bluuebunny/crossref_metadata_2025_split huggingface dataset:
916-P: The Demographic Variables Associated with Diabetes Technology Knowledge or Use in Adults with Type 2 Diabetes
Authors: YE YUTING , ACEVEDO-MENDEZ BERNARDO A. , IZARD STEPHANIE , MYERS ALYSON K. 
Published: June 2023

Background: Studies in populations with type 1 diabetes highlight the racial-ethnic disparities in the use of diabetes technology. Our project aims to investigate racial-ethnic and socioeconomic disparities in diabetes technology knowledge and use in adult patients with type 2 diabetes (T2D) in ambulatory setting.
Method: We recruited adults aged 40 and older with T2D who visited one of four internal medicine practices between July 1, 2018 and June 30, 2021. We selected patients in the electronic record who use insulin, have English as a primary language, and have an email address. Eligible participants were invited to participate via an email link to a REDCap questionnaire. All variables were summarized descriptively using frequencies and percentages, and were compared across groups using Pearson’s Chi-Square Test or Fisher’s Exact Test.
Results: We included 116 patients in the analysis, most of whom were white (62%), elderly Medicare recipients. Those who are of racial-ethnic minoritized groups are less likely to have knowledge of CGM (p = 0.013) or insulin pumps (p = 0.001). Patients who have high school education or less have less awareness of insulin pumps (p = 0.041). Interestingly, neither awareness nor use of CGM or insulin pump were found to be associated with income.
Conclusion: This cross-sectional analysis suggests that racial-ethnic minoritized groups or those with lower education have lower knowledge of CGM or insulin pumps and this disparity cannot be explained by differences in socioeconomic status. Providers need to be aware of their potential implicit biases in relation to education and prescription of diabetes technology.

Disclosure
Y.Ye: None. B.A.Acevedo-mendez: None. S.Izard: None. A.K.Myers: Research Support; Neurocrine Biosciences, Inc.
919-P: Assessment of Eating Disorder Risk in Adolescents and Young Adults Starting an On-Body Automated Insulin Delivery (AID) System
Authors: TROJANOWSKI PAIGE J. , ESCOBAR ESTELLA , BERGET CARI , FORLENZA GREGORY P. , O'DONNELL HOLLY K. 
Published: June 2023

Individuals with type 1 diabetes are at higher risk for eating disorders than the general population. Body image satisfaction and disordered eating are infrequently evaluated when starting an insulin pump, even though wearing additional technology may impact body image and/or eating behavior. This pilot study describes the use of the validated Screen for Early Eating Disorder Signs (SEEDS) questionnaire prior to and 3 mo after starting Omnipod 5 (OP5) in a small sample of adolescents and young adults (TABLE 1). Average SEEDS total scores, which indicate eating disorder risk, fell in the low risk category (≤68), with 73% of responders being identified as low risk at both time points. Compared to the SEEDS validation sample, participants were younger (15.1 v 19.2 yrs) and had slightly lower HbA1c’s (8.0 v 8.4) but had similar racial backgrounds and age at diagnosis. The SEEDS demonstrated very good to excellent reliability at both time points. No differences in overall or subscale SEEDS scores were observed between baseline and 3 mo follow-up (p&gt;0.05). These preliminary results suggest that the SEEDS is a viable tool to assess eating disorder risk and body image concerns in adolescents and young adults who are starting a new AID system, such as OP5. Use of this self-report measure could improve detection of individuals at risk for disordered eating.

Disclosure
P.J.Trojanowski: None. E.Escobar: None. C.Berget: Consultant; Insulet Corporation, Dexcom, Inc., Other Relationship; Tandem Diabetes Care, Inc. G.P.Forlenza: Advisory Panel; Medtronic, Consultant; Dexcom, Inc., Insulet Corporation, Tandem Diabetes Care, Inc., Lilly Diabetes, Research Support; Medtronic, Abbott, Dexcom, Inc., Insulet Corporation, Tandem Diabetes Care, Inc. H.K.O'donnell: None.

