Lilly Diabetes Research Articles

1222-P: Characteristics, Mortality, and Clinical Outcomes of Hospitalized Patients with COVID-and Diabetes: A Reference Single-Center Cohort Study from Poland

Introduction: Diabetes is a risk factor for severe COVID-course. In this one-center report, we assessed clinical characteristics and risk factors associated with unfavorable outcomes in diabetic patients (DP) hospitalized due to COVID-19. Methods: We retrospectively analyzed data from a cohort of patients with confirmed SARS-CoV2 infection admitted to the University Hospital in Krakow (Poland) , a regional reference center for COVID-19, between March 6th 2020 and May 15th 2021. The data was collected from electronic medical records. Results: We included 5191 patients, mean age 61.98±16.66 years, 2348 (45.2%) women, 1364 (26.3%) DP. DP were older as compared to non-diabetics (median age 70 vs. 62 years, IQR 62-77 and 47-72, p<0.001) with similar gender distribution. DP were characterized by higher mortality (26.4% vs. 15.6%, p<0.001) , longer hospital stay (median 15 vs. 13 days, IQR 10-24 and 9-20, p<0.001) , more frequent ICU admission (15.7% vs. 11%, p<0.001) and more frequent requirement for mechanical ventilation (15.5% vs. 11.3%, p<0.001) . When adjusted for sex and age, the relative risk for in-hospital death, ICU admission and mechanical ventilation was 1.32 (95%CI 1.13-1.54) , 1.4 (95%CI 1.17-1.69) and 1.3 (95%CI 1.08-1.57) , respectively. Multivariable logistic regression showed age, CRP and D-dimer level, history of heart failure, and loop diuretic use were associated with higher risk of death, whereas anticoagulation therapy, ACEI/sartan/mineralocorticoid receptor antagonist use and thiazide use were associated with lower risk. Conclusions: In this large COVID-cohort, DP constituted more than one fourth of hospitalized patients. Their risk of death was ca. 30% higher as compared to non-diabetics, as was the risk of other important clinical outcomes. We identified a number of clinical, laboratory and therapeutical variables associated with risk of hospital death in DP with COVID-19. Disclosure M.Kania: None. T.Klupa: Advisory Panel; Abbott, BIOTON S.A., Sanofi, Research Support; Medtronic, Speaker's Bureau; Ascensia Diabetes Care, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Novo Nordisk. P.W.Witek: Other Relationship; Abbott, Berlin-Chemie AG, Boehringer Ingelheim International GmbH, Medtronic, Merck & Co., Inc., Novo Nordisk, Roche Diabetes Care, Sanofi-Aventis Deutschland GmbH. B.Katra: None. M.W.Rajzer: Consultant; A. Menarini Diagnostics, Speaker's Bureau; Bayer AG, Boehringer Ingelheim International GmbH, EGIS Pharmaceuticals, Servier Laboratories. M.Malecki: Consultant; Abbott Diabetes, Boehringer Ingelheim International GmbH, Lilly Diabetes, Novo Nordisk, Speaker's Bureau; Ascensia Diabetes Care, AstraZeneca, Bayer AG, Merck & Co., Inc., Mundipharma, Servier Laboratories. K.Mazur: None. M.Terlecki: None. Z.Chaykivska: None. M.K.Fiema: None. M.A.Kostrzycka: None. M.Kopka: None. M.Wilk: None. J.Hohendorff: Advisory Panel; Abbott. Funding The authors were supported by the Polish National Center for Research and Development grant (grant number SZPITALE-JEDNOIMIENNE/18/2020) .

1415-P: Risk–Benefit Data from the Worldwide EndoBarrier (EB) Registry

Uncertainty exists re risk:benefit of proximal intestinal exclusion with EB, a novel endoscopic duodenal jejunal liner device for obesity, both with and without diabetes. In view of this, during 2017, an independent, secure, on line registry was established under the auspices of the Association of British Clinical Diabetologists, for the collection of safety and efficacy data worldwide. As of December 2021, data had been entered on 10patients {age 52.1 ± 10.3 year, 53% male, 87% diabetes, BMI 41.1 ± 8.9 kg/m2} and showed many benefits (Table 1) . There were 43 (4.2%) SAEs and 139 (13.9%) less serious AEs (Table 2) . All SAE patients made a full recovery and most derived significant benefit. The benefits of EB therapy are likely to reduce the complications of diabetes. This international data from the EB registry suggests that the likely benefits of EB, far outweigh the risks Disclosure R.E.J. Ryder: None. J.P. Teare: None. A. Ruban: None. M. Haluzik: Advisory Panel; Boehringer Ingelheim International GmbH, Novo Nordisk A/S, Sanofi. Speaker's Bureau; Abbott Diabetes, AstraZeneca, Lilly Diabetes, Novartis AG. L. Munro: None. H. Frydenberg: None. J.J. McMaster: None. S. Fishman: None. R.V. Cohen: Advisory Panel; GI Dynamics. Research Support; Johnson & Johnson, Medtronic. C.M. Aboud: None. G.J. Holtmann: Research Support; AbbVie Inc., Allergan, Arena Pharmaceuticals, Inc., Bayer, Bristol Myers, Datapharm Australia Pty Ltd Commonwealth Laboratories, Pty Limited, Eli Lilly Australia Pty Limited, F.Hoffmann-La Roche Limited, Falk Foundation, Falk GmbH and Co Kg, GI Therapies Pty Ltd, Gilead Sciences Pty Limited, MedImmune Ltd Celgene Pty Limited, Mylan, Nestle Pty Ltd, Prometheus Laboratories, Quintiles Pty Limited, Servatus, Takeda Development Center Asia, Pty Ltd, Vital Food Processors Ltd. C. de Jonge: None. J. Greve: Advisory Panel; GI Dynamics. Other Relationship; Bariatric Solutions International, Ethicon, Inc. J.C. Mason: None. H. Sourij: Advisory Panel; AstraZeneca, Bayer AG, Boehringer Ingelheim International GmbH, Daiichi Sankyo, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk. Research Support; Boehringer Ingelheim International GmbH, Sanofi. Speaker's Bureau; Amgen Inc., AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novartis AG, Novo Nordisk. R. Drummond: Research Support; Fractyl Health, Inc. Speaker's Bureau; AstraZeneca, Bristol-Myers Squibb Company. B. McGowan: Advisory Panel; Johnson & Johnson, Lilly, Novo Nordisk. Research Support; Novo Nordisk. Speaker's Bureau; AstraZeneca, Novo Nordisk. Stock/Shareholder; Reset Health. S.A. Amiel: Advisory Panel; Medtronic, Novo Nordisk. Other Relationship; Sanofi. M. Yadagiri: None. P. Sen Gupta: None. K. Laubner: None. J. Seufert: Advisory Panel; Abbott, Sanofi-Aventis Deutschland GmbH. Research Support; Boehringer Ingelheim International GmbH. Speaker's Bureau; Abbott Diabetes, AstraZeneca, Bayer AG, Boehringer Ingelheim International GmbH, Lilly, Novo Nordisk, Sanofi-Aventis Deutschland GmbH. Funding Association of British Clinical Diabetologists

373-P: A Systematic Review and Meta-analysis of the Impact of Acute Hypoglycemia on Cognitive Function in Adults with Type 1 Diabetes

