bluuebunny/crossref_metadata_2025_split huggingface dataset:
664-P: Success of Interactive, Online Education Related to Interpretation and Application of AGP Data
Authors: LARKIN AMY , LACOUTURE MICHAEL , LE ANNE 
Published: May 2022

Objective: We sought to determine if interactive, case-based, online continuing medical education (CME) could improve the competence and confidence of diabetologists/endocrinologists (D/Es) and primary care physicians (PCPs) related to interpreting and applying ambulatory glucose profile (AGP) data to patient management regimens for T2D.
Methods: Educational design included a “test, then teach” approach to elicit cognitive dissonance, with evidence-based feedback provided following each learner response. A repeated pairs pre-/post-assessment study design and chi-square test (P &lt;.is considered significant) assessed educational effect, with Cramer’s V being used to assess educational impact (0.06-0.15 is a noticeable effect, 0.16-0.26 considerable, and &gt;0.26 extensive) . The activity launched May 11, 2021 and data were collected through August 12, 2021.
Results: In total, 94 D/Es and 576 PCPs were included in the analysis. Matched learner data indicate that overall, 29% D/Es learners’ responses and 36% of PCPs learners’ responses improved from pre-to-post (both P&lt;.with extensive overall impacts 0.267-0.293) . On a question-level: 34% of D/Es (P&lt;.01, V=.343) and 46% of PCPs (P&lt;.01, V=.402) improved at selecting the medication adjustment most appropriate based on a patient’s AGP data. 24% of D/Es (P&lt;.01, V=.19) and 26% of PCPs (P&lt;.01, V=.183) improved at currently interpreting the AGP. Overall, 23% of D/Es and 37% of PCPs reported increased confidence in iCGM in patients with T2D.
Conclusion: This study demonstrates the success of interactive, case-based, online CME on improving competence and confidence of D/Es and PCPs related to interpretation and application of AGP data. Case-based education with interactive polling questions and detailed explanations related to best choices should be employed more often to help clinicians apply knowledge/data into practice to improve patient management and care.

Disclosure
A.Larkin: None. M.Lacouture: None. A.Le: None.

Funding
Developed through an independent educational grant from Abbott Diabetes Care
676-P: Difference in CGM Estimated Hemoglobin A1c in Adults with Type 1 and Type 2 Diabetes
Authors: SALAM MAAMOUN , BAILEY RYAN , CALHOUN PETER , MCGILL JANET B. , BECK ROY , PRICE DAVID A. 
Published: May 2022

The relationship between mean glucose measured using a continuous glucose monitor (CGM) and hemoglobin A1c (A1C) was evaluated in adults with type 1 diabetes (T1D) or type 2 diabetes (T2D) . Data from participants enrolled in the MOBILE, DIAMOND, and WISDM trials and randomized to the CGM arm were used in the analysis. Follow-up visits collected A1C measured by a central laboratory at 8 months post-randomization in the MOBILE study and 6 months post-randomization in DIAMOND and WISDM studies. CGM data collected in the 91 days prior to the follow-up visit, when glucose control was thought to be relatively stable, was used to compute mean glucose. A least squares linear regression model estimated A1C using mean glucose as a predictor, and models were fit separately by diabetes type. 199 participants with T1D and 175 participants with T2D were included in the analysis. Mean age was 57±15 years among those with T1D and 58±years among those with T2D. Estimated A1C was similar but slightly higher for participants with T2D vs. T1D for the same mean glucose (Table) . Analyses restricting to White non-Hispanic cohort yielded similar results. Spearman partial correlation coefficients for mean glucose vs. A1C were 0.76 for T1D and 0.84 for T2D. Estimates of A1C based on CGM measured mean glucose were slightly higher for those with T2D compared with T1D.

Disclosure
M.Salam: Advisory Panel; Lilly Diabetes, Consultant; Neurocrine Biosciences, Inc., Research Support; Mylan N.V., Neurocrine Biosciences, Inc. R.Bailey: None. P.Calhoun: None. J.B.Mcgill: Advisory Panel; Gilead Sciences, Inc., Lilly Diabetes, MannKind Corporation, Novo Nordisk A/S, Provention Bio, Inc., Salix Pharmaceuticals, Consultant; Bayer AG, Boehringer Ingelheim International GmbH, Research Support; Dexcom, Inc., Novo Nordisk. R.Beck: Consultant; Diasome, Eli Lilly and Company, Insulet Corporation, Novo Nordisk, Research Support; Ascensia Diabetes Care, Beta Bionics, Inc., Bigfoot Biomedical, Inc., Dexcom, Inc., Eli Lilly and Company, Medtronic, Novo Nordisk, Roche Diabetes Care, Tandem Diabetes Care, Inc. D.A.Price: Employee; Dexcom, Inc.
684-P: Tracking Type 2 Diabetes Progression Using CGM Systems
Authors: SCHIAVON MICHELE , DALLA MAN CHIARA 
Published: May 2022