Funding
National Institute of Diabetes and Digestive and Kidney Diseases (5T32DK063687); JDRF (5-ECR-2019-736-A-N)
930-P: Advanced Hybrid Closed-Loop System Is Associated with Increase in Tighter Glycemic Range—One-Year Observational Study
Authors: RIZZI ALESSANDRO , TARTAGLIONE LINDA , LAURA LEO MARIA , LUCACCINI PAOLI LORENZO , TOSTI GIULIA , POPOLLA VALENTINA , PITOCCO DARIO 
Published: June 2023

Background and Aims: Advanced hybrid closed loop systems (AHCL) are associated with improvement of HbA1c and time in range (TIR). However AHCL give the possibility to gain even tighter glycemic control. Thus, the aim of this study was to evaluate the efficacy of AHCL to increase time spent in tighter glycemic range (TR, 70-140 mg/dl) and to assess any difference between younger and older subjects.
Methods: In an observational retrospective single center study, adults with T1DM using AHCL with predictive integrative derivative (PID) algorithm were enrolled. All participants were recruited at Diabetes Care Unit - Fondazione Policlinico Agostino Gemelli in Rome (IT). Data about TR and standardized metrics have been collected before starting AHCL and 3, 6, 9 and 12 months after AHCL initiation. We compared TR variation over time between younger (age &lt;65 years) and older (≥65 years) subjects. Change in TR over time was evaluated with a linear mixed-effect model including age-group and presence of diabetic complications.
Results: We enrolled 75 subjects with T1DM, age 50.5 (14.2) years [mean (standard deviation)], 35 females (46%), duration of disease 24.7 (13.3) years. 17 subjects (23%) were older and 58 (77%) were younger. 39 (52%) subjects were already using an insulin pump before starting AHCL and 36 (48%) were on multiple daily injections. HbA1c before AHCL was 7.6 (0.98) and 12 months after ACHL was 7.2 (0.6) (p=0.03). TR significantly increased over 12 months in the overall populations (TR before AHCL 37.6% (15.3) vs TR 12 months 52.9 % (12.8), p&lt;0.001). Age or presence of complications did not affect the improvement of TR (p=0.38). TR 50% corresponded to mean TIR 76.2%
Conclusions: AHCL is associated with significant improvement in tighter glycemic control. This improvement is not different between younger and older subjects. AHCL is an effective and safe system to aim to strict metabolic control in all subjects with T1DM.

Disclosure
A.Rizzi: None. L.Tartaglione: None. M.Leo: None. L.Lucaccini paoli: None. G.Tosti: None. V.Popolla: None. D.Pitocco: None.
931-P: Use of a Continuous Glucose Monitor System (CGM) in Latinx Patients with Type 2 Diabetes (DM2) Improves A1C and CGM Metrics—Real-Life Experience in a Latinx Diabetes Clinic
Authors: THATTE ARITA , WRIGHT LORENA A. 
Published: June 2023

Objective: There have been few studies of CGM benefits in the Latinx population with DM2, an ethnic group disproportionately affected. We hypothesized that in this population, the use of CGM results in a greater % decrease of A1c than in those without; and that in CGM users, mean glucose, time in range (TIR), below range (TBR) and coefficient of variation (CV) also improves in a 1-year period.
Methods: Review of electronic records included Spanish speaking Latinx DM2 patients, age 31-78, baseline A1c ≥8.0 ≤13.0%, on insulin. We included age, gender, BMI, baseline insulin regimen: basal, bolus or both, and A1c at the time CGM was offered ±4 months and post 12-months±4 months. Linear regression was used to calculate % change in A1c. CGM metrics were recorded at the same timepoints and analyzed using T-tests.
Results: CGM users: n=30, age 54.3±13.2, 67% female, BMI 34.4±7.9, 20% were on basal (29% at 12 months), 3% on bolus insulin (0% at 12 months) and 77% on both (67% at 12 months) and 4% on no insulin at 12 months, baseline A1c was 8.8% ±1.6 and 8.1±1.3 at 12 months, p=0.02. Mean % decrease in A1c in 1 year 5.1%±12.8. Baseline mean glucose was 202mg/dl±58 and 173±35 at 12 months, p= 0.001. TIR went from 47 to 60%, p= 0.003, TBR and CV did not change. Non-CGM users: n=27, age 52.9±12.1, 56% male, BMI 35.2 ±9.4, 30% were on basal (19% at 12 months), 4% on bolus insulin (0% at 12 months) and 67% on both (81% at 12 months), baseline A1c was 9.0%±1.6 and 8.5± 1.6 at 12 months, p=0.06. Mean % decrease in A1c in 1 year 4.7±13.1. There was no difference in % change in A1c between CGM vs non-CGM groups, p=.34.
Discussion: Both groups had improvements in A1c from baseline, but significant only in CGM users. The data support that adoption of CGM in Spanish speaking Latinx patients with DM2 on insulin results in better glycemic control, based on improved mean glucose and TIR, without an increase in hypoglycemia: TBR and CV; furthermore, this technology was well received by patients.