Acute hypoglycemia impacts negatively on cognitive function. However, it remains unclear which specific domains of cognitive function are affected, and the extent to which level of hypoglycemia modifies this relationship. We conducted a systematic review and meta-analysis to investigate the impact of controlled hyperinsulinaemic hypoglycemia on cognitive function in adults with type 1 diabetes, following PRISMA guidelines. Experimental studies comparing cognitive function task performance during euglycemia and hypoglycemia were eligible for inclusion. Preliminary analyses were conducted on 38 studies, involving 54 cognitive task outcomes across three domains of cognitive function of varying complexity: attention/information processing speed (simplest) , working memory, and complex reasoning (most complex) . Three-level meta-analyses of the standardized mean differences (SMD) in performance during euglycemia and hypoglycemia, moderated by hypoglycemia level (Mdn=2.51; range=1.98-3.5 mmol/l) were conducted for each domain, with study and task as random effects to allow inclusion of multiple effect sizes per study. Hypoglycemia significantly impaired performance on all domains, with large effect sizes for attention/information processing speed (SMD=-1.17, 95% CI:-1.60 to -0.74) and working memory (SMD=-0.84, CI:-1.to -0.63) , and a medium effect size for complex reasoning (SMD=-0.61, CI:-0.99 to -0.23) . The degree of hypoglycemia significantly moderated this relationship for working memory only, such that for every 1mmol/l decrease in glucose level, performance was reduced by SMD=0.84 (CI:0.2 to 1.49) . These findings suggest that the impact of hypoglycemia on cognitive function is related to the cognitive domain complexity, with more impaired performance on simpler relative to more complex tasks. Further, degree of hypoglycemia may be differentially related to performance depending on the domain of cognitive function. Disclosure M.M.Broadley: None. C.Hendrieckx: None. R.J.Mccrimmon: Advisory Panel; Novo Nordisk, Sanofi, Research Support; Diabetes UK, European Union, MedImmune. G.Nefs: None. U.Pedersen-bjergaard: Advisory Panel; Novo Nordisk A/S, Sanofi. C.E.Verhulst: None. J.Speight: Advisory Panel; Insulet Corporation, Research Support; Novo Nordisk, Sanofi. F.Pouwer: Research Support; Eli Lilly and Company, Novo Nordisk, Sanofi. The hypo-resolve consortium: n/a. H.Chatwin: None. U.Soeholm: Research Support; Novo Nordisk A/S. J.Axelsen: None. S.A.Amiel: Advisory Panel; Medtronic, Novo Nordisk, Other Relationship; Sanofi. P.Choudhary: Advisory Panel; Abbott Diabetes, Lilly Diabetes, Medtronic, Research Support; Novo Nordisk, Speaker's Bureau; Dexcom, Inc., Glooko, Inc., Insulet Corporation, Sanofi. B.E.De galan: Research Support; Novo Nordisk. T.W.Fabricius: None. S.R.Heller: Advisory Panel; Eli Lilly and Company, Medtronic, Mylan N.V., Zealand Pharma A/S, Zucara Therapeutics, Other Relationship; Eli Lilly and Company, Research Support; Dexcom, Inc., Speaker's Bureau; Novo Nordisk A/S. Funding Innovative Medicines Initiative 2 Joint Undertaking (777460)

806-P: Correlation of Derived Time in Range (dTIR) and Time in Range (TIR) in People with Type 2 Diabetes (T2D) Treated with IDegLira (IDL) , Degludec, or Liraglutide: A Post Hoc Analysis of the DUAL I Trial

Background and Aims: TIR (blood glucose 70-180 mg/dL) , measured by continuous glucose monitoring (CGM) , provides a more comprehensive picture of glycemic control than A1c alone. Derived TIR (dTIR) , a calculated estimate of TIR, is useful when CGM data are unavailable. This post hoc analysis of DUAL I investigated the correlation between dTIR and TIR in patients with CGM data. Materials and Methods: In DUAL I, people with T2D uncontrolled on oral antidiabetic drugs (n=1663) were randomized 2:1:1 to IDL, degludec or liraglutide, for up to 52 weeks. CGM data were collected using IPro1 and IPro2 (Medtronic) . dTIR was calculated from 9-point self-measured blood glucose (SMBG) profiles (minimum 6 points) . The Pearson correlation coefficient was used to assess correlation between dTIR and TIR at baseline, and at weeks 26 and 52. Also assessed were the correlation between change in dTIR and change in TIR, from baseline to end of trial (EOT) , and the proportion of patients achieving a ≥5% increase in TIR or dTIR at weeks 26 and 52. Results: 260 patients had CGM data. Using dTIR calculated from patients with ≥6-point SMBG profiles, a strong correlation was seen between dTIR and TIR at baseline (n=2observations; correlation 0.8838) , with a moderate correlation also seen at week 26 (n=165; correlation 0.5512) and week 52 (n=152; correlation 0.5184) . Change in dTIR and change in TIR, from baseline to EOT, were also correlated (n=137; correlation 0.7686) . Similar results were seen using dTIR calculated using ≥7- or ≥8-point SMBG profiles. A numerically greater proportion of patients achieved a ≥5% increase in dTIR vs. TIR at weeks 26 and 52 (78% vs. 54% and 62% vs. 50%, respectively) , perhaps due to missed nocturnal hypoglycemia, and limited data points, measured by SMBG. Conclusion: These data support the use of dTIR as a surrogate endpoint when CGM data are unavailable, to provide additional information on glycemic control. Disclosure A.Philis-tsimikas: Advisory Panel; Bayer AG, Novo Nordisk, Research Support; Lilly Diabetes, National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk, Viking Therapeutics. J.M.Dcruz: Employee; Novo Nordisk Global Business Services. R.Sivarathinasami: None. C.De block: Advisory Panel; Abbott Diagnostics, AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Medtronic, Novo Nordisk, Research Support; Indigo Diabetes, Speaker's Bureau; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Novo Nordisk. Funding Novo Nordisk A/S

1489-PUB: Know Diabetes by Heart Campaign and Project Dulce: A Culturally Tailored Mobile-Based Self-Management Program Supports High-Risk Populations with Diabetes to Manage Cardiovascular Disease Risk

Diabetes, high blood pressure, and obesity are major risk factors for cardiovascular disease (CVD) . Access to and awareness of health education programming is often low in ethnic/racial minorities and individuals of low socioeconomic status experience a higher prevalence of T2D, hypertension, CVD and stroke. Additionally, underserved, at-risk patients face barriers to accessing traditional in-person diabetes self-management education and support (DSME/S) due to transportation, caregiving, and work conflicts. To address this gap, the ADA’s Know Diabetes by Heart (KDBH) initiative partnered with Project Dulce, an evidence-based culturally and linguistically modified DSME/S program to overlay an innovative digital approach to diabetes support programming and resources in the community. In response to COVID-restrictions, Project Dulce sessions integrating KDBH content were delivered via telehealth group sessions and text messaging to encourage heart healthy self-management behaviors. Pre/post surveys assessed knowledge and self-management, and clinical metrics were evaluated via electronic health records. The KDBH/Project Dulce DSME/S program was delivered to 5 health systems in California: 2 Federally Qualified Health Centers, 2 County health clinics and 1 large community-based health system near the US/Mexico border. Of the N=553 who received KDBH/Project Dulce education, 47% were White, 36% Hispanic, 14% African American, Asian, Native American, Pacific Islander, and 3% other. Of all enrollees, 58% were female, and 15% were </= 45 y/o, 50% were 46-65 y/o and 35% were >/= 66 y/o. Participant feedback indicated acceptance of both the group virtual and texting programs. Findings demonstrate the feasibility of disseminating important heart healthy interventions to diverse ethnic/racial minority groups via a variety of digital and telehealth methods. Disclosure M.Ruiz: n/a. A.L.Fortmann: Consultant; Ascensia Diabetes Care, Employee; Dexcom, Inc. H.Sandoval: None. A.Philis-tsimikas: Advisory Panel; Bayer AG, Novo Nordisk, Research Support; Lilly Diabetes, National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk, Viking Therapeutics. M.Chichmarenko: None. S.R.Bagsic: None. J.Boyer: None. Funding American Diabetes Association/KDBH;

