Baseline A1C Research Articles

Association of food insecurity with changes in diet quality, weight, and glycemia over two years in adults with prediabetes and type 2 diabetes on medicaid

Little is known about longitudinal associations between food insecurity (FI) and diet, weight, and glycemia in people with prediabetes and type 2 diabetes (T2D). In a secondary analysis of Medicaid-enrolled health center patients with prediabetes or T2D in Boston, Massachusetts (N = 188), we examined associations between food security (FS) and measures of diet quality, weight, and hyperglycemia. FS (10-item USDA FS module) was ascertained at baseline, 1-year, and 2-year follow-up and categorized as persistently secure, intermittently insecure, or persistently insecure. Associations between FS category and changes in Healthy Eating Index-2020 (HEI-20), body mass index (BMI), and hemoglobin A1c (A1c) from baseline to year 2 were assessed using multivariate generalized linear models. Participants had median (p25, p75) age of 52 (42, 57); 71.8% were female and 62.8% Hispanic. Over follow-up, 32.4% were persistently food secure, 33.0% intermittently insecure, and 34.5% persistently insecure. Baseline mean (SD) HEI-20, BMI, and A1c were 55.8 (14.5), 35.9 (8.7) kg/m2, 7.1% (1.6) and did not differ by FS category. FS category was not associated with changes in HEI-20, BMI, and A1c at 2 years (all p > 0.05). Results suggest that Medicaid-enrolled adults with prediabetes or T2D, regardless of FS status, would benefit from dietary and weight management interventions.

The Impact of Glycemic Control on Sodium-Glucose Co-Transporter 2 Inhibitor-Associated Genitourinary Infections.

Patients with type 2 diabetes (T2D) are at an increased risk of genital urinary (GU) infections, with the risk increasing with higher A1Cs. Given the broad adoption of sodium-glucose co-transporter 2 inhibitors (SGLT2is) in patients with T2D, both providers and patients need to be aware of common adverse effects associated with these medications, specifically GU infections. However trials involving SGLT2is looked at patients with an average A1C of less than 9%, and thus, the incidence of GU infections may not truly reflect the general diabetic population. The purpose of this study is to assess the association between GU infections in patients started on SGLT2is and A1C levels. A retrospective study was conducted on patients seen in an adult, primary care clinic, at New York City Health and Hospitals, South Brooklyn Health. Men and nonpregnant, nonlactating women >18 years old with a diagnosis of T2D who were initiated on an SGLT2i between January 2018 and January 2023 were included in the analysis. The primary endpoint is to compare the risk of GU infections in patients with T2D who were started on SGLT2is, regardless of dose, with hemoglobin A1C of >9% to those with hemoglobin A1C <9% at baseline. Three hundred and twenty-eight patients were eligible based on specified inclusion and exclusion criteria. Overall, there was a statistically significant difference in the number of GU infections that occurred in patients with a baseline A1C >9% compared with those with an A1C <9% (95% confidence interval [CI] = 1.05-2.88; P = 0.041). Type 2 diabetes patients initiated on SGLT2is may experience an increased risk of GU infection, especially in those patients with an A1C of 9% or greater. Further research is necessary to validate and expand upon these findings.

Long-Term Results of a Digital Diabetes Self-Management and Education Support Program Among Adults With Type 2 Diabetes: A Retrospective Cohort Study.

The purpose of this study is to examine the long-term impact of a digital diabetes self-management education and support (DSMES) program on A1C among adults with type 2 diabetes (T2DM). Data analyzed were from a retrospective cohort of commercially insured members with T2DM enrolled in the Omada for Diabetes program between January 1, 2019, and January 31, 2022 (n = 1,322). Linear mixed models measured changes in A1C and weight across 12 months (collected at baseline and every 3 months over 1 year) overall and stratified by A1C at baseline (≥8% vs <8%). On average, members were 53.5 years old, 56.9% female, and 71.5% White, with a mean baseline body mass index (BMI) of 36.9 and A1C of 7.6%. Members with baseline A1C ≥8% demonstrated clinically and statistically significant adjusted mean reductions in A1C during follow-up, from 9.48% at baseline to 7.33%, 7.57%, 7.59%, and 7.47% at 3, 6, 9, and 12 months, respectively. Those with A1C <8% maintained glycemic stability (6.73%, 6.50%, 6.54%, 6.62%, and 6.51%, respectively). Collectively, members experienced a -1.17 kg/m2 mean reduction in BMI over 12 months. This study provides real-world evidence that members with elevated baseline A1C (≥8%) enrolled in a digital DSMES program experienced clinically meaningful and statistically significant reductions in A1C. Those with baseline A1C within goal treatment range (<8%) maintained glycemic stability over 1 year. The findings support existing evidence that scalable digital DSMES solutions can help individuals with T2DM manage their condition.