Disclosure
A.Thatte: None. L.A.Wright: None.
934-P: Effectiveness of a Digital, Personalized Lifestyle Program in People with Diabetes in Improving Glycemic Variability and Time in Range—An Urban Indian Real-World Study
Authors: SOORAGONDA BASAVARAJ , FATEMA ZAREEN , M MAHESH D. 
Published: June 2023

Background: Glycemic variability (GV) and Time in range (TIR) are evolving parameters helping people with diabetes (PwD) have better outcomes. The OneCare diabetes program offers CGM-monitored, digital personalized education through CDEs as health coaches and OneCare app for tracking patient’s behaviour.
Methods: In a 3-month prospective study, enrolled PwD (n=31) were equipped with 14 days of CGM (Abbott freestyle) at the beginning and end of OneCare program. Using 96 daily glucose readings from each patient’s CGM, GV values were obtained from days 2 to 4, of the first sensor (CGM1), and days 12 to 14, of the second sensor (CGM2) ending at day 90. GV was calculated using EasyGV© software. Demographics, HbA1c and glycemic parameters were captured at time points. The health coach guided the progress through weekly calls.
Results: 62 evaluable CGM tracings, were included in the study. At 90-day follow-up, HbA1c [%] had decreased by 1.9 from 8.7 (1.2) to 6.8 (0.8), weight [kg] decreased from 74.1 (12.2) to 70.6 (10.5), FPG [mg/dl] from 148.13 (55.5) to 107.5 (20). There were significant improvements seen between the CGM1 vs CGM2 of the GV metrics including %Coefficient Variation {28.52% (8.5); 25.85% (8.2); p=0.02}, Mean Average Glucose [mg/dL] {80.9 (34.4); 62.65 (32.6); (p=&lt;.001)}, Standard deviation of blood glucose {38.76 (14.59); 32.78 (11.2); (p = .01)} and MAGE {97.78 (31.9); 85.86 (28.68) (mg/dl); (p= .04)}. Significant improvements in TIR (%) were seen on follow up {54.4 (21.8); 67.4 (20.9)}. Percentage of people achieving the target TIR (&gt;70%) increased significantly from 25.8% to 54.8% (p&lt;0.001). On follow-up, 60%(n=20) patients required lesser medication for diabetes control.
Conclusion: PwD who participated in OneCare's CGM-assisted DSME program had definite improvements in GV, TIR along with other metabolic parameters. The results encourage a larger prospective study to validate the findings.

Disclosure
B.Sooragonda: None. Z.Fatema: Employee; Wellwork Technologies Private Limited, India. M.D.M: None.
944-P: Continuous Glucose Monitoring (CGM) Sampling Duration to Estimate Long-Term Glycemic Control in Adults with T2D Not Using Insulin
Authors: BACON SAM , THOMPSON NELS , FERRELL DAVID , FUNG JASON 
Published: June 2023

Objective: Current consensus is that 10-14 days of continuous glucose monitoring (CGM) sampling time is adequate to assess long-term glycemic control in T1D and insulin-using T2D populations. Optimal CGM sampling duration has not been widely studied in people with T2D not using insulin. We studied the relationship between true and estimated long-term (90-day) glycemic control in people with T2D not using insulin.
Methods: The study population (N = 829) was composed of adults with T2D enrolled in Level2, a virtual specialty clinic, with CGM data on 75% (68) of the 90 days preceding an A1c lab result and no insulin fills during this period. The mean age and A1c were 56 years and 6.7% respectively. We computed the median absolute percentage error (MAPE) and Pearson correlations (R) between glycemic metrics from sampling periods of increasing duration and the full 90-day period. Because this population was at low risk for hypoglycemia glucose management indicator (GMI) and time above range (&gt;180 mg/dL, TAR) were the primary outcomes of interest. We also assessed the correlations between GMI and A1c.
Results: GMI and TAR from 14-day measurements were highly correlated (R = 0.92) with 90-day values, increasing to R = 0.94 with 30-day measurements. Correlations of GMI and A1c were high with 14 and 30 days (R = 0.79, R = 0.82) but did not exceed R = 0.85 with longer sampling periods. MAPE was 2.2 (SD = 2.6) and 1.5 (SD = 2.1) for GMI with 14- and 30-day measurements, respectively, and 29.2 (SD = 47.4) and 21.2 (SD = 27.1) for TAR.
Conclusion: In the T2D population not using insulin, 14 days of CGM data is sufficient to estimate long-term mean glucose and the discordance with A1c is consistent with previous studies of people with T1D and insulin-using T2D. TAR is subject to greater error than in previous studies of people with T1D and insulin-using T2D and more work is needed to understand this discrepancy.