925-P: European Survey on Adults with Type 1 Diabetes (T1D) and Their Caregivers: Insights into Experience of T1D Management

Background and Aims: T1D requires constant self-management and can substantially impact quality of life. We aimed to survey patient and caregiver experiences of T1D management. Methods: Adult people with T1D (PwD) or their caregivers living in France, Germany, Italy, Spain, or the UK were invited to complete an online survey (July-August 2021) . Results: Responders were 458 PwD (54% female, mean age 47.8 years, mean age at diagnosis 24.4 years) and 54 caregivers. For PwD, moderate to very high impacts of T1D on daily life included fatigue (77%) and anxiety (65%) . The top 2 other illnesses with significant impact on PwD’s lives were hypertension (29%) and depression (26%) . Many PwD (68%) would have liked more psychological support, mainly from healthcare professionals (HCPs) . Most caregivers (76%) would have liked support, mainly from HCPs, especially diabetologists (39%) , nutritionists (31%) and psychologists (28%) . Over half of responders felt they lack knowledge on T1D (53% PwD, 56% caregivers) . Only 57% of PwD and 39% of caregivers had participated in education programmes; of those <30% of PwD/caregivers still regularly attended. There were regional differences in the proportion of PwD who had attended education programmes (Figure) , but not in the proportion who still were regularly attending. Conclusion: In Europe, PwD and their caregivers require more support and education for T1D management. Disclosure B.Kulzer: Advisory Panel; Bayer AG, Bayer AG, Becton, Dickinson and Company, Becton, Dickinson and Company, Berlin-Chemie AG, Berlin-Chemie AG, Dexcom, Inc., Dexcom, Inc., Insulet Corporation, Novo Nordisk, Roche Diabetes Care, Sanofi, Sanofi-Aventis Deutschland GmbH, Research Support; Novo Nordisk, Roche Diabetes Care. S.Down: Advisory Panel; Viatris, Speaker's Bureau; Abbott Diabetes, AstraZeneca, Lilly Diabetes, Merck Sharp & Dohme Corp., Novo Nordisk, Sanofi, Viatris. A.Seignez: Employee; Else Care. A.Vives: Other Relationship; Sanofi. M.Bonnemaire: Employee; Sanofi. A.Penfornis: Board Member; Insulet Corporation, Medtronic, Mundipharma, Novo Nordisk, Sanofi, Speaker's Bureau; Glooko, Inc., Insulet Corporation, Lilly, Novo Nordisk, Ypsomed AG. Funding Sanofi

493-P: Medical Assistant Health Coaching for Type 2 Diabetes in Primary Care: A Pragmatic, Cluster-Randomized Controlled Trial

While good cardiometabolic control can reduce complications in type 2 diabetes (T2D) , many individuals do not achieve clinical targets. This real-world trial compared medical assistant health coaching (MAC) to usual care (UC) in improving outcomes among adults with T2D and ≥ 1 of the following in the past 90 days: HbA1c ≥ 8%, LDL ≥ 100 mg/dL, SBP ≥ 140 mm/Hg. This N=600 study was conducted from 2016-2021 at four cluster-randomized clinics within two diverse health systems in Southern CA: a large, private insurance-based system [n = 298, majority non-Hispanic White, English-speaking, mid/upper socioeconomic status (SES) ]; M age = 70.2 ± 12.6] and a Federally-Qualified Health Center (n = 302, majority Hispanic, Spanish-speaking, lower SES; M age = 56.9 ± 12.0) . MAC and UC received diabetes care as usual in primary care, with referral to diabetes education and/or specialists as indicated. MAC also received in-clinic and telephone-based health coaching for up to one year (1-14 sessions; M = 5.2 ± 2.8) . Baseline mean HbA1c = 8.8 ± 2.2%, LDL = 101.8 ± 44.8 mg/dL, and SBP = 137.9 ± 19.4 mm/Hg. From baseline to 12-months, the percentage of individuals meeting quality metrics increased in both groups: HbA1c < 8% (MAC: 74.8 to 79.9%; UC: 64.0 to 80.4%) , LDL < 100 mg/dL (MAC: 75.7 to 84.9%; UC: 72.6 to 82.4%) , SBP < 140 mm/Hg (MAC: 75.0 to 86.9%; UC: 80.2 to 86.4%) . When outcomes were analyzed continuously using multi-level modeling, both MAC and UC demonstrated statistically significant improvements on all clinical outcomes; however, the rate of improvement was largely equivalent across groups (time-by-group ps > .05) . Due to the pragmatic nature of this trial, there was marked variation (by design) in intervention duration and intensity across participants, and in clinical and sociodemographic characteristics of participants across health systems. Additional analyses examining under what conditions and/or for whom the MAC intervention may prove more/less effective will be presented. Disclosure A.L.Fortmann: Consultant; Ascensia Diabetes Care, Employee; Dexcom, Inc. A.Philis-tsimikas: Advisory Panel; Bayer AG, Novo Nordisk, Research Support; Lilly Diabetes, National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk, Viking Therapeutics. T.Clark: None. S.R.Spierling bagsic: None. H.Sandoval: None. K.L.Savin: None. S.Roesch: None. L.Gallo: None. Funding NIH/NIDDK 1R18DK104250

90-OR: FreeStyle Libre (FSL) Time in Range (TIR) and Time Below Range (TBR) : Impact on HbA1c, Diabetes-Related Distress (DRD) , and Resource Utilisation in the Association of British Clinical Diabetologists (ABCD) National Audit

