (LepRb), or cholecystokinin (CCK). While the chemogenetic activation of each of these NTS populations decreased short- and long-term food intake and body weight, only CCKNTS cells activated aversive CGRP-containing neurons of the parabrachial nucleus (CGRPPBN cells) and promoted a conditioned taste aversion. Indeed, the combined activation of CalcrNTS+LepRbNTS (LCNTS) cells provoked a stronger and more durable suppression of food intake and body weight than any single population but failed to promote aversive responses. Thus, while CCKNTS cells provoke aversive anorexia, CalcrNTS and LepRbNTS cells cooperatively suppress food intake without engaging aversive systems. To understand the roles for these NTS neurons in the physiologic control of food intake and energy balance, we chronically silenced them and examined food intake and energy balance. We found that silencing any single NTS population not only interfered with the response to gut peptide-mimetics, but also increased food intake and body weight, and that high-calorie food accentuated this effect. Additionally, simultaneously silencing multiple populations further increased food intake and body weight, promoting greater adiposity. These findings not only reveal the importance of both aversive and non-aversive brainstem circuits for the control of long-term energy balance, but also identify multiple synergistic hindbrain circuits that non-aversively suppress feeding. These non-aversive systems represent ideal targets for the potential treatment of obesity and associated metabolic diseases. Disclosure W.C. Cheng: None. E. Ndoka: None. B. Maerz: None. K.J. Roelofs: None. C.J. Rhodes: Employee; Self; AstraZeneca. R.J. Seeley: Consultant; Self; Ionis Pharmaceuticals, Inc., Kintai, Kintai, Novo Nordisk A/S, Sanofi, Scohia Pharma Inc. Research Support; Self; AstraZeneca, Novo Nordisk A/S, Pfizer Inc. Stock/Shareholder; Self; Redesign Health. D.A. Sandoval: Research Support; Self; MedImmune, Novo Nordisk A/S. D. Olson: Research Support; Self; MedImmune, Inc, Novo Nordisk A/S. M.G. Myers: Research Support; Self; AstraZeneca, Novo Nordisk Inc. Funding American Diabetes Association (1-16-PDF-021 to W.C.C.)

999-P: Six Months At-Home Hybrid Closed-Loop vs. Manual Insulin Delivery with Finger-Stick Blood Glucose Monitoring in Adults with Type 1 Diabetes: A Randomized Controlled Trial

Background: Few long-term RCTs compare Hybrid Closed Loop (HCL) insulin delivery to manual (non-HCL) insulin dosing in type 1 diabetes (T1D). Objective: To examine glycemic and psychosocial outcomes in adults with T1D using HCL vs. manual insulin dosing with self-monitoring of blood glucose (SMBG) for 6 months. Methods: Adults using multiple daily injections or pumps with SMBG were randomized 1:1 after insulin dose optimization to 26 weeks of HCL (Medtronic 670G) or continuation of current therapy. The primary outcome was time in target range (70-180mg/dL) with masked CGM during the final 3 weeks. Secondary outcomes included other CGM metrics, HbA1c, treatment satisfaction (DTSQs) and diabetes distress (PAID). Intention to treat analysis was performed with ANCOVA or rank sum test. Results: HCL and control groups were well balanced at baseline (Table). At 26 weeks, mean (95% CI) CGM time in range with HCL was greater by 14.8% (11.1, 18.5), with reduced high and low glucose time, and lower HbA1c. There were no between-group differences in treatment satisfaction or diabetes distress (Table). Conclusions: HCL provided a significant and sustained glycemic benefit compared with standard therapy. Results will inform potential users and health professionals and a cost-benefit analysis may facilitate HCL access. Disclosure S.A. McAuley: Advisory Panel; Self; Medtronic. Research Support; Self; Medtronic, Roche Diabetes Care. Speaker’s Bureau; Self; Lilly Diabetes, Roche Diabetes Care. M.H. Lee: Research Support; Self; Medtronic. Speaker’s Bureau; Self; AstraZeneca, Medtronic. B. Paldus: Research Support; Self; JDRF. Speaker’s Bureau; Self; Australian Diabetes Society, Medtronic. S. Vogrin: None. M.B. Abraham: Speaker’s Bureau; Self; Lilly Diabetes. L. Bach: None. M. Burt: None. N. Cohen: Advisory Panel; Self; Abbott, AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Lilly Diabetes. Research Support; Self; Ypsomed AG. Speaker’s Bureau; Self; Novo Nordisk A/S. P.G. Colman: None. E.A. Davis: None. C. Hendrieckx: None. M. de Bock: None. J. Holmes-Walker: None. J. Kaye: Advisory Panel; Self; Abbott. Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Novo Nordisk Inc. K. Kumareswaran: None. R. MacIsaac: None. R.W. McCallum: None. C.M. Sims: Stock/Shareholder; Self; Medtronic. J. Speight: Research Support; Self; Abbott, AstraZeneca, Medtronic, Sanofi-Aventis. Speaker’s Bureau; Self; American Diabetes Association, Australian Diabetes Society, Roche Diabetes Care. S. Stranks: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Lilly Diabetes, Sanofi-Aventis. S. Trawley: None. V. Sundararajan: None. G. Ward: None. A.C. Keech: Advisory Panel; Self; Amgen, Kowa Research Institute, Inc. Consultant; Self; Sanofi-Aventis. Speaker’s Bureau; Self; Abbott, Amgen. A. Jenkins: Advisory Panel; Self; Abbott, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Sanofi-Aventis. T. Jones: Other Relationship; Self; Medtronic. D.N. ONeal: None.