Disclosure
S.Bacon: Employee; Optum Labs, Research Support; Level2. N.Thompson: Employee; Level2, Stock/Shareholder; UnitedHealth Group. D.Ferrell: Stock/Shareholder; Level2, Medexpress Urgent Care. J.Fung: Employee; Level2.
947-P: Glycemic Control Utilizing Continuous Glucose Monitoring vs. Point-of-Care Testing in Older Adults with Type 2 Diabetes in Long-Term Care Facilities
Authors: IDREES THAER , CASTRO-REVOREDO IRIS A. , GAVALLER MONICA D. , OH HYUNGSEOK , ZABALA ZOHYRA , MORENO EMMELIN M. , MOAZZAMI BOBAK , GALINDO RODOLFO J. , CABB ELENA , JOHNSON THEODORE M. , PENG LIMIN , UMPIERREZ GUILLERMO 
Published: June 2023

We compared the efficacy of continuous glucose monitoring (CGM) and point of care (POC) testing (standard of care) in assessing glycemic control in older adults with T2D treated with either basal insulin or insulin secretagogues plus sliding scale in long-term care facilities (LTCF). All 97 subjects underwent POC testing before meals and bedtime and wore a Dexcom CGM. Treatment adjustment was performed by the primary care team, with a target glucose of 140-180 mg/dL, and for a duration of intervention up to 60 days. Study endpoints included differences in hypoglycemia &lt; 70 and 54 mg/dL and hyperglycemia &gt; 180 and 250 mg/dL by POC and CGM. Participants baseline characteristics (age: 74.7±11 years, BMI: 29.6±7.9, HbA1c: 8.06±2.2%) admitted to skilled nursing care/subacute rehab (80%) or long-term care (20%) facilities with a median length of participation of 17 (interquartile range 11, 29) days. The mean daily glucose by POC was lower than CGM (171±45 vs. 188±45 mg/dL, p&lt;0.01). CGM detected significant greater proportions of subjects with hypoglycemia &lt;70 mg/dL (40% vs. 14%) and &lt;54 mg/dL (21% vs. 1.0%); as well as hyperglycemia &gt;250 mg/dL (77% vs. 56%) compared to POC testing, all p&lt;0.001. Conclusion: In older adults with T2D admitted to long-term care facilities, the use of CGM significantly improved detection of hypoglycemic and hyperglycemic events compared to POC.

Disclosure
T.Idrees: None. T.M.Johnson: Consultant; Astellas Pharma Inc., Research Support; Dexcom, Inc. L.Peng: None. G.Umpierrez: Research Support; Abbott, Dexcom, Inc., Baxter. I.A.Castro-revoredo: None. M.D.Gavaller: None. H.Oh: None. Z.Zabala: None. E.M.Moreno: None. B.Moazzami: None. R.J.Galindo: Consultant; Novo Nordisk, Eli Lilly and Company, Sanofi, Pfizer Inc., Bayer Inc., WW (Weight Watchers), Research Support; Novo Nordisk, Eli Lilly and Company, Dexcom, Inc. E.Cabb: None.