Introduction: With increasing access to intermittently scanned continuous glucose monitoring (isCGM) , with the FSL, it is essential to understand the effect of TIR and TBR on HbA1c, DRD, and resource utilisation in people living with diabetes Methods: Clinicians from 1NHS UK hospitals submitted FSL user data for16,034 participants, (96% type 1 diabetes) of whom 6859 had follow-up data, collected during routine clinical care and submitted to a web-based secure tool. Linear regression analysis was used to estimate the age, gender and baseline HbA1c adjusted reduction in HbA1c in the TIR categories. Results: Follow up TIR data were available for 3250 (47%) participants of which, 1241 (38%) reported TIR in line with the international consensus (3.9-mmol/l) . After adjustments for age gender, baseline HbA1c and duration of diabetes follow-up TIR ≥50% was associated with an 0.8% (8.75 mmol/mol) reduction in HbA1c (P<0.0001) and -0.29 reduction in DRD (P<0.0001) , while follow-up TIR ≥70% was associated with a 1.3% (14.mmol/mol) reduction in HbA1c (P<0.0001) and 0.40 reduction (P<0.0001) in DRD vs. those with TIR <50%. With the use of FSL, there was a 67% reduction in hospital admissions due to hypoglycaemia (none in those with TIR≥50) , a 63% reduction in hospital admissions related to hyperglycaemia/DKA and an 85% reduction in paramedic outcalls. The reduction in hospital admissions for hyperglycaemia/DKA and paramedic callouts was independent of the TIR achieved during follow-up. The incidence of severe hypoglycaemia was lower in those with TBR ≤5% as compared to those with TBR >5% (7% vs. 11%) but was not statistically significant (P=0.31) . Conclusion: In a large cohort of UK FSL users, we demonstrate a significant reduction in HbA1c, diabetes-related distress and resource utilisation which was associated with improved TIR Disclosure H.Deshmukh: None. T.Sathyapalan: n/a. B.Pieri: None. E.G.Wilmot: Advisory Panel; Abbott Diabetes, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Medtronic, Sanofi, Research Support; Insulet Corporation, Novo Nordisk, Speaker's Bureau; Abbott Diabetes, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Novo Nordisk, Sanofi. P.Choudhary: Advisory Panel; Abbott Diabetes, Lilly Diabetes, Medtronic, Research Support; Novo Nordisk, Speaker's Bureau; Dexcom, Inc., Glooko, Inc., Insulet Corporation, Sanofi. N.Shah: None. V.Tsatlidis: None. A.N.Lumb: Advisory Panel; Abbott, Dexcom, Inc., Research Support; Abbott, Novo Nordisk, Speaker's Bureau; Abbott, Dexcom, Inc., Insulet Corporation, Novo Nordisk. R.E.Ryder: None. C.Walton: None. Funding NIHR clinical lectureship

1023-P: Clusters of Depressive Symptoms and Glycemic Outcomes in Youth with Type 1 Diabetes (T1D)

Aim: Depression is a heterogeneous construct that includes various symptoms (e.g., cognitive, somatic) and is linked to worse diabetes outcomes. We examined the associations of depressive symptom clusters with glycemic outcomes using continuous glucose monitoring (CGM) data in youth with T1D. Methods: Participants (N=120) provided blood samples for HbA1c, completed a validated survey for depressive symptoms (CES-DC) , and wore CGM for one week. CGM glucose metrics were derived: % time in range (TIR) 70-180 mg/dL; % time <70 mg/dL; % time >180 mg/dL; % time >250 mg/dL; mean glucose; and glucose variability (GCV) . CES-DC items were categorized as somatic, cognitive, anhedonic, and interpersonal for analyses. Results: Youth (49% male) had a mean (±SD) age of 12.7±2.7 years, T1D duration 6.1±3.5 years, HbA1c 7.9±0.8%. Overall, higher total CES-DC score was associated with higher HbA1c (r=0.21, p=0.02) . In youth with HbA1c ≤8% (n=68) , there were no significant associations between depressive clusters and glycemic outcomes, but several significant associations emerged in youth with HbA1c >8% (n=52) . For those with HbA1c >8%, higher CES-DC total score was associated with higher HbA1c (r=0.55, p<0.0001) , greater % time >250 (r=0.29, p=0.03) , and higher mean glucose (r=0.33, p=0.02) . More symptoms on the cognitive and interpersonal clusters were associated with higher HbA1c (r=0.29, p=0.03; r=0.43, p=0.002, respectively) . More somatic symptoms were associated with greater % time >180 (r=0.34, p=0.01) , less % TIR (r=-0.34, p=0.01) , and higher mean glucose (r=0.31, p=0.03) . Conclusions: In our sample of youth with T1D, associations between depressive symptoms and glucose varied according to overall glycemic control, with notable associations in youth with HbA1c >8%. Somatic depressive symptoms were especially related to uncontrolled glucose levels, highlighting the importance of targeting glucose TIR to reduce adverse physical complaints. Disclosure A.Shapira: None. L.K.Volkening: None. L.M.Laffel: Advisory Panel; Medtronic, Roche Diabetes Care, Consultant; Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompé, Insulet Corporation, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Novo Nordisk, Provention Bio, Inc. Funding T32DK007260, P30DK036836, R01DK089349

718-P: Patients Achieving an HbA1c <5.7% with =5% Weight Loss and without Hypoglycemia: A Post Hoc Analysis of SURPASS 1 to 5

In the phase 3 SURPASS studies of tirzepatide (TZP) , a novel dual GIP/GLP-1 receptor agonist developed for the treatment of type 2 diabetes, 23%-62% of TZP-treated participants achieved a HbA1c <5.7% and 54%-88% achieving ≥5% weight loss. This post hoc analysis evaluated the proportion of participants who achieved the triple endpoint of HbA1c <5.7%, ≥5% weight loss, and no clinically significant or severe hypoglycemia. We compared the proportion of participants achieving the triple endpoint between the TZP (5, 10, or 15 mg) and respective comparator groups using the efficacy analysis dataset without rescue medication. HbA1c and weight were evaluated at the end of the treatment period at week 40 (SURPASS 1, 2, 5) or week 52 (SURPASS 3, 4) . Hypoglycemia included blood glucose level <54 mg/dL with symptoms or severe hypoglycemia at any time. Significantly more participants treated with any dose of TZP achieved the triple endpoint compared to placebo or active comparators in SURPASS 1-5 (Figure) . Of the participants treated with TZP 15 mg, 45%, 48%, 48%, 41%, 55% reached the triple endpoint compared to 1% with placebo, 15% with semaglutide 1 mg, 2% with degludec, 1% with glargine U100, and 1% with placebo, in SURPASS 1-5, respectively. Significantly more participants treated with TZP achieved a HbA1c <5.7% with ≥5% weight loss and without hypoglycemia compared to placebo, semaglutide 1 mg, or basal insulin. Disclosure A.Y. Cheng: Advisory Panel; Abbott, AstraZeneca, Bayer AG, Boehringer Ingelheim International GmbH, Dexcom, Inc., Eli Lilly and Company, HLS Theraoeutics, Insulet Corporation, Janssen Pharmaceuticals, Inc., Medtronic, Novo Nordisk, Sanofi. Board Member; Type 1 Diabetes Think Tank Network. Speaker's Bureau; Bausch Health, Canada, Merck & Co., Inc. Other Relationship; Diabetes Canada. I. Lingvay: Advisory Panel; AstraZeneca, Boehringer Ingelheim International GmbH, Lilly, Mannkind, TARGET PharmaSolutions; Valeritas;; Altimmune; DataRevive; Click; Medscape Duke CRI; Janssen Pharma; Bayer; Intercept, Novo Nordisk, Sanofi, Zealand Pharma A/S. Consultant; Novo Nordisk. Research Support; NovoNordisk; Mylan; Merck, Sanofi. P. Choudhary: Advisory Panel; Abbott Diabetes, Lilly Diabetes, Medtronic. Research Support; Novo Nordisk. Speaker's Bureau; Dexcom, Inc., Glooko, Inc., Insulet Corporation, Sanofi. E. Gomez-Valderas: Employee; Lilly. Stock/Shareholder; Lilly. S. Allen: None. K.T. Ranta: Employee; Eli Lilly and Company. J.A. Levine: Employee; Eli Lilly and Company. Stock/Shareholder; Eli Lilly and Company. V. Thieu: None. Funding Eli Lilly and Company

672-P: Performance of a New Disposable Zero-Calibration Continuous Glucose Monitoring (CGM) Sensor