Disposition index (DI) is an index quantifying the quality of glucose control, usable to track disease progression. It is usually calculated as the product of beta-cell function and insulin sensitivity, assessed, in hospitalized setting, either from clamp data, surrogate indices or model-based methods, like the Oral Minimal Model (OMM) . The increasing use of continuous glucose monitoring (CGM) systems, even in individuals with type 2 diabetes (T2D) , opens the door to the use of such devices to monitor glucose control in outpatients. Here, we propose a method to assess DI from CGM data, validated it against OMM and proved its usability to track disease progression. We studied 100 early stage (ES) and 100 advanced stage (AS) subjects with T2D of the Padova T2D simulator, matched for age (54 [42,75] y) and different BMI (33 [29,37] vs. 31 [28,34] kg/m2; p=0.016) , which underwent a mixed meal challenge (75g of carbohydrates) while wearing CGM.
Plasma glucose, insulin and C-peptide concentrations were measured for 6 hours after the meal and used for the estimation of the DI with the OMM (DIMM) , while CGM sensor data were used to calculate DI with the sensor-based method (DISB) .
DISB well correlated with DIMM (ρES = 0.81 and ρAS = 0.77; p&lt;0.001) and both were significantly lower in AD than ES (p&lt;0.001, Fig. 1) .
We conclude that DISB is usable to assess DI in subjects with different stage of T2D wearing CGM and thus, potentially, to track disease progression in noninvasive way.

Disclosure
M.Schiavon: None. C.Dalla man: Research Support; Becton, Dickinson and Company, Sanofi-Aventis Deutschland GmbH.

Funding
MIUR (Italian Minister for Education) under the initiative "Departments of Excellence" (Law 232/2016)
687-P: Changes in HbA1c after Initiating Real-Time Continuous Glucose Monitoring (rtCGM) for Primary Care Patients with Type 2 Diabetes
Authors: SHIELDS STEPHEN , NORMAN GREGORY J. , CIEMINS ELIZABETH L. 
Published: May 2022

Background: Many patients with type 2 diabetes (T2D) have suboptimal control and are not meeting their glycemic targets. Use of CGM devices has increased substantially for patients with T2D. However, the effects of rtCGM on glycemia in T2D primary care patients, particularly those not on intensive insulin therapy, in real world settings has not been well studied.
Materials and Methods: This retrospective observational study examined data from 13 U.S. health systems and multispecialty medical groups. Personal rtCGM use was determined from prescription codes. The cohort included patients with a diagnosis for T2D and ≥1 outpatient visit with a primary care provider (PCP) in the 18 months prior to rtCGM use. The outcome was change in hemoglobin A1c (A1c) from baseline to 3-9 months after rtCGM initiation. The cohort was stratified into two groups based on baseline A1c (A1c &gt;7.5 and A1c ≤7.5) .
Results: Between August 1, 2015, and September 30, 2020, 458 T2D patients initiated rtCGM (mean age 61, 50% female, 84% white, 50% commercial insurance, and a mean of 3.7 PCP visits in the prior year) . Of the 458 patients, 64 (14%) were prescribed antidiabetes drugs but not insulin (NIT) , 51 (11%) were prescribed basal but not bolus insulin (NIIT) , and 343 (75%) were prescribed bolus insulin, with or without basal insulin (IIT) . Univariate analysis of change in A1c showed for those with a baseline A1c &gt;7.5 (n=306, 67%) , A1c changed an average of -0.9% (95% CI -0.7, -1.1, p&lt;.001) and varied by diabetes management regimen: NIT -1.13% (SD=2.3%) , p&lt;.01; NIIT -1.59% (SD=2.3%) , p&lt;.001; IIT -0.76% (SD=1.6%) , p&lt;.001. For those with a baseline A1c ≤7.5 (n = 152, 33%) , change in A1c was not statistically significant (0.12%, p=.123) .
Conclusions: These findings suggest, for poorly controlled patients with T2D, regardless of therapy regimen, rtCGM use improved glycemic control. This real-world evidence supports further studies of the benefits of rtCGM in the broader T2D population.