Endocrinology/Primary Care Pharmacy Collaboration vs Endocrinology Care Alone in Patients With Type 2 Diabetes and A1c >9.

Background: Type 2 diabetes (T2D) requires close collaboration between patients and their care management team, often including endocrinology. Primary care pharmacist impact on diabetes management in collaboration with endocrinology is not well established. Objective: To assess if pharmacy and endocrinology collaboration results in a greater A1c reduction in patients with T2D vs endocrinology alone. Methods: This retrospective, observational cohort study was conducted in adult outpatients with T2D and baseline A1c >9% who saw endocrinology within 1 year preceding the study period (January 1, 2021 to January 1, 2022). Patients were included if they had a follow-up A1c 6 months (±90 days) from index date and completed at least 1 endocrinology visit during the study period. Patients managed by endocrinology/primary care pharmacist collaboration (Endo/PharmD) were compared with those who received endocrinology care alone (Endo). Primary outcome was change in A1c from baseline to 6 months. Secondary outcomes included total number of completed visits and percentage of patients achieving A1c <6.5%, <7%, <8%, and <9% between groups at 6 months. Results: A total of 418 patients were included (22 Endo/PharmD, 396 Endo). The change in follow-up A1c was not significantly different between groups, -0.481% (standard error [SE] = 0.396); P = 0.6179. Endo/PharmD patients had significantly more provider visits during the study period (5.3 ± 2.3 vs 2.3 ± 1.2; P < 0.001). No significant difference was observed in odds of A1c goal attainment between groups at 6 months. Conclusion and Relevance: Endocrinology/primary care pharmacist collaboration occurred infrequently but was associated with a trend toward greater A1c reduction in patients with T2D and A1c >9%.

Program ACTIVE II: 6- and 12-month outcomes of a treatment approach for major depressive disorder in adults with type 2 diabetes

AimsTo evaluate the long-term effects of behavioral treatments on glycemic and psychological outcomes for patients with major depressive disorder (MDD) and type 2 diabetes (T2D). MethodsProgram ACTIVE II was a multicenter randomized controlled comparative effectiveness trial of cognitive behavioral therapy (CBT), exercise (EXER), combination treatment (CBT + EXER) and usual care (UC) for adults with MDD and T2D. ResultsPrimary outcomes: change in A1c and depressive symptoms at 6- (N = 87) and 12-months (N = 75) from baseline. In those with a baseline A1c ≥7.0 %, CBT + EXER showed lasting A1c benefit at 6- (−1.2 %; SE: 0.6; p = 0.032) and 12-months (−1.4 %; SE: 0.6; p = 0.025) compared to UC. All groups had clinically significant improvements in depressive symptoms. At 6 months, CBT + EXER had significant improvements in diabetes-related distress regimen burden (p = 0.005); and social support (CIRS, p = 0.043) compared to UC. ConclusionsThe Program ACTIVE II CBT + EXER intervention demonstrated a sustained improvement in A1c for a subgroup of study participants with a baseline A1c ≥7.0 %. However, this finding should be considered preliminary because of small sample size. All 3 behavioral intervention groups demonstrated improvements in psychosocial outcomes one-year post-intervention. These findings point to the enduring benefits of community-based interventions to extend the availability of depression treatment for T2D patients.

Metabolomic analysis of serum samples from a clinical study on ipragliflozin and metformin treatment in Japanese patients with type 2 diabetes: Exploring human metabolites associated with visceral fat reduction.

The effects of the sodium-dependent glucose transporter-2 inhibitor ipragliflozin were compared with metformin in a previous study, which revealed that ipragliflozin reduced visceral fat content by 12%; however, the underlying mechanism was unclear. Therefore, this sub-analysis aimed to compare metabolomic changes associated with ipragliflozin and metformin that may contribute to their biological effects. In the previous study, 103 patients with type 2 diabetes were randomly assigned to receive ipragliflozin 50 mg or metformin 1000 mg daily. Of the 103 patients, 15 patients in the ipragliflozin group with the highest reduction in visceral fat areas and 15 patients in the metformin group with matching characteristics, such as age, sex, baseline A1C, baseline visceral fat area, smoking status, and concomitant medication, were selected. The clinical data were reanalyzed, and metabolomic analysis of serum samples collected before and 24 weeks after drug administration was performed using capillary electrophoresis time-of-flight mass spectrometry. The reduction in the mean visceral fat area after 24 weeks of treatment was significantly larger (P=0.002) in the ipragliflozin group (-19.8%) than in the metformin group (-2.5%), as were the subcutaneous fat area and body weight. The A1C and blood glucose levels decreased in both groups. Glutamic pyruvic oxaloacetic transaminase, γ-glutamyl transferase, uric acid, and triglyceride levels decreased in the ipragliflozin group. Low-density lipoprotein cholesterol level decreased in the metformin group. After ipragliflozin administration, N2 -phenylacetylglutamine, inosine, guanosine, and 1-methyladenosine levels increased, whereas galactosamine, glucosamine, 11-aminoundecanoic acid, morpholine, and choline levels decreased. After metformin administration, metformin, hypotaurine, methionine, methyl-2-oxovaleric acid, 3-nitrotyrosine, and cyclohexylamine levels increased, whereas citrulline, octanoic acid, indole-3-acetaldehyde, and hexanoic acid levels decreased. Metabolites that may affect visceral fat reduction were detected in the ipragliflozin group. Studies are required to further elucidate the underlying mechanisms.