Objective: A CGM sensor that is disposable and requires no calibration may make glucose management easier for people living with diabetes. The present study reports on the interim analysis of a new disposable zero-calibration sensor in adults and youth with type 1 (T1D) or type 2 diabetes (T2D) . Methods: A prospective study enrolled individuals (N=123 adults, aged 18-80 years and N=120 youth, aged 2-17 years) with diabetes at 13 sites in the United States. Raw sensor data were compared with a YSI (Yellow Springs Instruments) or blood glucose (BG) reference and involved N=15388 paired points (pps) from the arm of adults, and N=8627pps from the arm and 7781pps from the buttock of youth. Data were processed using a new zero-calibration algorithm. The primary endpoint was agreement within 20%/20mg/dL (sensor glucose [SG] ≥80mg/dL/<80mg/dL) . Multiple secondary and descriptive endpoints included agreement within 15%/15mg/dL (SG ≥70mg/dL/<70mg/dL) and the mean absolute relative difference (MARD) for the adult arm location and youth arm and buttock locations. Results: The overall 20%/20mg/dL agreement rate was 90.6% for adults, and 87.8% and 88.5% for youth arm and buttock, respectively. For adults, the 15%/15mg/dL agreement rates were 90.1% and 87.6% (SG <70 mg/dL and SG >180 mg/dL, respectively) . For youth, the 15%/15mg/dL rates were 93.2% and 86.5% for the arm (SG <70 mg/dL and SG >180 mg/dL, respectively) and 90.3% and 89.5% for the buttock (SG <70 mg/dL and SG>180 mg/dL, respectively) . The MARDs were 10.2% for adults, and 10.7% and 10.1% for youth arm and buttock, respectively. Conclusion: These interim findings on the clinical performance of the new disposable and calibration-free sensor are good and may support non-adjunctive insulin dosing in standalone CGM and automated insulin delivery systems. Disclosure B.W.Bode: Advisory Panel; CeQur SA, MannKind Corporation, Medtronic, Novo Nordisk, Zealand Pharma A/S, Consultant; Bigfoot Biomedical, Inc., Research Support; Abbott, Beta Bionics, Inc., Dexcom, Inc., Diasome, Dompé, Eli Lilly and Company, Insulet Corporation, IQVIA Inc., Jaeb Center for Health Research, Medtronic, Novo Nordisk, Provention Bio, Inc., REMD Biotherapeutics, Sanvita Medical, Senseonics, ViaCyte, Inc., Speaker’s Bureau; Abbott, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Insulet Corporation, MannKind Corporation, Novo Nordisk, Sanofi, Xeris Pharmaceuticals, Inc., Stock/Shareholder; AgaMatrix, Glytec, LLC. J.Shin: Employee; Medtronic. F.Peng: None. S.Huang: n/a. A.S.Rhinehart: Employee; Medtronic, Stock/Shareholder; Medtronic. R.A.Vigersky: Employee; Medtronic. T.S.Bailey: Advisory Panel; Abbott Diabetes, CeQur SA, MannKind Corporation, Medtronic, Novo Nordisk, Consultant; LifeScan, Sanofi, Research Support; Abbott Diabetes, Abbott Diagnostics, Biolinq, Capillary Biomedical, Inc., Dexcom, Inc., Eli Lilly and Company, Kowa Research Institute, Inc., Livongo, MannKind Corporation, Medtronic, Novo Nordisk, REMD Biotherapeutics, Sanofi, Sanvita Medical, Senseonics, ViaCyte, Inc., vTv Therapeutics, Zealand Pharma A/S, Speaker’s Bureau; Becton, Dickinson and Company, Medtronic, Sanofi. K.N.Castorino: Consultant; Lilly Diabetes, Research Support; Abbott Diabetes, Dexcom, Inc., Drawbridge Health, Inc., Eyenuk, Inc., Laxmi Therapeutic Devices, Medtronic, National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk, Speaker’s Bureau; Dexcom, Inc. M.P.Christiansen: Research Support; Abbott Diabetes, Ascensia Diabetes Care, AstraZeneca, Biolinq, Dexcom, Inc., Eli Lilly and Company, Helixmith, MannKind Corporation, Medtronic, Merck Sharp & Dohme Corp. S.K.Garg: Advisory Panel; Bayer AG, Medtronic, Zealand Pharma A/S, Consultant; Novo Nordisk, Research Support; Dexcom, Inc., Medtronic. K.B.Kaiserman: Advisory Panel; Medtronic, Consultant; Medtronic, Employee; MannKind Corporation, Research Support; Medtronic, Speaker’s Bureau; Medtronic, Stock/Shareholder; MannKind Corporation. D.R.Liljenquist: None. D.I.Shulman: Advisory Panel; Medtronic. R.H.Slover: None.

536-P: Impact of Physical Activity (PA) and Macronutrient Intake on CGM Glucometrics in Youth with T1D

Aim: Maintaining in-range glucose on days with PA is challenging for youth with T1D, often requiring fine-tuning of diet and insulin. We examined how PA and macronutrient intake impact glycemic outcomes in youth with T1D. Methods: Youth and parents completed 3-day PA and diet records and youth wore 3-day masked CGM (iPro) every 3 months for 18 months. Days were classified as active (≥60 min PA) or inactive. Diet data were analyzed using Nutrition Data System for Research (NDSR) . Daytime (6 AM-11:59 PM) CGM glucometrics were: % time (T) in range (TIR) 70-180 mg/dL, %T<70, %T>180, and glucose CV. Analyses included complete days for PA, diet, and CGM data. Separate longitudinal mixed models for daily carb, fat, and protein intake (adjusted for age, T1D duration, sex, pump vs. MDI) , assessed changes in glucometrics on active vs. inactive days. Results: Youth (N=136, 49% male, 73% pump users) were ages 8-17 yrs (12.9±2.6) with T1D duration 6.0±3.1 yrs and daily insulin 0.9±0.3 U/kg. At baseline, A1c was 8.0±0.9%, daytime %TIR 50±22% (12.0 hrs) , %T<70 5±8% (1.2 hrs) , %T>180 44±25% (10.6 hrs) , CV 37±11%; macronutrient intake was 49±9% carb, 35±8% fat, 16±4% protein. In all models of macronutrient intakes, %TIR increased by ∼5.3% (76 min; p=.01) with pump use; by 2.8% (40 min; p=.02) on active days; by 1.4% (20 min; p=.03) with 10% increase in carb intake; and by 1.7% (24 min; p=.02) with 10% decrease in fat intake. PA and carb intake did not impact %T<70; %T<70 decreased by 0.6% (9 min; p=.03) with 10% increase in fat intake. PA did not impact %T>180; %T>180 decreased by ∼5.6% (81 min; p=.02) with pump use; by 1.7% (24 min; p=.02) with 10% increase in CHO intake; and by 2.2% (32 min; p=.01) with 10% decrease in fat intake. CV decreased by 1.3% on inactive days (p=.04) ; by 1.1% with 10% decrease in CHO intake (p<.01) ; and by 1.3% with 10% increase in fat intake (p<.01) . Conclusion: PA and macronutrient intake have varying effects on glycemic outcomes. The findings reinforce the need to tailor insulin dosing algorithms for diet and PA. Disclosure R.O.La banca: None. L.K.Volkening: None. E.Dassau: Employee; Eli Lilly and Company, Research Support; Dexcom, Inc., JDRF, National Institute of Diabetes and Digestive and Kidney Diseases, Stock/Shareholder; Eli Lilly and Company. S.N.Mehta: None. L.M.Laffel: Advisory Panel; Medtronic, Roche Diabetes Care, Consultant; Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompé, Insulet Corporation, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Novo Nordisk, Provention Bio, Inc. Funding National Institutes of Health (K12DK094721, P30DK036836) ; Iacocca Foundation