Funding
Dexcom, Inc. (IIS-2020-119_6X)
951-P: Intermittently Scanned Continuous Glucose Monitoring (isCGM) for T1DM—Subgroup Analysis from the FLASH-UK Study
Authors: LEELARATHNA LALANTHA , SUTTON CHRIS J. , EVANS MARK , NEUPANE SANKALPA , RAYMAN GERRY , LUMLEY SARAH , CRANSTON IAIN C. , NARENDRAN PARTH , BARNARD KATHARINE , TAXIARCHI VICKY P. , BURNS MATTHEW , CAMM MAISIE E. , THABIT HOOD , WILMOT EMMA G. , BEHALF OF THE FLASH-UK TRIAL STUDY GROUP ON 
Published: June 2023

The recently published1, multi-site, FLASH-UK, randomized controlled trial (n=156, males 56%, Baseline HbA1c 71±9 mmol/mol, age 44±15) showed improved HbA1c and sensor-based metrics in adults with type 1 DM and an HbA1c ≥58 mmol/mol. Here we present results from pre-specified subgroup analysis for HbA1c (Table 1) and “Time in range (TIR)” (Table 2).
The effect of isCGM on both HbA1c and TIR did not differ significantly across subgroups for baseline HbA1c category, treatment modality, prior structured education, sex, deprivation status or depression category. The effect of isCGM on HbA1c was larger for younger people. Those with at least a bachelor’s degree had greater TIR improvement.
Conclusion: isCGM is effective across a range of clinical and demographic factors.
1N Engl J Med. 2022 Oct 20;387(16):1477-1487

Disclosure
L.Leelarathna: Advisory Panel; Abbott Diabetes, Medtronic, Insulet Corporation, Sanofi, Research Support; Abbott Diabetes, Novo Nordisk, Speaker's Bureau; Sanofi, Abbott Diabetes. V.P.Taxiarchi: None. M.Burns: None. M.E.Camm: None. H.Thabit: Advisory Panel; Dexcom, Inc., Roche Diabetes Care, Research Support; Dexcom, Inc., Speaker's Bureau; Eli Lilly and Company. E.G.Wilmot: Advisory Panel; Abbott Diabetes, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk, Sanofi, Roche Diabetes Care, Embecta, Consultant; Springer Healthcare, Research Support; Abbott Diabetes, Diabetes UK, Insulet Corporation, Novo Nordisk, NIH - National Institutes of Health, Speaker's Bureau; Abbott Diabetes, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk, Sanofi, Ypsomed AG, Glooko, Inc. On behalf of the flash-uk trial study group: n/a. C.J.Sutton: None. M.Evans: Advisory Panel; Zucara Therapeutics, Pila Pharma, Dexcom, Inc., Other Relationship; Novo Nordisk, AstraZeneca, Abbott Diabetes, Speaker's Bureau; Eli Lilly and Company. S.Neupane: Advisory Panel; Quin, Abbott Diabetes, Roche Diabetes Care, Insulet Corporation, Other Relationship; Abbott Diabetes. G.Rayman: Other Relationship; Diabetes UK, Novo Nordisk, Research Support; Abbott Diabetes, Speaker's Bureau; Abbott Diabetes, Lilly Diabetes, Sanofi. S.Lumley: None. I.C.Cranston: Research Support; Eli Lilly and Company, Speaker's Bureau; Abbott Diabetes, AstraZeneca, Bristol-Myers Squibb Company, Eli Lilly and Company, Insulet Corporation, Novo Nordisk, Sanofi, Viatris Inc. P.Narendran: Advisory Panel; Omnipod, Speaker's Bureau; Abbott Diabetes, Lilly Diabetes. K.Barnard: Advisory Panel; Abbott Diabetes, Roche Diabetes Care, Sanofi, Consultant; LifeScan Diabetes Institute, Tandem Diabetes Care, Inc., Research Support; Novo Nordisk.

Funding
Diabetes UK (18/0005836)
956-P: Association between Glycemia Risk Index (GRI) and Diabetic Retinopathy in Type 2 Diabetes—A Prospective Cohort Study
Authors: WANG YAXIN , LU JINGYI , NI JIAYING , WANG MING , SHEN YUN , LU WEI , ZHU WEI , BAO YUQIAN , RODBARD DAVID , VIGERSKY ROBERT A. , JIA WEIPING , ZHOU JIAN 
Published: June 2023