Disclosure
S.Shields: None. G.J.Norman: Employee; Dexcom, Inc. E.L.Ciemins: None.
690-P: Deterioration in Glycemic Control on School Days among School-Aged Children with Type 1 Diabetes: A Continuous Glucose Monitoring–Based Study
Authors: WU XIUMEI , ZHANG WEN HAO , DING YU , ZHENG XUEYING , WENG JIANPING , LUO SIHUI 
Published: May 2022

Background: Children with type 1 diabetes (T1D) spend more time in school when they turn school age. The impact of such transition on glycemic control remains unclear. We aimed to investigate the impact of school life by comparing the glycemic control between holidays and schooldays in school-aged children with T1D.
Methods: This observational study collected data from school aged T1D children with continuous glucose monitoring (CGM) data from September 20to July 2021. Eligible datasets should include CGM records for at least 3 schooldays and 3 holidays. Data providers’ demographic and lifestyle-related information were collected via questionnaires. We compared the CGM metrics between schooldays and holidays using paired T-test.
Results: A total of 78 school aged children with T1D were included (40 boys, median age 9.75 years, median diabetes duration 2.20 years) . 142,945 hours of CGM data were analyzed. Overall, time in range (3.9-7.8 mmol/L, TIR) was better on holidays than that during schooldays [57.0% (SD 15.0%) vs. 55.9% (SD 15.1%) , p = 0.039] and time above range (&gt;7.8mmol/L, TAR) was lower on holidays [35.8% (SD 15.5%) vs. 36.9% (SD 15.5%) , p = 0.085]. No significant difference was observed in time spent &lt;3.9mmol/L or numbers of hypoglycemia events per week. Nocturnal glycemic deterioration could be attributed to a significantly longer nighttime (0am to 6am) TIR [60.4% (SD 17.1%) vs. 56.9% (SD 18.1%) , p = 0.001] and a shorter nighttime TAR [31.8% (SD 17.5%) vs. 35.6% (SD 18.5%) , p = 0.001] on holidays compared with those on schooldays, with no difference in daytime metrics. Stratified analysis revealed the nocturnal difference was more prone to children aged 6 to years, girls, and insulin pump users, while bedtime and midnight snacks had no impact.
Conclusion: Among school-aged children with T1D, deterioration in nocturnal glycemic control was found in schooldays and active adjustment in treatment is needed to improve schooldays glycemia.

Disclosure
X.Wu: None. W.Zhang: None. Y.Ding: None. X.Zheng: None. J.Weng: None. S.Luo: None.
696-P: Increasing CGM Use through Standardized Documentation
Authors: DELACEY SEAN E. , SULLIVAN NAOMI J. , FOGEL NAOMI R. 
Published: May 2022

Continuous glucose monitor (CGM) use is known to improve glycemic outcomes for patients with Type 1 Diabetes, but uptake is not universal in the pediatric population. We hypothesized that requiring standardized documentation of CGM use and identification of barriers would increase awareness and identify potential targets for future interventions, ultimately increasing CGM use in our population. We designed standard documentation within the electronic medical record for outpatient visits to assess CGM use and barriers to use. The documentation collects data on CGM possession, %time in use, prescriptions, and barriers to use in patients with Type 1 Diabetes. Our intervention involved integrating the standard CGM documentation into diabetes note template thus automating completion by providers. Data was pulled from clinic days two weeks prior to intervention (100 patients) and another days, two months after intervention (74 patients) . Before intervention 83% of patients had a CGM compared to 87% of patients after intervention (p=0.51) . While 63% used a CGM &gt;70% of the time before intervention, 73% of patients had &gt;70% use post intervention (p=0.19) . Provider documentation was not universal with 12% and 4% of encounters with no documentation of time in use before and after intervention respectively. After standardization 7/patients without a CGM were prescribed one during the visit compared to 5/17 of patients prior. Barriers identified included (n) : insurance coverage (4) , skin adhesion/issues (3) , self-image (2) , lack of education /distrust (1) , technological issues (1) , resistance to wearables (1) , and other (3) . Our patient population had a high rate of CGM use. Two months after the intervention, both use of CGM and new prescriptions increased. The improvement may be related to increased awareness and addressal of CGM barriers among providers. The intervention provided insight on barriers to CGM use, such as skin/adhesion issues, that will be targeted for future improvement.