118-OR: Fat Distribution Patterns Predict Type 2 Diabetes Risk and Provide Insights into Prediabetic Metabolism

Objective: Fat accumulation in liver, pancreas, skeletal muscle, and visceral bed relates to type 2 diabetes (T2D) . However, distribution of fat in these compartments is heterogenous and it is unclear if specific distribution patterns indicate high T2D risk. We therefore investigated fat distribution patterns and their link to future T2D. Methods: From 2168 individuals without diabetes undergoing computed tomography in Japan, this case-cohort study included 658 randomly selected individuals and 146 incident cases of T2D with a 6-year follow-up. Data-driven analysis (k-means) was applied to develop clusters based on fat content in liver, pancreas, muscle, and visceral bed. Hazard ratios (HRs) for association of clusters and incident T2D were estimated using weighted Cox regression. In 3 individuals without diabetes with magnetic resonance imaging and metabolic phenotyping in Germany, cluster validation with additional assessment of glycemic traits from OGTTs was conducted. Results: We identified four clusters of fat distribution: cluster 1 (Hepatic steatosis cluster) , cluster 2 (Pancreatic steatosis cluster) , cluster 3 (Myosteatosis dominant cluster) , cluster 4 (Steatopenic cluster) . Compared with Steatopenic cluster, the adjusted-HRs (95%CIs) for incident T2D were 4.02 (2.27-7.12) in Hepatic steatosis cluster, 3.38 (1.65-6.91) in Pancreatic steatosis cluster, and 1.95 (1.07-3.54) in Myosteatosis dominant cluster. The clusters were replicated in the German cohort with similar distribution of AUC-glucose to the diabetes hazard in the Japanese cohort. Insulin sensitivity and insulin secretion were different across clusters with the lowest insulin sensitivity and highest insulin secretion in Hepatic steatosis cluster. Conclusions: Extending evidence about fat accumulation in single compartments, we identified specific patterns of fat distribution with different T2D risk presumably due to differences in insulin sensitivity and insulin secretion. Disclosure H.Yamazaki: None. N.Stefan: Advisory Panel; Gilead Sciences, Inc., GlaxoSmithKline plc., Sanofi, Consultant; AstraZeneca, Intercept Pharmaceuticals, Inc., Novo Nordisk, Pfizer Inc., Speaker's Bureau; AstraZeneca, Boehringer Ingelheim International GmbH, Lilly Diabetes, Merck Sharp & Dohme Corp. A.Fritsche: Advisory Panel; Boehringer Ingelheim International GmbH, Novo Nordisk, Sanofi-Aventis Deutschland GmbH. A.L.Birkenfeld: None. R.Wagner: Advisory Panel; Akcea Therapeutics, Daiichi Sankyo, Sanofi-Aventis Deutschland GmbH, Speaker's Bureau; Lilly, Novo Nordisk, Sanofi-Aventis Deutschland GmbH. M.Heni: Advisory Panel; Boehringer Ingelheim International GmbH, Research Support; Boehringer Ingelheim International GmbH, Sanofi, Speaker's Bureau; Amryt Pharma Plc, Boehringer Ingelheim International GmbH, Novo Nordisk. S.Tauchi: None. J.Machann: None. T.Haueise: None. Y.Yamamoto: None. M.Dohke: None. N.Hanawa: None. Y.Kodama: Other Relationship; Eisai Co., Ltd. A.Katanuma: None. Funding the German Center for Diabetes Research (DZD, 01GI0925) , the state of Baden-Württemberg (32-5400/58/2, Forum Gesundheitsstandort Baden-Württemberg) , and JSPS KAKENHI Grant Number 19K16978

890-P: Health Care Economic Burden and Resource Utilization in Adults with Type 2 Diabetes and Stroke

Objectives: To evaluate health care resource utilization and all-cause healthcare costs in adults with type 2 diabetes mellitus (T2DM) and stroke. Methods: Patients ≥ 18 years of age with T2DM, with or without incident stroke, were identified between January 1, 2012 and December 31, 2020 using the Optum® Clinformatics® Data Mart database. Healthcare utilization and cost were measured for the 12 months after stroke (T2DM + stroke) or random ICD-9/ICD-code (T2DM only) . Stroke was defined as overnight hospitalization with a primary discharge code for hemorrhagic or ischemic stroke. We compared patient cohorts using an inverse probability of treatment weighting approach. Results: The incidence rate of stroke in the year following T2DM diagnosis was 0.9% (n = 16,034) . Weighted analysis compared 11,021 patients with T2DM and incident stroke (mean age, 75.1; mean Charlson comorbidity index, [CCI] 4.6) and 11,1patients with T2DM alone (mean age, 75.2; mean CCI, 4.7) . Compared to patients with T2D alone, patients with T2DM and stroke were more likely to have an IP visit (adjusted rate ratio [ARR], 5.4; 95% CI, 5.3-5.6; p < 0.01) , outpatient (OP) visit (ARR, 1.6; 95% CI, 1.6-1.6; p < 0.01) , ER visit (ARR, 1.7; 95% CI, 1.6-1.7; p < 0.01) , and longer hospital stay (ARR, 5.9; 95% CI, 5.8-5.9; p < 0.01) . Pharmacy, IP, OP, and ER costs were higher in patients with T2DM and stroke compared to patients with T2DM alone (Total costs, $8,864 per patient per month [PPPM] vs. $2,902 PPPM; p < 0.01) . IP visits (+$4,062) and OP visits (+$1,642) accounted for the biggest differences in healthcare costs. In a hypothetical population of one million patients with T2DM, we project an initial cost difference of +$615 million annually for patients with T2DM + stroke compared to T2DM alone. Conclusions: In adults with T2DM, copresence of stroke was associated with higher healthcare utilization and cost compared to adults with T2DM alone. Treatments that lower risk of stroke in patients with T2DM should be considered in this population. Disclosure A.A.King: Advisory Panel; Novo Nordisk, Board Member; JDRF, Speaker's Bureau; Abbott, Dexcom, Inc., Lilly Diabetes, MannKind Corporation, Medtronic, Novo Nordisk. J.J.Rajpura: Employee; Novo Nordisk. Y.Liang: Employee; Novo Nordisk. Y.M.Paprocki: Employee; Novo Nordisk, Stock/Shareholder; Novo Nordisk. C.Uzoigwe: Employee; Novo Nordisk, Stock/Shareholder; Novo Nordisk.