1261-P: OGTT Model–Derived ß-Cell Function Reveals Differential Loss in Youth vs. Adults during and following Treatment Withdrawal in the Restoring Insulin Secretion (RISE) Study

Loss of β-cell function is critical in the pathogenesis of T2D and may progress more rapidly in youth. We compared 3-hr OGTT model-derived measures of β-cell function in youth and adults with IGT or T2D in RISE treated for 12 mo with metformin (MET), or glargine followed by metformin (G/M) and 9 mo after treatment withdrawal. Model parameters included insulin sensitivity (OGIS), insulin secretion rate (ISR) at glucose 6.5 mM (ISR-6.5), total ISR (tISR), glucose sensitivity (GS: slope ISR vs. glucose concentration) and rate sensitivity (RS: ISR relative to glucose rate of change). Linear mixed models tested for differences by time (0-12 and 0-21 mo), age (youth vs. adults) and treatment (MET vs. G/M). Key observations included the following. Insulin sensitivity (OGIS) increased transiently in all but adults on G/M. In youth, insulin secretion (ISR-6.5 and tISR) and RS decreased relative to baseline, with GS also decreased in the G/M arm. In contrast, in adults there were no significant changes in modeled parameters at 21 mo. Insulin secretion and β-cell function parameters decreased more in youth vs. adults in the G/M arm. By treatment, GS decreased more in the G/M vs. MET arm in youth, but there were no differences in adults. In conclusion, only youth exhibited worsening of features of β-cell function that can only be derived with mathematical modeling. Disclosure K. Utzschneider: Other Relationship; Self; Medtronic. M. Tripputi: None. M. Cree-Green: Advisory Panel; Self; Novo Nordisk Inc. T.S. Hannon: None. K.J. Nadeau: None. E. Barengolts: None. J.P. Palmer: None. K.J. Mather: Research Support; Self; Abbott, Merck & Co., Inc., Novo Nordisk Inc., Sanofi. S. Caprio: None. S. Edelstein: None. A. Mari: Consultant; Self; Lilly Diabetes. Research Support; Self; Boehringer Ingelheim International GmbH. T. Consortium: None. Funding American Diabetes Association (1-14-RISE-01); National Institute of Diabetes and Digestive and Kidney Diseases

342-OR: Optimal Ages for Screening for T1D Risk in Children

Screening for pre-symptomatic T1D can significantly reduce the risk of DKA at diagnosis. Screening can also identify children who may benefit from interventions to delay/prevent progression from islet autoimmunity (IA) to diabetes. To help design a rational screening schedule, we analyzed data to determine the optimal ages to screen children for IA. Longitudinal data sets from birth cohort studies (DIPP, BABYDIAB, DiPiS, and DAISY) were harmonized for analyses. We analyzed the age of screening for multiple autoantibodies to insulin, GAD and IA-2 to maximize the sensitivity and positive predictive value (PPV) to predict development of T1D by age 15. Inverse probability censoring weighting was used to account for right censored outcomes. Cumulative sensitivity, dynamic specificity, positive and negative predictive values were used to describe the models. In the combined cohorts (n=6061), a one-time screening for multiple autoantibodies achieved a maximum sensitivity of 35% and a PPV of 70-80% when applied at age 3-5 yr. To increase the sensitivity above 50% and retain PPV >70%, two screenings should occur: at 2-3 yr and at 5-6 yr (Fig). Public health screening efforts to identify children progressing to T1D must make compromises based on feasibility, cost, optimal metrics. Our data represent a starting point for these considerations that should be customized based on the population’s underlying disease characteristics and public health infrastructure. Disclosure M. Ghalwash: None. V. Anand: None. W. Hagopian: Consultant; Self; Novo Nordisk Inc. M. Lundgren: None. M. Rewers: None. R. Veijola: None. A. Ziegler: None. J.L. Dunne: None.