SAT666 Feasibility, Acceptability And Preliminary Efficacy Of Continuous Glucose Monitoring In Adolescents With Obesity

Abstract Disclosure: S. Chimatapu: None. S. Mittelman: None. M. Habib: None. L. Wisk: None. A. Klomhaus: None. A.P. Vidmar: None. Background: Childhood obesity is a global health concern that presents as a multifaceted challenge requiring comprehensive interventions targeting nutritional, physical activity and behavioral domains. Despite this, treatment outcomes have been modest due to challenges in adherence and individual variability in response. Wearable technologies, such as Continuous Glucose Monitors(CGMs), offer a unique solution to promote consistent weight control in youth. These devices provide real-time biofeedback, allowing youth to make timely and informed decisions about their lifestyle choices. To date, no trial has explored the feasibility and efficacy of CGM use as a standalone intervention for adolescents with obesity. Hypothesis: We hypothesize that this study will demonstrate feasibility, acceptability and preliminary efficacy of CGMs in facilitating weight management among adolescents with obesity. Furthermore, we postulate that the unblinded CGM use will lead to greater changes in diet and physical activity compared to blinded use; emphasizing the use of biofeedback as a motivator for behavior change in this population. Methods: Adolescents with obesity have been recruited into a six-week cross-over trial. All participants wear the CGM daily for six weeks. For three weeks subjects will wear the CGM in a blinded manner, and for the other three weeks they will have access to the real-time CGM data, with blocks assigned in a random, cross-over manner. Outcomes will include recruitment and retention rate, adherence, CGM metrics, sleep, dietary intake, physical activity, eating behaviors and change in weight compared between study arms. Results: We have so far recruited 16 of a goal of 30 adolescents (15.3± 2.4 years old, 68% female, 75% Hispanic). Baseline A1c was 5.6 ± 0.3%. Four participants completed the study; one was lost to follow up, and 11 are currently enrolled in the study. Data logs from weekly telephone calls revealed high continuous engagement throughout the six weeks of the study. Our qualitative analysis of participant feedback suggest that they engaged with their real-time device data during the unblinded window. Device itself was deemed comfortable to wear, fit properly, without adverse effects or negative impacts on daily functioning. One participant reported 2 lbs. weight loss in 2 weeks after wearing the CGM by modifying their behaviors based on the glucose readings. Conclusions: Our preliminary findings suggest that CGM use in youth with obesity is a feasible, acceptable and well-tolerated tool. CGMs also have the potential to bring forth sustainable changes in youth behavior and could be a powerful intervention to enhance lifestyle changes in pediatric weight management programs. Further analyses will be pursued to help understand effect of continuous glucose monitoring on glycemic variability, body composition and self-reported health behaviors in youth with obesity. Presentation: Saturday, June 17, 2023

FRI654 Concentrated Regular U-500 Insulin In An Automated Insulin Delivery System: A Case Report

Abstract Disclosure: J. Aurora: None. A. Saraswat: None. Background: Concentrated regular U-500 (U-500R) insulin is commonly used in patients with T2DM who are highly insulin-resistant, requiring more than 200 units of insulin per day. Utilizing U-500R reduces the number of daily injections, decreases injection volume, and improves cost effectiveness. There have been clinical trials using U-500R for continuous subcutaneous insulin infusion (CSII), particularly in Omnipod which has been shown to improve glycemic control and patient satisfaction without an increase in hypoglycemia (1). In addition, U-500R administration via multiple daily injections (MDI) and an investigational U-500R CSII, have been compared and demonstrated improved glycemic control with both modalities, but an increase in nocturnal hypoglycemia with CSII (2). Automated insulin delivery (AID) systems, or hybrid closed loop systems, have not formally been studied in patients with T2DM using U-500R. We present a case of a patient with T2DM with high insulin resistance using U-500R with Omnipod 5 AID system. Clinical Case: A 54-year-old female with T2DM with high insulin resistance was initially on Omnipod Dash with U-100 insulin lispro with baseline A1c 12.1%. She was transitioned to Omnipod 5 in 2022, and over 4 months A1c improved to 8.8%, GMI 8.8%, TIR 38%, TAR 62%, TBR 0%, CV 35.9%, and automated mode 97%. However, her total daily dose was 134 units leading to pod changes every 1.5 days. She expressed interest in switching to U-500R to reduce pod changes while utilizing her current CSII technology. We switched to U-500R, continued automated mode, increased her 24-hour BG target from 120 mg/dL to 130 mg/dL to reduce hypoglycemia risk, and increased her active insulin time from 3 to 6 hours to reflect U-500R kinetics. After 4 weeks, her GMI improved to 8.0%, TIR 47%, TAR 52%, TBR 1%, CV 45.9%, and automated mode 94%. Although nocturnal BG readings were normal, ranging from 70-130 mg/dL, she was having nightly symptoms of relative hypoglycemia. We then adjusted her BG target overnight to 150 mg/dL, which kept BG between 80-130 mg/dL with resolution of her symptoms. Conclusion: U-500R proved to be safe and effective with Omnipod 5 AID. Despite setting a higher BG target, the algorithm continuously kept BG well below this, particularly overnight. However, the safety mechanisms incorporated with the CSII suspended insulin delivery for predicted hypoglycemia. Further research will be required to adapt the automated dosing algorithm to U-500R to reduce the risk of nocturnal hypoglycemia.