Disclosure
S.E.Delacey: None. N.J.Sullivan: None. N.R.Fogel: None.

Funding
National Institute of Diabetes and Digestive and Kidney Diseases Ruth L. Kirschstein National Research Service Award T32 DK007169 and T1D Exchange
704-P: Time in Range and Time Below Range in Insulin-Treated Older Adults with Type 2 Diabetes
Authors: LEITE SILMARA A.O. , SILVA MICHAEL , LAVALLE ANA C.R. , BASTOS MURILO , BERTOGY MARIA C. , VIEIRA SUELEN C. , UMPIERREZ GUILLERMO E. 
Published: May 2022

Hypoglycemia is the key limiting step for optimizing glycemic control in older adults. Continuous glucose monitoring (CGM) technology has not been well-evaluated in insulin treated older patients with type 2 diabetes (T2D) .
Methods: This prospective observational cohort study assessed of glycemic control using the FreeStyle Libre Flash CGM in insulin treated older adult patients with T2D. Subjects &gt;65 years with T2DM on insulin therapy and HbA1c between 7% and 9%, with or without oral agents, were identified from a public hospital and a private diabetes clinic and invited by phone to participate (n= 462) . Patients treated with GLP1 agonists; eGFR &lt;30 ml/min; Hb &lt;11g/dL; ALT&gt; 3x ULN; glucocorticoid use in the previous 3 months, and active malignancy were excluded. Participants worn the CGM continuously during a 6-weeks study period. They returned to clinic every 2 weeks for CGM data downloaded and new CGM placement, assessment of glycemic control and hypoglycemia. The investigators adjusted insulin treatment at each visit as needed. The first 2 weeks of CGM was considered baseline point and the last 2 weeks was the endpoint. The differences on time in range (TIR 70-180, mg/dl) and time below range (TBR, &lt; 70 mg/dl) was tested using the Wilcoxon Signed-rank test with p &lt;0.05.
Results: A total of 125 patients were randomized and 49 patients completed the 6 weeks follow-up (women=53.9%; age=72.8 ± 5.0 years; BMI=28.3±3.6 Kg/m2; eGFR=62.4 ± 16.6; ml/min A1c=8.0 ± 0.57%; GMI=7.1 ± 0.8%. The patients had a median TIR of 65% (min= 7%, max= 94%) at the baseline and 68% (min= 4%; max= 97%) at the endpoint. The median TBR was 3% (min= 0%, max= 23%) at the baseline and 2% (min= 0%; max= 18%) at the end of study. The TBR was significantly reduced after 6 weeks of CGM (p&lt;0.01) .
Conclusions: An individualized approach may be possible using FreeStyle Libre Flash CGM to avoid overtreatment and undertreatment of older adults with T2D. CGM is a useful tool to reduce hypoglycemia in insulin older adults with T2D.

Disclosure
S.A.O.Leite: None. M.Silva: None. A.C.R.Lavalle: None. M.Bastos: None. M.C.Bertogy: None. S.C.Vieira: None. G.E.Umpierrez: Research Support; AstraZeneca, Dexcom, Inc., Novo Nordisk.

Funding
Abbott DiabetesCare (ADC-OUS-IIS-19-47)
708-P: Hypertension Control among People with Diabetes Using a Self-Management Multicondition Digital Platform
Authors: HERSHCOVITZ YIFAT , TAMIR MICHAL , MANEJWALA OMAR 
Published: May 2022

Introduction: Digital multicondition platforms seek to assist persons with diabetes in management of their diabetes and comorbidities. Hypertension is reported in over two-thirds of patients with type 2 diabetes. Both are major risk factors for cardiac, stroke, and kidney disorders. Dario’s digital therapeutics platform for chronic conditions supports self-management of diabetes and high blood pressure. The platform enables digital evaluation of blood glucose and blood pressure levels in real time and supports interventions based on clinical indicators.
Method: A retrospective data evaluation was performed on the Dario data base since 2019. A population of active users who started with hypertension stage 1 as baseline was identified. Blood glucose and blood pressure readings were assessed at first month and 6th month of use. A subgroup of users who started at hypertension stage 2 was evaluated as well. Systolic, diastolic pressures and average blood glucose were evaluated along of the study.
Results: For the 2554 users identified with diabetes and hypertension, more than two thirds improved their systolic blood pressure by 13 mmHg (P&lt;0.001; 144±14 to 131±13) . A group of 38.7% (N=990) moved to a lower hypertensive stage (P&lt;0.001) . The subset of 1367 users with stage 2 hypertension improved their systolic blood pressure from 150±12.4 to 141±15.2 mmHg on average and 43.9% (N=600) improved their blood pressure by more than mmHg over six months (P&lt;0.001) . A subgroup of 3users who started at high-risk blood glucose levels significantly reduced their blood glucose average by 15% over 6 months (232.4±46 to 198±65 mg/dL) (P&lt;0.001) .
Conclusion: A multicondition digital therapeutic platform may promote behavioral modifications and result in sustainable improvements in both glycemic control and blood pressure levels. The study demonstrates an improvement in multiple chronic conditions (diabetes and Hypertension) for people using one digital platform.