185-OR: Efficacy and Safety of Bempedoic Acid in Patients with Diabetes, Prediabetes, and Normoglycemia: Analysis of Pooled Patient-Level Data from Four Phase 3 Clinical Trials

Background: Current guidelines support aggressive LDL-C lowering in patients with diabetes. We assessed the efficacy and safety of BA, a first-in-class ATP-citrate lyase inhibitor, by baseline glycemic status (diabetes, prediabetes, or normoglycemia) in patients with hypercholesterolemia. Methods: Four phase 3 trials randomized 3623 patients on stable lipid-lowering therapy to receive BA 180 mg or placebo (PBO) once daily for 12 to 52 weeks. Studies were grouped into 2 pools by enrollment criteria (52-weeks in patients with atherosclerotic cardiovascular disease and/or heterozygous familial hypercholesterolemia vs. 12- or 24- weeks in patients with statin intolerance). Primary efficacy endpoint was percent change from baseline to week 12 in LDL-C. Results: In both pools, BA significantly lowered LDL-C compared with PBO, regardless of baseline glycemic status (all P<.001; Table). Significant reductions with BA vs. PBO were seen in total cholesterol, non-HDL-C, apolipoprotein B, and hsCRP (all P<.01). The safety profile of BA was similar to PBO and did not vary by glycemic status. BA did not worsen measures of glycemic control or increase occurrence of new-onset diabetes mellitus compared with PBO. Conclusion: BA significantly lowered LDL-C and had a safety profile comparable to PBO, regardless of baseline glycemic status. Disclosure L.A. Leiter: Advisory Panel; Self; Abbott, Amgen, AstraZeneca, Boehringer Ingelheim (Canada) Ltd., Boehringer Ingelheim International GmbH, Eli Lilly and Company, HLS Therapeutics, Inc., Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Novo Nordisk Inc., Sanofi, Servier. Research Support; Self; Amgen, AstraZeneca, Kowa Pharmaceuticals America, Inc., Medicines Company. Speaker’s Bureau; Self; Amgen, AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, HLS Therapeutics, Inc., Janssen Pharmaceuticals, Inc., Medscape, Merck & Co., Inc., Novo Nordisk Inc., Sanofi, Servier. M. Banach: Advisory Panel; Self; Esperion Therapeutics, Inc., Novo Nordisk Inc. Research Support; Self; Resverlogix Corp. Speaker’s Bureau; Self; Amgen, Sanofi. A.L. Catapano: Other Relationship; Self; Akcea Therapeutics, Amgen, Daiichi Sankyo, Esperion Therapeutics, Inc., Kowa Company, Ltd., Menarini Group, Mylan, Novartis, Ionis Pharmaceuticals, Medco, MSD, Recordati, Astrazeneca, Aegerion, Amryt, Eli Lilly, Genzyme, Regeneron Pharmaceuticals, Sanofi. P. Duell: Consultant; Self; Akcea Therapeutics, AstraZeneca, Esperion Therapeutics, Inc. Other Relationship; Self; Regeneron Pharmaceuticals, REGENXBIO Inc., Retrophin, Inc. A. Gotto: Board Member; Self; Esperion Therapeutics, Inc. Consultant; Self; Amarin Corporation, Kowa Company, Ltd. Other Relationship; Self; Ionis Pharmaceuticals, Inc. U. Laufs: Advisory Panel; Self; Esperion Therapeutics, Inc. G. Mancini: Advisory Panel; Self; Amgen, AstraZeneca, Bayer Healthcare Pharmaceuticals Inc., Boehringer Ingelheim (Canada) Ltd., Esperion Therapeutics, Inc., HLS Therapeutics, Inc., Sanofi. K.K. Ray: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Esperion Therapeutics, Inc., Novo Nordisk Inc., Sanofi. J.C. Hanselman: Employee; Self; Esperion Therapeutics, Inc. Stock/Shareholder; Self; Esperion Therapeutics, Inc. A. Feng: Employee; Self; Esperion Therapeutics, Inc. H. Bays: Advisory Panel; Self; Esperion Therapeutics, Inc. Consultant; Self; Kowa Company, Ltd. Research Support; Self; Abbott, Acasti, Akcea, Amarin Corporation, Amgen, AstraZeneca, Dr. Reddy’s Laboratories, Esperion Therapeutics, Inc., Gan & Lee Pharmaceuticals, Ionis Pharmaceuticals, Inc., Janssen Pharmaceuticals, Inc., Johnson & Johnson, LIB, Lilly Diabetes, Matinas BioPharma, Medicines Company, MedImmune, Merck & Co., Inc., Novo Nordisk A/S, Pfizer Inc., Regeneron Pharmaceuticals, Sanofi.