SAT135 Prospective Analysis For Improvement For Glycemic Control Using A Patient Portal And Automated Messages

Abstract Disclosure: C.C. Cristancho: None. M. Brandao: None. A. Lema Morocho: None. T. Amorim: None. Background: Type II diabetes is a complex metabolic disorder which is influenced in part by patient dietary choices, medication adherence, and environmental factors. Behavioral health interventions offer an opportunity to potentially affect patient outcomes in a cost-effective manner. Purpose: To study whether automated clinical messaging via the electronic medical chart would be associated with improvement in diabetes-related health measures. Methods: We created an automated clinical messaging system (January 2020) via our electronic medical record. Patients who opted-in for this service received bi-weekly messages which included reminders about diabetes medication adherence as well as exercise and dietary recommendations. We then performed a retrospective longitudinal analysis of patients followed in our diabetes clinic, comparing those who opted-in for messing vs those who did not, and assessed diabetes-related biomarkers including baseline and follow-up hemoglobin A1c, lipid markers, and BMI using linear mixed-effects regression models. Results: 69 patients who had at least 2 measures of hemoglobin A1c were followed longitudinally, of whom 37 (54%) had opted to receive automated messaging. Patients who opted-in were younger (53±12 vs 62±11 years old, p&amp;lt;0.1), but not different in terms of sex (60% F vs 61% F), BMI (31±6 vs 30±7, p=0.84), or A1c (9.4±2.3 vs 8.8±2.7, p=0.34). In the group that received messages, we did not find any significant pre-post differences in A1c, LDL, or BMI over time. In the opt-in group, mean change (over average follow-up of 256 days) in HgbA1c was -0.4 (p=0.42) compared to a change of 0.0 in the non-opt-in group (p=0.99). Discussion: Patients who opted-in to electronic messaging were younger on average. We did not observe any significant longitudinal change in diabetes-related biomarkers within or between groups as related to an automated clinical messaging service, although there was a directional trend toward improvement. Given the cost-effectiveness and ease of this program, consideration should be given toward a trial with a larger sample size and longer follow-up. Presentation: Saturday, June 17, 2023

Safety Event Outcomes and Glycemic Control with a Hybrid Closed-Loop System Used by Chinese Adolescents and Adults with Type 1 Diabetes Mellitus.

Background: While evidence supports glycemic control benefits for individuals with type 1 diabetes mellitus (T1DM) using hybrid closed-loop (HCL) systems, HCL automated insulin delivery therapy in China has not been assessed. This study evaluated safety events and effectiveness during HCL system use by Chinese adolescents and adults with T1DM. Methods: Sixty-two participants (n = 12 adolescents with a mean ± standard deviation [SD] of 15.5 ± 1.1 years and n = 50 adults [mean ± SD of 37.6 ± 11.1 years]) with T1DM and baseline A1C of 7.1% ± 1.0% underwent a run-in period (∼2 weeks) using open-loop Manual Mode (sensor-augmented pump) insulin delivery with the MiniMed™ 770G system with the Guardian™ Sensor (3) glucose sensor, followed by a study period (4 weeks) with HCL Auto Mode enabled. Analyses compared continuous glucose monitoring data and insulin delivered during the run-in versus study period (Wilcoxon signed-rank test or t-test). Safety events included rates of severe hypoglycemia and diabetic ketoacidosis (DKA). Results: Compared to baseline run-in, overall Auto Mode use increased time in range (TIR, 70-180 mg/dL) from 75.3% to 80.9% (P < 0.001) and reduced time below range (TBR, <70 mg/dL) from 4.7% to 2.2% (P < 0.001). Subgroup analysis demonstrated that participants (n = 29) with baseline A1C <7.0% had TBR that reduced from 5.6% to 2.0%, while participants (n = 21) with baseline A1C ≥7.5% had time above range (TAR, >180 mg/dL) that reduced from 31.6% to 20.8%. Auto Mode use also increased the percentage achieving combined recommendations for time at sensor glucose ranges (i.e., TIR of >70%, TBR of <4% and TAR of <25%) from 24.2% at baseline to 77.4% at study end. Total daily insulin dose reduced from 42.8 ± 19.8 to 40.7 ± 18.9 U (P = 0.013). There were no severe hypoglycemic, DKA, or serious adverse events. Conclusions: Chinese adolescents and adults, some of whom met target A1C at baseline, safely achieved significantly improved glycemia with 1 month of MiniMed 770G system use when compared to open-loop insulin delivery. ClinicalTrials.gov ID: NCT04663295.