875-P: Different Effects of SGLT-2 Inhibitors on Subcutaneous and Epicardial Adipose Tissue Metabolome in Heart Failure Subjects

The exact mechanisms behind favorable metabolic and cardioprotective effects of SGLT-2 inhibitors (SGLT-2i) are still not fully understood. We performed a complex metabolomic analysis of subcutaneous (SAT) and epicardial (EAT) adipose tissue of heart failure subjects treated with SGLT-2i in order to assess their impact on different fat depots and identify potential cardioprotective factors. Nine subjects with severe heart failure with reduced ejection fraction (NYHA class III-IV) treated with SGLT-2i and 8 age-, BMI- and left ventricular ejection fraction-matched control subjects scheduled for heart transplantation or mechanical support implantation were included into the study. Eight SGLT-2i subjects and 5 control subjects had type 2 diabetes mellitus. A complex metabolomic analysis of SAT and EAT obtained during surgery was performed using liquid chromatography and mass spectrometry. SAT of SGLT-2i subjects showed marked increase in ketone bodies and a corresponding decrease of ketogenic triacylglycerols with medium-chain fatty acids suggesting enhanced ketogenesis typical for SGLT-2i use. In contrast, no such change was seen in EAT which, conversely, contained increased amount of long-chain triacylglycerols indicating significant differences in response to SGLT-2i treatment between these depots and a tendency to preserve EAT lipid content. Compared with control group, both SAT and EAT of SGLT-2i subjects consistently exerted surprisingly high levels of sphingolipids, especially sphingomyelins and ceramides, and ether-linked lipid species. In conclusion, SGLT-2i treatment leads to different metabolic responses in SAT and EAT with SAT showing mainly accented ketogenesis, while the preservation of EAT suggests other functions including potential cardioprotection. The exact role of increased sphingolipids and ether-linked lipids in both adipose tissue depots remains to be elucidated. Disclosure B.Kasperova: None. I.Pleyerova: None. K.Rosolová: None. P.Svoboda: None. J.Trnovska: None. P.Novodvorsky: Advisory Panel; Novo Nordisk, Sanofi, Other Relationship; Eli Lilly and Company, Sanofi, Research Support; Dexcom, Inc., Speaker's Bureau; Eli Lilly and Company, KRKA, Mundipharma, Novo Nordisk, Sanofi. P.Ivak: Consultant; Abbott, CARMAT SA. V.Melenovsky: Consultant; Bayer AG, Merck Sharp & Dohme Corp., Novo Nordisk, Research Support; Regeneron Pharmaceuticals Inc. I.Netuka: Board Member; LeviticusCardio Ltd., Consultant; Abbott, CARMAT SA. M.Haluzik: Advisory Panel; Boehringer Ingelheim International GmbH, Novo Nordisk A/S, Sanofi, Speaker's Bureau; Abbott Diabetes, AstraZeneca, Lilly Diabetes, Novartis AG. M.Mraz: None. O.Kuda: None. T.Cajka: None. D.Hlavácek: None. J.Mahrík: None. L.Tomanová: None. I.Lankova: n/a. S.Stemberkova hubackova: None. Funding Ministry of Health, Czech Republic - conceptual development of research organization („Institute for Clinical and Experimental Medicine – IKEM, IN 00023001“) NV19-02-00118

471-P: Glycated Haemoglobin in the First Year after Diagnosis of Type 1 Diabetes Is an Independent Risk Factor for Diabetic Retinopathy: The IMDIAB 25 Years Follow-Up Study

Background: Intensive glycemic control reduces the risk of diabetic retinopathy (DR) in people with type 1 diabetes (T1D) . However, the impact of glycemic control during the peri-diagnostic period on the long-term risk of DR is not known.Aim: To evaluate the association between the glycemic control obtained within the first year after T1D diagnosis and the long-term risk of DR. Methods: We retrospectively studied a cohort of 150 subjects enrolled within 1 year of T1D diagnosis in intervention trials conducted by the IMmunotherapy DIABetes (IMDIAB) group between 1994 and 20 and still attending follow-up visits in one of the IMDIAB centers. Data regarding clinical and biochemical features at T1D onset and during the first year of the disease were collected at the time of enrollment in the IMDIAB studies. Follow-up data about clinical features including presence of chronic complications were collected between January 2020 and January 2021 through the consultation of medical records. Results: After a median follow-up of 25 [25th-75th percentiles: 22-28] years, 26 (17.3%) people had developed DR. People with DR showed significantly higher updated first-year HbA1c (6.8 [6.2-7.8] % vs. 6.3 [5.7-7.2] %, p=0.037) and higher HbA1c at follow-up (8.0 [6.9-8.9]% vs. 7.2 [6.5-7.8]%, p=0.005) compared to people free from DR. Higher updated first-year HbA1c was also a significant predictor of higher HbA1c at follow-up (beta-coefficient: 0.24, p=0.015) . The association between the updated first-year HbA1c and DR did not significantly change after adding HbA1c at follow-up and disease duration in the multivariate model. Conclusion: Glycemic control obtained during the very first year after T1D onset is associated with long-term risk of diabetic retinopathy independently from subsequent glycemic control and other confounders. Disclosure E.Maddaloni: Consultant; Merck KGaA, Speaker's Bureau; Abbott, Medical Technology & Devices, PIKDARE S.p.A. C.Moretti: None. N.Visalli: Consultant; Sanofi. F.Tramontana: None. A.Crino: None. R.Schiaffini: Advisory Panel; Abbott, Sanofi. R.Buzzetti: Board Member; Lilly, Novo Nordisk, Sanofi, Speaker's Bureau; Abbott, AstraZeneca. P.Pozzilli: Advisory Panel; Dompé, Consultant; Abbott, Speaker's Bureau; Dompé, Lilly Diabetes, Medtronic, Sanofi. Imdiab study group: n/a. A.Carlone: None. D.Pitocco: None. G.Leanza: None. C.Suraci: None. M.Altomare: None. M.G.Cavallo: Advisory Panel; Eli Lilly and Company, Board Member; Novo Nordisk, Speaker's Bureau; AstraZeneca, Sanofi. I.Barchetta: None. S.Morano: None. Funding Italian Ministry of University and Research (PRIN 2017: 20175L9H7H)

625-P: Exploring Social Media as Potential Support for Young Adults (YA) with T1D

Objective: YA use social media (SM) frequently. Diabetes-focused SM posts may offer support for those with T1D. This qualitative study sought to explore perspectives of YA with T1D on diabetes-focused SM posts. Methods: Semi-structured interviews were conducted through videoconferencing with YA with T1D (age 18-25 years, T1D duration 1 year) . Ten diabetes-focused Instagram posts were selected, encompassing major topic areas identified in previous SM literature (e.g., humor, venting) . Participants viewed posts with captions and provided their perspectives. Interview transcripts were coded and evaluated using thematic analysis. Results: Fifteen YA participated (age 22±1.9 years, 86% white, 33% male, T1D duration 12±5.7 years, A1c 8.1±1.6%, 80% pump use, 100% CGM use) . All participants reported using SM at least once daily, but very few reported viewing or posting diabetes content. YA reactions to posts encompassed four major themes: 1. Perception of personal relevance: many participants noted whether posts applied to them. While many posts were described as “relatable,” others were suggested to be more useful soon after diagnosis or in contrast to participants’ own self-care behaviors. 2. Reduced isolation with T1D: many participants reported the posts made them feel “not alone;” some noted their lack of friends with T1D and mentioned benefits of community. 3. Frustration about living with T1D: some participants expressed anger or annoyance with diabetes, especially about hyperglycemia and cost of insulin. 4. Appreciation of public displays of T1D self-care: many participants valued openness with self-management in posts, although some expressed hesitancy in self-displays. After viewing and discussing all posts, some participants reported they may seek out diabetes-focused SM in the future when they had not previously. Conclusions: SM may be a source of community, support, and reduced isolation for YA with T1D. Further research is needed to assess SM as a means to improve self-care in this group. Disclosure T.Kaushal: None. L.A.Branka: None. K.Wentzell: None. P.V.Commissariat: None. L.M.Laffel: Advisory Panel; Medtronic, Roche Diabetes Care, Consultant; Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompé, Insulet Corporation, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Novo Nordisk, Provention Bio, Inc. Funding NIH/NIDDK (K12DK094721,P30DK036836)