303-OR: Effect of Dapagliflozin on Risk for Fast Decline in EGFR: Analyses from the DECLARE-TIMI 58 Trial

SGLT2 inhibitors may lead to short term decrease in eGFR, with later stabilization and long-term reduction in the risk for end stage kidney disease. Fast decline (FD) in eGFR can be defined as a reduction of ≥3 ml/min/1.73m2/year and is associated with poor long-term renal prognosis. In this post-hoc analysis we studied the effect of dapagliflozin (dapa) on the risk for FD in the DECLARE-TIMI 58 trial. In DECLARE-TIMI 58, 17,160 patients with T2D and established or increased risk for CVD, with mean baseline eGFR of 85.2 ml/min/1.73m2, were randomized to dapa vs. placebo and followed for a median of 4.2 years. The risk for FD was compared between treatment arms. In the time frame of 0.5 years (after stabilization) to 4 years, the proportion of patients with FD was reduced with dapa vs. placebo (26.8% vs. 37.1% respectively, p<0.0001). This observation was persistent in all subgroups assessed (Table). The mean (SD) reduction in eGFR per year was 6.3 (3.7) vs. 0.0 (2.5) ml/min/1.73m2/year in the FD (N=4,788) vs. non-FD (N=10,224) patients. The proportion of patients with FD during the entire study period (i.e., 0-4 years) was reduced with dapa vs. placebo as well (33.6% vs. 37.0% respectively, p<0.0001). Dapagliflozin reduced the risk for FD in eGFR in a broad population of patients with T2D and either established or increased risk for CVD, but relatively preserved renal function, irrespective of patients’ baseline characteristics.

247-OR: ADA Presidents’ Select Abstract: Detection of T-Cells Reactive to Hybrid Insulin Peptides in Subjects at Risk for Type 1 Diabetes

Our lab recently established that Hybrid Insulin Peptides (HIPs) are antigenic ligands for diabetogenic T cell clones in the NOD mouse model of autoimmune diabetes. Importantly, we have found that the phenotype of HIP-reactive T cells present in the peripheral blood of NOD mice is indicative of ongoing autoimmunity in the pancreas. In the human setting, we demonstrated that T cells reactive to HIPs are present in the residual islets of type 1 diabetic (T1D) organ donors and more recently, in PBMC from T1D patients. Using an IFN-gamma ELISPOT assay to test T cell reactivity in the peripheral blood of T1D patients or control subjects to a panel of 16 HIPs, we demonstrated that 70% of the responding patients showed reactivity to multiple HIPs. To determine whether the presence of HIP-reactive T cells might serve as a biomarker of disease activity in humans, we are following longitudinally a cohort of subjects positive for multiple islet autoantibodies (Ab+), individuals that are at high risk for developing T1D. Using IFN-gamma ELISPOT and CFSE dilution assays, our data indicate that HIP-reactive T cells with an inflammatory phenotype can be detected before disease onset. In one Ab+ individual that showed HIP reactivity, we used single-cell RNA sequencing to study the phenotype and TCR usage of HIP-responding T cells in 3 longitudinal samples collected 6 months apart. We observed that T cells with a regulatory phenotype (FoxP3+, CTLA-4+, LAG3+) can be observed when a proliferative response - but not inflammatory - is detected. In this ongoing study, we are reporting for the first time that HIP-reactive T cells can be observed in the peripheral blood of subjects at risk for T1D, and our data may indicate that the balance of inflammatory vs. regulatory signals of HIP-reactive T cells could be potential indicators of disease activity. Disclosure R.L. Baker: None. T. Delong: None. M. Rewers: None. P. Gottlieb: Advisory Panel; Self; Janssen Scientific Affairs, LLC., Tolerion, Inc., Viacyte, Inc. Research Support; Self; Caladrius Biosciences, Inc., Immune Tolerance Network, Janssen Pharmaceuticals, Inc., JDRF, Leona M. and Harry B. Helmsley Charitable Trust, Mercia/Nova Laboratories, National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk Inc. Stock/Shareholder; Self; IM Therapeutics. K.M. Haskins: None. Funding American Diabetes Association (1-15-ACE-14 to T.D.); JDRF (2-SRA-2017-511-S-B); National Institutes of Health (R21AI133059-01A1)

1512-P: Severe Hypoglycemia and Hyperglycemia among U.S. Adults with Diabetes and ESRD on Dialysis, 2010-2015