Impact of Intra-Articular Corticosteroid Injection on Glycemic Control: A Population-Based Cohort Study.

This retrospective cohort study investigated the longer-term hyperglycemic effects of intra-articular corticosteroid (IACS) administration by evaluating changes in A1C after large joint IACS injection. Among 1,169 patients (mean age 66.1 ± 12.2 years, 52.8% female), 184 (15.7%) experienced a greater-than-expected rise in A1C (actual A1C ≥0.5% above predicted) after IACS. Greater-than-expected rise in A1C was associated solely with baseline A1C (odds ratio [OR] 1.84, 95% CI 1.08-3.13 for baseline A1C of 7.0-8.0% compared with <7.0% and OR 4.79, 95% CI 2.83-8.14 for baseline A1C >8.0% compared with <7.0%). Although most patients do not experience an increase in A1C after IACS, clinicians should counsel patients with suboptimally controlled diabetes about risks of further hyperglycemia after IACS administration.

Effectiveness of Oral Semaglutide in Weight Loss and Glycemic Control among Type 2 Diabetes Population: A Real-world Longitudinal Study

Abstract Background: Oral semaglutide is a drug belonging to the class of glucagon-like peptide-1 receptor agonists which is known for its ability to maintain glycemic levels while reducing weight and lowering the risk of cardiovascular events. This study aims to explore the effectiveness of oral semaglutide by using real-world data from South Asia (India). Materials and Methods: The study is a real-world longitudinal study, and the data for the study were extracted from electronic medical records of a comprehensive diabetes center in Kerala. The primary outcome variables were measured at the baseline and at 6 months. The subjects who had data from March 2022 to July 2023 were included in the study while those with no follow-up data were excluded. The sample size was calculated as 52 using the sample size formula for the comparison of two dependent groups with a quantitative outcome. All the analyses were carried out at a level of significance of 5% using R version 4.3.1. Results: The clinical characteristics such as weight, systolic blood pressure, estimated glomerular filtration rate, and serum glutamic-oxaloacetic transaminase/aspartate aminotransferase were found to have a significant difference between the baseline and endpoint (P &lt; 0.05). The mean absolute difference between the baseline and endpoint hemoglobin A1c (HbA1c) was found to be 0.65% (P &lt; 0.001), and for body mass index (BMI), it was found to be 1.69 kg/m2 (P &lt; 0.001). The baseline HbA1c and BMI were found to be significantly associated with the change in HbA1c and BMI, respectively (P &lt; 0.05). Conclusion: This study is one of the first real-world studies conducted in South Asia (India) that explores the effectiveness of oral semaglutide. The study showed that the usage of oral semaglutide induced a significant reduction of weight and HbA1c among people with type 2 diabetes. Addressing the limitations can bring new insights into the diabetes management paradigm.

943-P: Improved Glycemic Outcomes after One Year among Level 2 Members

Background: Level2’s virtual specialty clinic, offered across the United States to people with type 2 diabetes on participating insurance plans, combines providers, coaches, continuous glucose monitors (CGM), and fitness trackers to help members gain insight, and focus on long-term behavior change. We retrospectively assessed differences in glycemic outcomes following one year of participation in Level2. Methods: People joining Level2 between 01/01/21 and 07/31/21 with 15 months of Level2 participation and 3 prior months of continuous enrollment in a participating commercial health plan were included in the analysis. We used CGM-derived GMI and A1c values available from a database of de-identified administrative claims to determine baseline and 12-month follow-up glycemic outcomes. Wilcoxon signed-rank tests were used to test for pair-wise improvements in glycemic measures between baseline and follow-up overall and stratified by baseline A1c. Results: Of the 3,440 people identified for the analysis, a subset (N = 200) had both baseline A1c and valid GMIs during follow-up. This subset was 53% (N = 106) male with mean age of 55.4 (SD = 8.5) years and had mean baseline A1c of 7.97% (SD = 1.02). The median difference between baseline A1c and follow-up GMI was -0.83% (p &amp;lt; 0.001) overall, with significant differences of -0.82% (p &amp;lt; 0.001) and -2.41% (p &amp;lt; 0.001) in those with baseline 7% &amp;lt; A1c &amp;lt; 9% and A1c &amp;gt; 9%, respectively. Over 50% of people had a decrease in glycemic outcome of more than 0.5%, with 67% and 95% of people improving by more than 0.5% in the 7-9% and &amp;gt; 9% groups respectively. There were 87 people that also had an A1c at 12-month follow-up; the median difference in A1c was -0.65% (p &amp;lt; 0.001), 50% had a decrease of more than 0.5%, and median difference between GMI/A1c follow up values was 0.13 (p = 0.11). Conclusion: Level2 members with baseline A1c and follow-up GMI saw significant improvements in glycemic control over one year of engagement. These improvements were observed for measures of both follow-up A1c and GMI. 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.