Background: The glycemia risk index (GRI) is a new composite metric for assessing the quality of glycemia based on expert ranking by 330 clinicians of 14-day continuous glucose monitoring (CGM) tracings. Compared with time in range (TIR), GRI has been shown to correlate more closely with the clinicians’ opinions as to the overall quality of glycemia profiles. However, the relationship between GRI and diabetes-related outcomes remains unknown. We aimed to investigate the association between GRI and incident diabetic retinopathy (DR).
Methods: A total of 1,204 adult type 2 diabetes without DR at baseline were included between 2005-2019 from a single center in Shanghai, China. GRI was obtained from 3-day CGM data at baseline. Cox proportional hazards regression models were used to estimate the association between GRI and incident DR.
Results: During a median follow-up of 8.4 years, 301 patients developed DR. The multivariable-adjusted (age, sex, current smoking status, diabetes duration, BMI, systolic BP, TG, HDL-C, and LDL-C) hazard ratios (HRs) for incident DR across ascending GRI quartiles (≤14 [reference], 15~28, 29~47 and &gt;47) were 1.00, 1.05 (95% CI 0.74-1.48), 1.33 (95% CI 0.96-1.84) and 1.53 (95% CI 1.11-2.11), respectively. For per 1-SD increase in GRI, the risk of DR was increased by 20% (HR=1.20, 95% CI 1.07-1.33) after adjustment for confounders. With respect to TIR, per 1-SD decrease was associated with a 23% (HR=1.23, 95% CI 1.10-1.37) increased risk of DR. There was no statistically significant difference in risk discrimination for incident DR when using GRI and TIR, as measured by C statistic, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) (all P&gt;0.05), after adjustment for confounders.
Conclusion: In patients with type 2 diabetes, higher GRI is associated with an increased risk of incident DR, with a predictive value comparable to TIR. The potential value of GRI needs to be explored in future studies.

Disclosure
Y.Wang: None. R.A.Vigersky: Employee; Medtronic. W.Jia: None. J.Zhou: None. J.Lu: None. J.Ni: None. M.Wang: None. Y.Shen: None. W.Lu: None. W.Zhu: None. Y.Bao: None. D.Rodbard: Consultant; Lilly Diabetes.
960-P: Hemodialysis-Related Glycemic Patterns among People with Insulin-Treated Type 2 (T2D) Diabetes—Role of Continuous Glucose Monitoring (CGM)
Authors: GALINDO RODOLFO J. , MOAZZAMI BOBAK , GERGES AMANY Y.G. , PENG LIMIN , TUTTLE KATHERINE R. , UMPIERREZ GUILLERMO 
Published: June 2023

Background: Hemodialysis (HD) impacts glucose and insulin metabolism and increases hypoglycaemia rates. Glucose-containing dialysate decreases the risk, but studies using CGM metrics are lacking.
Methods: Prospective observational study of insulin-treated adults with T2D, receiving hemodialysis (dialysate glucose 100mg/dl), at least thrice weekly. Subjects were instructed to wear a Dexcom G6-Pro for 10 days. We assessed CGM metrics (mean glucose, %TIR, %TAR, %TBR, and hypoglycemic and hyperglycemic rates) during three time periods: 20-hours before (PreHD), during (HD, ~4 hours), and 20-hours after (PostHD) hemodialysis sessions.
Results: Among 56 subjects (mean age 57.3±9, HbA1c 7.2±1.4), mean glucose, %TAR, %TIR and rates of hypoglycaemia &lt;70mg/dl were significantly better during HD. %TAR &gt;180mg/dl and &gt; 250mg/dl were significantly higher after HD, see Table 1. Other hypoglycaemia metrics were overall low, and not different in relation to HD timing.
Conclusion: CGM patterns demonstrated improved glycemic control during dialysis, with tendency for higher glucose metrics before HD. Hypoglycaemia metrics were low, while severe hyperglycemia excursions are common across all HD-related periods. Future studies using newer CGM technology and providing longer duration of CGM monitoring are needed for subjects with T2D treated by HD.

Disclosure
R.J.Galindo: Consultant; Novo Nordisk, Eli Lilly and Company, Sanofi, Pfizer Inc., Bayer Inc., WW (Weight Watchers), Research Support; Novo Nordisk, Eli Lilly and Company, Dexcom, Inc. B.Moazzami: None. A.Y.G.Gerges: None. L.Peng: None. K.R.Tuttle: Consultant; Lilly, AstraZeneca, Gilead Sciences, Inc., Research Support; Bayer Inc., Boehringer Ingelheim (Canada) Ltd., Novo Nordisk, Goldfinch Bio, Inc., Traveere Pharmaceuticals. G.Umpierrez: Research Support; Abbott, Dexcom, Inc., Baxter.