Glycemic management in patients with diabetes and end-stage renal disease (ESRD) is challenging. There is limited evidence about the incidence of severe hypoglycemia and hyperglycemia in this population. Here, we examine rates of emergency department visits and hospitalizations for severe hypoglycemia and hyperglycemia (ascertained using validated ICD-9/10 codes) in a national cohort of adults with diabetes and incident ESRD, included in the United States Renal Data System, between 2010-2015. We then examine risk factors for these events using logistic regression. Among 678,376 patients with ESRD, 59.5% (n=403,490) had diabetes (63.6±13.0 years, 56.4% male, 26.8% Black, and 18.0% Hispanic). Rates of severe hypoglycemia and hyperglycemia were 126.2 and 35.5 per 1000 person-years, respectively. Strongest risk factors for hypoglycemia were insulin therapy (OR 4.5 [95% CI, 4.4-4.6] vs. no medications) and non-insulin diabetes medications (OR 3.7 [3.6-3.8]); Black race (OR 1.3 [1.3-1.4] vs. Caucasian); older age: 65-74 years (OR 1.2 [1.1-1.3] and ≥75 years OR 1.1 [1.1-1.1] vs. 18-44 years); and history of amputation (OR 1.4 [1.4-1.5]) or retinopathy (OR 1.2 [1.2-1.3]). Strongest risk factors for hyperglycemia were insulin (OR 7.7 [7.4-8.2]) and non-insulin diabetes medication use (OR 2.8 [2.6-3.1]) and retinopathy (OR 1.5 [1.4-1.5]). Older age was protective for hyperglycemia (OR 0.1 [0.1-0.1] for age ≥75 and 0.2 [0.2-0.2] for age 65-74 vs. 18-44 years). Patients on peritoneal dialysis had a lower risk (OR 0.8 [0.8-0.9]) of hypoglycemia, but no difference in odds of hyperglycemia, compared to patients on hemodialysis. Hypoglycemia requiring ED/hospital care was 3.6-fold more prevalent than severe hyperglycemia, greatly exceeding rates previously reported for older adults and those with non-end stage chronic kidney disease. There is a critical need for proactive interventions to reduce hypoglycemia and related ED/hospital use in this high-risk population. Disclosure R.J. Galindo: Advisory Panel; Self; Lilly Diabetes. Consultant; Self; Valeritas, Inc. Research Support; Self; Novo Nordisk Inc. Other Relationship; Self; UpToDate. M.K. Ali: Research Support; Self; Merck &amp; Co., Inc. N. Shah: None. S. Funni: None. G.E. Umpierrez: None. R.G. McCoy: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (P30DK111024)

1280-P: Improving Type 1 Diabetes (T1D) Prediction by Incorporating Growth Features into Landmark Models

We explored the association between growth features and T1D development using landmark analysis at different ages. Analysis included individuals from 2 birth cohort studies: DAISY and BABYDIAB (n=2,664; 129 progressed to T1D). Using height and weight measured over time, percentiles for age were calculated. Missing values were imputed using LMS parameters of CDC growth charts. Rates of change of percentiles were computed over the prior year. Twelve ages (1-12 years) were used for landmark analysis with Random Survival Forest to predict probability of T1D onset in the 1- to 19-year follow up windows. The baseline model used HLA risk group, sex, T1D family history and breastfeeding history. The full model added growth features: height and weight percentiles at age and change in percentiles. Performance was measured using C-index and feature importance was ranked. Incorporating growth features significantly improved prediction accuracy of T1D onset for 95% of combinations of landmark ages and prediction window sizes (Table 1, not all ages and windows shown). The order of features from most to least predictive is: HLA group, rates of height and weight changes, height and weight percentiles, family history, breastfeeding and sex. This analysis demonstrates that using growth features can significantly improve prediction of T1D. Table 1: C-Index with and without inclusion of growth features for landmark age of 3 years. Disclosure Z. Li: None. V. Anand: None. J.L. Dunne: None. B.I. Frohnert: None. W. Hagopian: Consultant; Self; Novo Nordisk Inc. H. Hyoty: None. M. Maziarz: None. A. Ziegler: None. J. Toppari: None. Funding JDRF (1-IND-2019-717-I-X, 1-SRA-2019-722-I-X, 1-SRA-2019-720-I-X, 1-SRA-2019-721-I-X, 1-SRA-2019-719-I-X, 1-SRA-2019-723-I-X)

2054-P: Combination of Dipeptidyl Peptidase-4 (DPP-4) Inhibitor and Sodium–Glucose Cotransporter 2 (SGLT2) Inhibitor Substantially Protects Pancreatic ß-Cells Especially in Early Phase of Diabetes Rather than Advanced Phase