272-OR: The Efficacy of Sotagliflozin on Heart-Failure Related Outcomes Is Independent of Baseline A1C

Background: SGLT inhibitors reduce the risk of cardiovascular (CV) events in patients with heart failure (HF) and chronic kidney disease regardless of diabetes status. Although the SOLOIST-WHF and SCORED trials enrolled high CV risk patients with T2DM, participants had a wide range of baseline A1C values. Thus, the present analysis evaluated the effects of sotagliflozin relative to placebo on cardiovascular (CV) death and total HF-related outcomes by baseline A1C range. Methods: SOLOIST-WHF had no baseline A1C entry criteria (baseline median = 7.1%, range = 4.5, 15.0%), while SCORED randomized patients with T2DM and an A1C ≥7% at screening (8.3%, 6.5, 17.3%). Natural cubic splines from Poisson regression models estimated the relationships between continuous A1C and the primary endpoint for both studies: total number of CV deaths, hospitalizations for HF, and urgent visits for HF. Results: Within each trial, patients with higher baseline A1C experienced higher event rates (spline effect p=0.0349 and 0.0014 for SOLOIST-WHF and SCORED, respectively). Sotagliflozin reduced the primary outcome in each trial (p for treatment &amp;lt;0.0001 for both SOLOIST-WHF and SCORED) and this did not differ across A1C (p for interaction &amp;gt;0.10; Figure). Conclusion: Sotagliflozin was effective in reducing the risk of CV death and HF-related events independent of baseline A1C. Disclosure R.Aggarwal: None. D.L.Bhatt: Board Member; Bristol-Myers Squibb Company, Research Support; Lexicon Pharmaceuticals, Inc., Sanofi, Lilly, Boehringer Ingelheim Inc., AstraZeneca, Novo Nordisk. M.Szarek: Consultant; Amarin Corporation, ESPERION Therapeutics, Inc., Other Relationship; Janssen Pharmaceuticals, Inc., Research Support; Lexicon Pharmaceuticals, Inc., Regeneron, Sanofi, Bayer Inc. M.J.Davies: Employee; Lexicon Pharmaceuticals, Inc. P.L.Banks: Employee; Lexicon Pharmaceuticals, Inc. B.Pitt: Consultant; Bayer Inc., AstraZeneca, Boehringer Ingelheim International GmbH, Vifor Pharma Management Ltd., Lexicon Pharmaceuticals, Inc., PhaseBio Pharmaceuticals, Inc., KBP Bioscience, Merck &amp; Co., Inc. P.G.Steg: Advisory Panel; Merck &amp; Co., Inc., Consultant; Sanofi, Amarin Corporation, Amgen Inc., BMS, PhaseBio Pharmaceuticals, Inc., Idorsia Pharmaceuticals Ltd., Novartis AG, Janssen Pharmaceuticals, Inc., AstraZeneca, Research Support; Lexicon Pharmaceuticals, Inc.

31-LB: The Relationship between Improvements in Glycemic Control following a Digital Health Intervention and the Food Environment in a Medicare Advantage Population