Disclosure
Y.Hershcovitz: None. M.Tamir: None. O.Manejwala: Employee; DarioHealth Corp., Stock/Shareholder; DarioHealth Corp.
712-P: Suhoor Timing in T1DM Patients Fasting during Ramadan: A Randomized Crossover Trial
Authors: ALAMOUDI REEM , ALASSIRI MISHARY A. , ALJAWHRJI ABDULRHMAN , ALMAGHRABI MAZIN M. , BASULAYMAN DALIA S. , RAMADAN MAJED 
Published: May 2022

IDF-DaR guidelines recommend late Suhoor (pre-dawn meal) , this does not give much time for correction and can lead to breaking the fast in the early hours.
Objective: To estimate Hypoglycemia risk in T1D fasting Ramadan when eating Suhoor 90-120 minutes before dawn versus 30 minutes before dawn.
Methods: Prospective randomized cross-over design. T1D insisting to fast recruited. Data collected using pre/post-Ramadan questionnaires, and FCGM - Freestyle Libre.
Results: 44 T1D patients randomized to early vs. late Suhoor regimens for a week then crossed to the other regimen the second week. 42 MDI and 2 CSII. Mean age 25 ±5.9 years (range 15-39) , DM duration 13.7 ±6.6 years, 73.5% female. Pre-Ramadan A1c ≤7 30.2%, and &gt;9 20.9%. (22.7%) reported frequent hypoglycemia (≥3/week) , and 4 (9.1%) reported hypoglycemia unawareness.
During the early vs. late regimen self-reported hypoglycemia leading to breaking of fast 64.5% vs. 58.1%, p=0.18; occurring most commonly in: Morning (38.5%) vs. 14 (60.9%) , and noon 11 (42.3%) vs. 5 (21.7%) p=0.09. Mean days fast broken 2.5±1.6 vs. 2.05±1.4, p=0.7. One severe hypoglycemia, and one admission reported with the late regimen. No DKA admission during either regimen.
FCGM detected mean hypoglycemia events per patient per week of early vs. late regimen was 5.5 vs. 5.4, p=0.65; for post Suhoor (6 -11am) 0.94 vs. 1.07, p=0.25. Overall hypoglycemic events were significantly higher during morning/noon compared to pre-sunset 1.9 vs. 0.43, p&lt;0.001.
AGP report: GMI 7.58 ±1.vs. 7.49 ±0.9, p=0.36, Time in range (70-180 mg/dl) 46.9 ±17.3% vs. 47.9 ±17.3%, p=0.99, Time below range (&lt;70mg/dl) 8.6 ±14.3% vs. 7.8±7.6%, p=0.15, Time above range (&gt;180mg/dl) 45.8 ±22.03% vs. 44.5 ±20.1%, p=0.6, and Glucose variability 39.3 ±10.5% vs. 40.6 ±6.5%, p=0.005.
Conclusion: Managing T1D who fast Ramadan is challenging. Adjusting Suhoor meal and insulin dose time to allow post meal correction provides flexibility. Larger studies needed to demonstrate effectiveness of this approach.
ClinicalTrials.gov: NCT04864483

Disclosure
R. Alamoudi: None. M.A. Alassiri: None. M.M. Almaghrabi: None. D.S. Basulayman: None.

Funding
KAIMRC
718-P: Patients Achieving an HbA1c &lt;5.7% with =5% Weight Loss and without Hypoglycemia: A Post Hoc Analysis of SURPASS 1 to 5
Authors: CHENG ALICE Y. , LINGVAY ILDIKO , CHOUDHARY PRATIK , GOMEZ-VALDERAS ELISA , ALLEN SHERYL , RANTA KARI T. , LEVINE JOSHUA A. , THIEU VIVIAN 
Published: May 2022

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 &lt;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 &lt;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 &lt;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 &lt;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