In diabetes treatment, it is important to protect pancreatic β-cells in addition to correct hyperglycemia. Although DPP-4 inhibitor and SGLT2 inhibitor are widely used nowadays, there is no report about β-cell protective effect by combination of both inhibitors. In this study, we examined the effects of DPP-4 inhibitor and/or SGLT2 inhibitor on β-cells and compared their effects between in early and advanced phase of diabetes. We used 7-week-old BKS. Cg-+ Leprdb/Jcl (db/db) mice as early phase and 16-week-old mice as advanced phase, and treated them for 2 weeks with oral administration of linagliptin 3 mg/kg (Lina group), empagliflozin 30mg/kg (Empa group), linagliptin + empagliflozin (L+E group), and 0.5% carboxymethylcellulose (Cont gourp). After 2-week treatment, blood glucose levels in Empa and L+E group were significantly lower than Cont group. OGTT after 1-week treatment showed that blood glucose levels were significantly lower in Empa and L+E group in both phases, and slightly lower in Lina group only in early phase. After 2-week treatment, islets size in L+E group was significantly larger than Cont group only in early phase. In GSIS using isolated islets, insulin levels in Lina, Empa and L+E group were significantly higher than Cont group in both phases. Furthermore, mRNA expression levels of ins1, ins2 and their transcription factors mafa, pdx-1, neurod and nkx6.1 were all higher in Lina and L+E group in early phase. Contrarily, mRNA expression levels of caspase3, 8 were lower in Lina and L+E group, and jnk and c-jun levels were lower in Empa and L+E group in early phase. Intriguingly, such changes were not observed in advanced phase. It seemed that DPP-4 inhibitor and SGLT2 inhibitor exerted beneficial effects on β-cells through some different mechanism. In conclusion, combination of DPP-4 inhibitor and SGLT2 inhibitor protects β-cells in early phase of diabetes. Disclosure Y. Fushimi: None. A. Obata: None. J. Sanada: None. Y. Nogami: None. T. Ikeda: None. Y. Obata: None. M. Shimoda: None. S. Nakanishi: None. T. Mune: None. K. Kaku: Advisory Panel; Self; Nippon Boehringer Ingelheim Co. Ltd., Novo Nordisk Inc. Consultant; Self; Sanwa Kagaku Kenkyusho. Research Support; Self; Taisho Pharmaceutical Co., Ltd. Speaker’s Bureau; Self; Astellas Pharma Inc., AstraZeneca, Daiichi Sankyo, Eli Lilly Japan K.K., Kowa Company, Ltd., Merck Sharp &amp; Dohme Corp., Mitsubishi Tanabe Pharma Corporation, Ono Pharmaceutical Co., Ltd., Takeda Pharmaceutical Company Limited. H. Kaneto: Research Support; Self; Astellas Pharma Inc., Boehringer Ingelheim Pharmaceuticals, Inc., Daiichi Sankyo, Eli Lilly Japan K.K., Kissei Pharmaceutical Co., Ltd., Mitsubishi Tanabe Pharma Corporation, Novo Nordisk Inc., Ono Pharmaceutical Co., Ltd., Sanofi, Sumitomo Dainippon Pharma Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Company Limited. Speaker’s Bureau; Self; Astellas Pharma Inc., AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Daiichi Sankyo, Eli Lilly Japan K.K., Mitsubishi Tanabe Pharma Corporation, Novartis Pharmaceuticals Corporation, Novo Nordisk Inc., Ono Pharmaceutical Co., Ltd., Sanofi, Sumitomo Dainippon Pharma Co., Ltd., Takeda Pharmaceutical Company Limited.

496-P: Risk Factors for Incident CKD in Prediabetes

The magnitude of risk for chronic kidney disease (CKD) in prediabetes is unclear. The study aim was to determine CKD incidence and risk factors in patients with prediabetes from the CURE-CKD registry of electronic health record data from &amp;gt;2.6 million patients with or at-risk for CKD. Adults with prediabetes were identified by established criteria for %A1C, random and fasting blood glycemia, and administrative codes. CKD was defined by estimated glomerular filtration rate (eGFR) &amp;lt;60 mL/min/1.73m2 or urine albumin-to-creatinine ratio &amp;gt;30 mg/g based upon two or more measurements &amp;gt;90 days apart and administrative codes. Cox proportional hazards regression was used to predict incident CKD. From 2006 to 2017, there were 544,253 patients with prediabetes and no CKD. Baseline A1C was 5.9±0.3% (mean±SD) and eGFR was 90.7±16.8 mL/min/1.73 m2. Notable medication use was: NSAIDs n=110,964 (20%), PPIs n=49,916 (9%), and ACEi/ARB n=63,738 (12%). Incident CKD occurred (n=59,583) at a rate of 25.2/1,000 person-years with mean time to CKD of 2.9 years. Older age, female gender, Hispanic/Latinx, Black, Native Hawaiian and Other Pacific Islander race/ethnicity, lower eGFR, PPI and ACEi/ARB use were associated with higher hazards of CKD in prediabetes (Table 1). Incident CKD is common in prediabetes with risk factors similar to those in diabetes. CKD screening and detection with a focus on kidney protection may offer novel opportunities to reduce CKD risk in prediabetes. Disclosure K.A. Hennessey: None. K.B. Daratha: None. R.Z. Alicic: None. C. Jones: None. J.J. Neumiller: None. O. Duru: None. S. Nicholas: Speaker’s Bureau; Self; Janssen Pharmaceuticals, Inc. Other Relationship; Self; Centers for Disease Control and Prevention, George Institute for Global Health, Goldfinch Bio, Inc., National Institutes of Health. S.M. McPherson: None. K.C. Norris: None. K.R. Tuttle: Consultant; Self; AstraZeneca, Bayer Inc., Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Gilead Sciences, Inc., Goldfinch Bio, Novo Nordisk Inc.