Diabetes is a complex disease that is influenced by social determinants of health (SDOH). An inadequate food environment, as a function of socioeconomic status and proximity to food retailers, has been associated with both increased prevalence of diabetes and barriers to diabetes self-management. This work examined the relationship between improvements in glycemic control as a result of a digital health intervention and the food environment in Medicare Advantage members at risk for diabetes-related complications (hemoglobin A1c [A1c] ≥ 8%). Participants enrolled in the Vida Health Diabetes Management program as part of their medical insurance benefit and utilized remote sessions with Registered Dietitians and Certified Diabetes Care and Education Specialists as well as content related to goal-setting to account for SDOH factors. The 2010 USDA Food Access Research Atlas was used to identify areas of low income and the absence of a food retailer within 0.5 or 1 urban and 10 rural miles (LILA). Participants were included if they had a laboratory A1c between -365 to -1 and 60 to 365-days of enrollment. Participants with baseline A1c ≥ 8.0 (n=430, 229 F, 68.9 y) demonstrated a decrease of -0.90 points (SD 1.71, p&amp;lt;0.001). Thirty-five percent resided in LILA areas at the 0.5, and twenty percent at 1 mile distance. Participants who resided in LILA areas had higher baseline A1c (0.5 difference: 0.37 (p=0.02), 1 difference: 0.51 (p=0.005)). Those with baseline A1c ≥ 9.0 (n=216, 120 F, 67.8 y) demonstrated a decrease of -1.38 points (SD 1.96, p&amp;lt;0.001). Thirty-nine percent resided in LILA areas at the 0.5, and twenty-three percent at 1 mile distance. Baseline A1c differences were not observed. Differences in improvements in A1c based on LILA were not observed (p’s &amp;gt; 0.05). Irrespective of LILA residence, the Vida Health program demonstrated significant improvements in glycemic control within 1 year in a high-risk Medicare Advantage population. Disclosure C. Edwards: Employee; Vida Health. L. Voelker: Employee; Vida Health. G. Zimmermann: Employee; Vida Health. K. Rawlings: Employee; Vida Health. A. Venkatesan: Employee; Vida Health. Funding Vida Health

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

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.

968-P: Real-World Comparison of Younger and Older Cohorts Using the Bigfoot Unity System for Six Months

Background: The Bigfoot Unity® System is an FDA-cleared smart pen cap system incorporating CGM data, real-time alerts, and clinician-directed dose recommendations. The objective was to analyze real world data from younger and older subgroups using the System for MDI. Methods: We conducted a 6-month retrospective analysis using deidentified data and a prespecified analysis plan for commercial users with ≥50% CGM data in the 6th month (N=127, 24 clinics). A baseline A1C was obtained from clinic medical records (N=118). Outcomes for those &amp;lt;65 (N=58) and ≥65 (N=69) years old were compared. Results: Most (83%) in each group had T2D; mean age in &amp;lt;65 and ≥65 groups was 54 and 73 years. Mean baseline A1C was 8.6±1.7% and 8.2±1.6% in the &amp;lt;65 and ≥65 groups; mean 6 month GMI was 7.5±0.9% and 7.3±0.8%, respectively. Glycemic outcomes and System use data are shown for age subgroups (Table). Using GMI as an A1C proxy, pairwise comparisons of GMI at 6 months to baseline A1C (N=118) show a 1.1±1.4% improvement overall (P&amp;lt;0.05). Discussion: The overall cohort consisted mostly of older T2D adults using MDI with suboptimal glycemic control. Given there may be concerns with older people adequately adopting and using new technology to manage diabetes, comparison with those younger highlights similar glycemic control and System engagement with Bigfoot Unity. Both groups demonstrate close adherence to established glycemic targets at 6 months. Disclosure S.Vaughan: Employee; Bigfoot Biomedical, Inc. J.Tillman: Employee; Bigfoot Biomedical, Inc. B.P.Olson: Employee; Bigfoot Biomedical, Inc. F.Sheikh: Employee; Bigfoot Biomedical, Inc. J.K.Malone: Employee; Bigfoot Biomedical, Inc. Funding Bigfoot Biomedical, Inc.

154-LB: HEDIS Glycemic Goals Achieved by Control-IQ Technology Users across All Payer Types

Background: The t:slim X2 with Control-IQ technology (“Control-IQ”) is an advanced hybrid closed-looped system. This analysis evaluated glycemic outcomes in Control-IQ users by payer type using Healthcare Effectiveness Data and Information Set (HEDIS) quality thresholds. HEDIS is used by &amp;gt;90% of health plans to measure performance and includes a metric to identify A1c control (&amp;lt;8.0%) and poor control (&amp;gt;9.0%). Glucose management indicator (GMI) is a recognized surrogate for A1c when sufficient data are provided (≥14 days, 70% CGM use). Methods: We retrospectively analyzed glycemic data for individuals with type 1 diabetes from 1/1/20 to 3/4/23 who used Control-IQ for ≥1 year (with ≥70% of CGM use in final 3 months) and had a recorded baseline A1c prior to Control-IQ initiation. Results were stratified by payer type, prior therapy, and baseline A1c. GMI was calculated for last 3 months and compared to baseline A1c. Results: Analysis included 20,319 users, with 42% (n= 8,493) on multiple daily injections (MDI) and 58% (n=11,826) on pump therapy at baseline. Control-IQ use significantly improved glycemic outcomes and mean HEDIS thresholds were achieved for all payer types and strata (table). Conclusion: Control-IQ use improved HEDIS A1c (GMI) outcomes across all payer types, with the largest glycemic improvement seen in those with the highest A1c at baseline and for prior MDI users. Disclosure B. V. Patel: Employee; Tandem Diabetes Care, Inc. Stock/Shareholder; Tandem Diabetes Care, Inc. G. Alencar: Employee; Tandem Diabetes Care, Inc. S. M. Wang: Employee; Tandem Diabetes Care, Inc. Stock/Shareholder; Tandem Diabetes Care, Inc. S. Leas: Employee; Tandem Diabetes Care, Inc. L. H. Messer: Employee; Tandem Diabetes Care, Inc. Consultant; Dexcom, Inc. Advisory Panel; Lilly. Consultant; Capillary Biomedical, Inc. Research Support; Beta Bionics, Inc., Medtronic, Insulet Corporation. J. E. Pinsker: Employee; Tandem Diabetes Care, Inc.