1492-PUB: In Silico Modeling of the Performance of a Novel Closed-Loop Algorithm Using the UVA/PADOVA Type 1 Diabetes Simulator

AIAPS is a novel smartphone-based closed-loop algorithm in development that can be combined with any insulin pump and continuous glucose monitor. AIAPS strives to reduce burden of diabetes by requiring only limited input and by handling unannounced meals. Prior to launching the clinical research program in-silico modelling of the most recent features was performed. The objective of this study was to evaluate the AIAPS performance using the UVA/PADOVA Type 1 Diabetes (T1D) Simulator in people with T1D. AIAPS was used in the in-silico population of 33 subjects (children, adolescents, and adults) of the UVA/PADOVA T1D Simulator. Upon initialisation, 5 min CGM data, body weight, average daily insulin dose and sex for each person was available. To model a scenario with limited information for each individual upon initialization, no data on basal insulin profiles (BIP) , carbohydrate-to-insulin ratio (CR) and insulin sensitivity factor (ISF) were put into AIAPS. Additionally, no information on meals (time or carbohydrate content) were put into AIAPS. The following scenario was modelled: 84 days of closed-loop therapy without user interaction and with variable routine conditions representing the duration of the planned clinical study. Data on glycemic control for the three age groups over the 84 days are shown in table 1. Modelling included 2-5 unannounced meals with a random schedule and carbohydrate content of 130-250 g per day. In an in-silico model the AIAPS closed-loop system exceeded current glycemic targets with a TIR >70% and a TBR <4% in all age groups without user interaction or input of BIP, CR and ISF upon initialization. The next step includes testing the AIAPS performance in a randomized controlled trial. Table 1 - Glycemic control for the three age groups. Data are mean standard deviation. Disclosure A.J.Dedeshko: Stock/Shareholder; AI APS France. V.Fedotov: Stock/Shareholder; AIAPS France. A.Simic: None. C.Thivolet: Board Member; Insulet Corporation, Medtronic, Research Support; Abbott Diabetes, Lilly Diabetes, Novo Nordisk A/S, Sanofi. J.K.Mader: Advisory Panel; Abbott Diabetes, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Medtronic, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Roche Diabetes Care, Sanofi-Aventis Deutschland GmbH, Speaker's Bureau; Abbott Diabetes, Eli Lilly and Company, Medtronic, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Roche Diabetes Care, Sanofi-Aventis Deutschland GmbH, Servier Laboratories, Stock/Shareholder; decide Clinical Software GmbH.

667-P: Impact of Direction of Long-Haul Travel on Glycemic Control in Adults with Type 1 Diabetes (T1D) Using Multiple Daily Injections (MDI) of Insulin

Long-haul travel (flights >6 hours) can be very disruptive for people living with type 1 diabetes (T1D) . As part of a study comparing long-acting basal insulins during long-haul travel (Bevier & Castorino, et al) , we evaluated the impact of direction of travel on glucosecontrol (Abbott Freestyle Libre Pro) . Each journey began in Honolulu (HI) with a non-stop flight to New York (NY) lasting hours with a 6-hour time difference. After 72 hours, participants returned non-stop to HI. Each subject completed round trips (using either Glargine or Insulin Degludec as the basal insulin) . Participants traveled in the same direction for either basal insulin. To assess the impact of direction of travel, data using either basal insulin were combined. Overall, 21 participants (13 women, age 34.2±15.2 years, HbA1c 7.5±1.2%) completed both journeys. CGM-derived metrics comparing (a) initial 72 hours at each destination, (b) during each flight and (c) for the total journey are shown below. During sleep, TIR70-180 was 56±26% travelling East to West and 66±26% going from West to East. Although there were no significant differences in CGM-derived metrics irrespective of direction of travel, the data suggest that achieving the recommended time in range between 70-180 mg/dl is elusive for adults with T1D using MDI when travelling across multiple time zones. Disclosure W.C.Bevier: Research Support; Abbott Diabetes. H.Liu: Employee; Abbott Diabetes. K.N.Castorino: Consultant; Lilly Diabetes, Research Support; Abbott Diabetes, Dexcom, Inc., Drawbridge Health, Inc., Eyenuk, Inc., Laxmi Therapeutic Devices, Medtronic, National Institute of Diabetes and Digestive and Kidney Diseases, Novo Nordisk, Speaker's Bureau; Dexcom, Inc. D.Kerr: Advisory Panel; Abbott Diabetes, Novo Nordisk A/S, Sanofi, Consultant; Evidation Health, Research Support; Novo Nordisk A/S, Stock/Shareholder; Glooko, Inc., Hi.Health. Funding Novo Nordisk Investigator Sponsored Study - ISS-001227

282-OR: The Emotional Burden of Diabetes during Emerging Adulthood: “Cost. Everything Else Is Secondary.”

Emerging adults (EA) with type 1 diabetes (T1D) have multiple developmental stage-specific challenges in diabetes management, including the transition to financial independence. The recently validated Problem Areas in Diabetes-EA (PAID-EA) survey is the first measure of diabetes distress (DD) in EA to include financial concerns. A sample of 287 participants with T1D ages 18-30 years completed an online survey including the 25-item PAID-EA, measures of DD and depressive symptomology, and clinical and demographic questions. To evaluate content validity, 2 open-ended questions asked for the most important worry mentioned and what worries were missed in the questions. Responses were analyzed using directed qualitative content analysis. As cost emerged as a major contributor to DD, responses to the PAID-EA item 21 (“I worry about the cost of diabetes”) were analyzed using Chi-square or Fisher’s exact test to assess participant factors associated with cost-related DD. Most participants (89%) provided open-ended responses (78% female, mean age 24 years) . Cost was the most frequent code in the qualitative analysis: 15% reported DD related to cost and 6% to insurance. Responses included worries about aging out of parents’ insurance and limitations on career choices to ensure payment for diabetes supplies. In all survey respondents, 90% replied “Agree” or “Somewhat agree” to PAID-EA item 21. Responses to this item did not differ by gender, age (< vs. >=25) , continuous glucose monitor use (Y/N) , insulin pump use (Y/N) , student status (full time vs. part time vs. no) , income (< vs ≥$75k) , or insurance status (parent vs. own vs. uninsured) . A greater proportion of those with HbA1c ≥ 7% endorsed worry about cost than with HbA1c < 7% (94% vs. 87%, p = 0.008) . Diabetes cost was a major contributor to DD in this sample of EA with T1D. Worry about diabetes costs was endorsed by nearly all participants, especially those not meeting glycemic targets. Managing the cost of diabetes care for EA may be an avenue to reduce DD. Disclosure R.J.Vitale: None. K.Wentzell: None. L.M.Laffel: Advisory Panel; Medtronic, Roche Diabetes Care, Consultant; Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompé, Insulet Corporation, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Novo Nordisk, Provention Bio, Inc. Funding NIH T32DK007260NIH T32DK007529NIH P30DK036836