1125-P: Association of Plasma Volume with Body Weight and BNP after Long-Term Administration and Subsequent Withdrawal of the SGLT2 Inhibitor Tofogliflozin

SGLT2 inhibitors (SGLT2is) promote diuresis and reduce plasma volume (PV). However, the impact of long-term administration and subsequent withdrawal of SGLT2is on PV is little known. This study investigated the effect of long-term administration and then withdrawal of the SGLT2i, tofogliflozin (TOFO), on PV and explored correlations with variables in type 2 diabetes mellitus (T2DM). Analyzed were 166 T2DM patients who received TOFO for 52 weeks as initial monotherapy and underwent 2 weeks of withdrawal (week 54) in a phase-3 study. Percent change in estimated PV (%ΔePV) was calculated by the Strauss formula: {100*(pre Hb/post Hb)*[(100 - pre Ht)/(100 - post Ht)] - 100}. Baseline characteristics were: male (66%), age (mean: 58 y), HbA1c (8%), BMI (26kg/m2), BNP (12pg/mL) and eGFR (84mL/min/1.73m2). Paired t-tests analyzed differences from baseline to week 52 and from week 52 to 54. Correlation analysis was performed by Pearson’s product-moment correlation coefficients. Multivariate analysis explored predictors for %ΔePV. Body weight (BW) [mean, -3kg (-5%)*; * p&amp;lt;0.01 vs. baseline], ePV (-2.7%*) and ln-transformed BNP [ln-BNP: -0.1ln(pg/mL)*] had significantly decreased by week 52. %ΔBW was not significantly correlated with %ΔePV (r=-0.06) and Δln-BNP (r=0.13) while %ΔePV was significantly correlated with Δln-BNP (r=0.35). Higher baseline ln-BNP levels were independently correlated with greater reductions in %ΔePV. After 2 weeks of withdrawal, BW [+0.9kg (+1.3%)†, † p&amp;lt;0.001 vs. week 52], ePV (+6.5%†) and ln-BNP [+0.3ln(pg/mL) †] were significantly increased. %ΔBW was significantly correlated with %ΔePV (r=0.22) and Δln-BNP (r=0.32). Also, %ΔePV was significantly correlated with Δln-BNP (r=0.30). After long-term TOFO therapy, reduced PV might be correlated not with weight loss but with reduced BNP indicating fluid loss and baseline BNP might predict changed PV. Weight gain after TOFO withdrawal might be caused by fluid gain. Disclosure Y. Matsubayashi: None. A. Yoshida: Employee; Self; Kowa Company, Ltd. T. Nojima: Employee; Self; Kowa Company, Ltd. H. Suganami: Employee; Self; Kowa Company, Ltd. K. Fujihara: None. K. Kaku: Advisory Panel; Self; Nippon Boehringer Ingelheim Co. Ltd., Novo Nordisk Inc. Consultant; Self; Sanwa Kagaku Kenkyusho. Research Support; Self; Taisho Pharmaceutical Co., Ltd. Speaker’s Bureau; Self; Astellas Pharma Inc., AstraZeneca, Daiichi Sankyo, Eli Lilly Japan K.K., Kowa Company, Ltd., Merck Sharp &amp; Dohme Corp., Mitsubishi Tanabe Pharma Corporation, Ono Pharmaceutical Co., Ltd., Takeda Pharmaceutical Company Limited. H. Sone: Research Support; Self; Kyowa Hakko Kirin Co., Ltd., Novartis AG, Ono Pharmaceutical Co., Ltd., Taisho Pharmaceutical Co., Ltd., Takeda Pharmaceutical Co.