964-P: Real-World Comparison of Rural and Urban Cohorts Using the Bigfoot Unity System for 6 Months

Background: The Bigfoot Unity® System incorporates CGM data, real-time alerts, and clinician-directed dose recommendations. Clinicians use a web portal to view patient data remotely. Our objective was to analyze real world data from rural and urban subgroups. Methods: A 6-month retrospective analysis was done using a prespecified analysis plan for commercial users with ≥50% CGM data at 6 months (N=127, 24 clinics). A baseline A1C was obtained from clinic medical records (N=118). Glycemic and System engagement outcomes for those living in urban (N=102) and rural (N=25) zip codes were compared. Results: Most in urban and rural groups had T2D (82 v 84%); mean age was 65 and 61 years, respectively. Urban users had mean baseline A1C of 8.4±1.6% and 7.5±0.8% mean GMI at 6 months; rural users had baseline A1C of 8.5±1.9% and 6-month GMI of 7.2±0.8%. Subgroup outcomes are shown (Table). Using GMI as an A1C proxy, pairwise comparisons of 6 month GMI to baseline A1C in the overall cohort (N=118) show a 1.1±1.4% improvement (P &amp;lt;0.05). Discussion: Overall, both groups were primarily older adults with T2D using MDI and having suboptimal glycemic control before System use. Given concerns with disparity in diabetes management in rural areas, we evaluated rural and urban users of Bigfoot Unity. The rural cohort was small but data suggests that for both groups, using the System resulted in similar improved and durable glycemic control at 6 months. Disclosure J.Tillman: Employee; Bigfoot Biomedical, Inc. B.P.Olson: Employee; Bigfoot Biomedical, Inc. S.Vaughan: Employee; Bigfoot Biomedical, Inc. F.Sheikh: Employee; Bigfoot Biomedical, Inc. J.K.Malone: Employee; Bigfoot Biomedical, Inc. Funding Bigfoot Biomedical, Inc.

1029-P: Building Diabetes Care Capacity in Rural Underserved Communities—A Comparison of Cardiorenal Risk Factor Outcomes in Patients Treated by ECHO-Trained Providers vs. an Academic Medical Center

Background: National trends in diabetes outcomes, particularly in rural communities, do not mirror the significant benefits seen in clinical trials with emerging therapeutics and technologies. This disconnect is partly attributable to therapeutic inertia around uptake of clinical practice guidelines that have prioritized cardiorenal risk reduction. Project ECHO is a workforce development program that supports implementation of guidelines in under-resourced areas through virtual communities of practice and case-based learning. We hypothesized that the care of patients with diabetes treated by rural ECHO-trained providers would be non-inferior to those treated by specialists at an academic medical center (AMC). Methods: A multidisciplinary team from a minority-majority state-funded AMC launched a weekly 2-hour diabetes ECHO program to mentor care dyads consisting of a primary care provider and community health worker at 10 rural primary care clinics. We compared cardiorenal risk factor changes in patients with diabetes treated by ECHO-trained dyads to patients treated by specialists at the AMC. Multiple regression models were adjusted for age, sex, baseline A1c and BMI, baseline risk factor outcome, and interactions with site. All model assumptions were satisfied. Results: The mean follow-up duration was 21 months in the ECHO cohort and 18 months in the AMC cohort. Compared to the AMC cohort (n=151), patients in the ECHO cohort (n=856) experienced a greater A1c reduction (-1.4% vs -0.3%; P=0.017) and were more likely to achieve an A1c&amp;lt;8% (20.1% vs. 0.3% increase in those achieving A1c&amp;lt;8%; P&amp;lt;0.001). Changes from baseline in BP, LDL, and urine microalbumin were similar between groups (P&amp;gt;0.05). Conclusions: ECHO may be a suitable intervention for improving diabetes and cardiorenal risk factor outcomes in rural, under-resourced communities where access to a specialist is limited. Disclosure M.F.Bouchonville: None. E.B.Erhardt: None. Y.L.Leyva: None. L.Myaskovsky: None. M.L.Unruh: None. S.Arora: None.