404-P: Cardiovascular Risk Scoring and Stratification in Patients with Type 2 Diabetes Enrolled in a Medicare Advantage Plan

Current tools to identify patients at risk for cardiovascular (CV) disease or events are variable, limiting their utility and generalizability. The purpose of this study was to develop a predictive model to identify patients with type 2 diabetes (T2D) who are ≥65 years of age, enrolled in a Medicare Advantage Prescription Drug (MAPD) plan and at risk for future CV events. This retrospective cohort study used administrative claims, laboratory and enrollment data from 1/2011-12/2018. Patients with T2D were identified from 1/2012-12/2013 using diagnosis codes and/or claims for antihyperglycemic medications. The dependent variable was the first composite CV event defined as ≥1 inpatient hospitalization for myocardial infarction, ischemic stroke, unstable angina, or heart failure or any evidence of revascularization. Independent variables for the prediction survival model included baseline demographic and clinical characteristics prognostic for the dependent variable. C-statistic, accuracy, sensitivity, and specificity were used to assess model performance. Risk ranking was conducted, whereby patients were classified as low, medium or at high risk of an event based on probability distribution derived cut-points. A total of 362,791 patients with T2D were identified. The proportion of patients with ≥1 CV event was 18.0% up to 5 years after T2D identification. The final model included 42 demographic and clinical variables. The C-statistic was 0.68, and accuracy, sensitivity and specificity were 0.63. Results were consistent across the training, test and holdout datasets suggesting internal validity. Up to 5 years after identification, 11% of patients classified as low, 27% as medium, and 51% as high risk had a future CV event. A predictive model for composite CV events utilizing administrative claims to identify and risk stratify patients may be used to scale focused interventions to high-risk T2D patients in a MAPD population to prevent future CVD events. Disclosure J.D. Hayden: Employee; Self; Humana. P. Pimple: Employee; Self; Boehringer Ingelheim Pharmaceuticals, Inc. Employee; Spouse/Partner; CVS Caremark. R. Luthra: Employee; Self; Boehringer Ingelheim Pharmaceuticals, Inc. T.G. Prewitt: None. V. Chiguluri: None. M. Kattan: Consultant; Self; GlaxoSmithKline plc. Research Support; Self; Boehringer Ingelheim (Canada) Ltd., Novo Nordisk Inc. R. Harvey: None. A.M. Goss: Employee; Self; Boehringer Ingelheim Pharmaceuticals, Inc. E.O. Caplan: Employee; Self; Humana. Funding Boehringer Ingelheim; Humana

215-LB: Ablation of Nos-1 Neurons in the PVH Reveals an Essential Role in Sustaining Metabolic Homeostasis, Independent of Melanocortin Function

The paraventricular hypothalamus (PVH) is vital for energy balance regulation, as developmental or mechanical lesions targeting the PVH lead to massive obesity. We have shown that activation of PVH neurons expressing nitric oxide synthase-1 (Nos1PVH) suppresses food intake and increases energy expenditure. This differentiates these neurons from the well-studied melanocortin 4 receptor-expressing population (Mc4RPVH), as activation of Mc4RPVH neurons suppresses feeding but does not alter energy expenditure. In situ hybridization studies in our laboratory show that Mc4R and Nos1 mRNAs do not overlap in the PVH, suggesting that these cell populations may regulate energy balance independently. We hypothesize that the contributions of Nos1PVH neurons to maintaining metabolic homeostasis are independent of Mc4RPVH neurons. To test this hypothesis, we used established Nos1 and Mc4R Cre-expressing lines to create a Nos1Cre+Mc4RCre dual recombinase model. Then, we inactivated Nos1PVH and Mc4RPVH neurons alone or in combination. Several metabolic parameters were monitored for 8 weeks post-injection. These experiments allowed us to examine the interdependency of Nos1 and Mc4R PVH populations in energy balance control. Silencing the Nos1PVH population alone resulted in the acute onset of obesity without affecting feeding behavior. This phenotype was exacerbated when we simultaneously silenced both Nos1 and Mc4R PVH neurons. This suggests an additive interaction between the two groups; although a synergistic effect cannot be excluded. Future studies will focus on the effects of Nos1PVH inactivation on energy expenditure and defining the Nos1 neurocircuitry that facilitates PVH-mediated metabolic regulation. Our overall goal is to unravel the cellular and neurobiological mechanisms engaged by Nos1PVH neurons and open new avenues for treating obesity. Disclosure L.D. Faulkner: None. I.E. Gonzalez: None. D. Olson: Research Support; Self; MedImmune, Inc, Novo Nordisk A/S. T.H. Meek: Employee; Self; Novo Nordisk Inc.