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To compare the efficacy and safety of a simple daily titration algorithm compared with a weekly dose adjustment of iGlarLixi in people with type 2 diabetes.LixiLan ONE CAN (NCT03767543), a randomized, 26-week, open-label, multicentre phase 3 trial conducted in Canada, involved 265 people with type 2 diabetes and an HbA1c of ≥7.5% to ≤ 10.5% or less (≥58 to ≤91 mmol/mol) on basal insulin for 6 months or longer. Participants were randomized 1:1 with instructions to self-titrate iGlarLixi daily (1 unit/day) or once weekly (2 or 4 units/week) to a common target fasting plasma glucose of 4.4 to 5.6 mmol/L (79 to 101 mg/dl). The primary objective was to show non-inferiority of the daily versus weekly titration algorithm.At 26 weeks, daily titration of iGlarLixi was not inferior to a weekly titration for both the prespecified primary endpoint of change in HbA1c from baseline (least square [LS] mean change: -1.24% vs. -0.92%, respectively; LS mean difference: 0.32%; 95% CI [0.07, 0.57]; P .0001) and for the secondary endpoint of change in weight from baseline (LS mean change: -0.22 vs. +0.81 kg, respectively; LS mean difference: 1.03 kg; 95% CI [0.01, 2.06]; P .0001). Indeed, for both the primary and secondary outcome, the daily titration of iGlarLixi was superior. There were no statistically significant differences in hypoglycaemia incidence between the two titration strategies during the 26-week study.A daily titration algorithm for switching basal insulin to iGlarLixi was shown to be non-inferior and superior for glycaemic control and weight compared with weekly titration.

Type 2 diabetes (T2D) is a progressive disease, with many individuals eventually requiring basal insulin therapy to maintain glycaemic control. However, there exists considerable therapeutic inertia to the prompt initiation and optimal titration of basal insulin therapy due to barriers that include fear of injections, hypoglycaemia, weight gain, and burdensome regimens. Hypoglycaemia is thought to be a major barrier to optimal glycaemic control and is associated with significant morbidity and mortality. Newer second-generation basal insulin analogues provide comparable glycaemic control with lower risk of hypoglycaemia compared with first-generation basal insulin analogues. The present review article discusses clinical evidence for one such second-generation basal insulin analogue, insulin glargine 300 U/mL (Gla-300), in the context of hypothetical case studies that are representative of individuals who may attend routine clinical practice. These case studies discuss individualised treatment needs for people with T2D who are insulin-naïve or pre-treated. Clinical characteristics such as older age, frequent nocturnal hypoglycaemia, and renal impairment, which are known risk factors for hypoglycaemia, are also considered.

To examine the mediating role of adiposity on the associations of diet quality with longitudinal changes in insulin sensitivity and beta-cell function.Adults at-risk for type 2 diabetes (T2D) in the PROMISE cohort had 4 assessments over 9 years (n = 442). Alternate Healthy Eating Index (AHEI) scores were used to assess diet quality. Generalized Estimating Equations (GEE) evaluated the associations between the AHEI and longitudinal changes in insulin sensitivity (HOMA2-%S and ISI) and beta-cell function (IGI/HOMA-IR and ISSI-2). The proportion of the mediating effect of waist circumference changes was estimated using the difference method. In the primary longitudinal analysis, AHEI was positively associated with insulin sensitivity and beta-cell function over time (% difference per standard deviation increase of AHEI for HOMA2-%S (β = 11.0, 95%CI 5.43-17.0), ISI (β = 10.4, 95%CI 4.35-16.8), IGI/HOMA-IR (β = 7.12, 95%CI 0.98-13.6) and ISSI-2 (β = 4.38, 95%CI 1.05-7.80), all p 0.05). There was no significant association between AHEI and dysglycemia incidence (OR = 0.95, 95%CI 0.77-1.17). Adjustments for longitudinal changes in waist circumference substantially attenuated all associations of AHEI with insulin sensitivity and beta-cell function. Mediation analysis indicated that waist circumference mediated 73%, 70%, 83% and 81% of the association between AHEI and HOMA2-%S, ISI, IGI/HOMA-IR, and ISSI-2, respectively (all p 0.01).In a Canadian population at-risk for T2D, AHEI score was positively associated with changes in insulin sensitivity and beta-cell function. These associations were substantially mediated by waist circumference, suggesting that changes in adiposity may represent an important pathway linking diet quality with risk phenotypes for T2D.

OBJECTIVE To determine the association of adipose tissue insulin resistance with longitudinal changes in biomarkers of adipose tissue function, circulating lipids, and dysglycemia. RESEARCH DESIGN AND METHODS Adults at risk for type 2 diabetes in the Prospective Metabolism and Islet Cell Evaluation (PROMISE) cohort had up to four assessments over 9 years (n = 468). Adipose tissue insulin resistance was determined using a novel validated index, Adipo-IR, calculated as the product of fasting insulin and nonesterified fatty acids measured at baseline. Fasting serum was used to measure biomarkers of adipose tissue function (adiponectin and soluble CD163 [sCD163]), circulating lipids (total cholesterol, HDL, LDL, triglyceride [TG]), and systemic inflammation (interleukin-6 [IL-6] and tumor necrosis factor-α [TNF-α]). Incident dysglycemia was defined as the onset of impaired fasting glucose, impaired glucose tolerance, or type 2 diabetes at follow-up. Generalized estimating equation (GEE) models were used to assess the relationship of Adipo-IR with longitudinal outcomes. RESULTS GEE analyses showed that elevated Adipo-IR was longitudinally associated with adipose tissue dysfunction (adiponectin −4.20% [95% CI −6.40 to −1.95]; sCD163 4.36% [1.73–7.06], HDL −3.87% [−5.15 to −2.57], TG 9.26% [5.01–13.69]). Adipo-IR was associated with increased risk of incident dysglycemia (odds ratio 1.59 [95% CI 1.09–2.31] per SD increase). Associations remained significant after adjustment for waist circumference and surrogate indices for insulin resistance. There were no significant longitudinal associations of Adipo-IR with IL-6, TNF-α, total cholesterol, or LDL. CONCLUSIONS Our findings demonstrate that adipose tissue insulin resistance is prospectively associated with adipose tissue function, HDL, TG, and incident dysglycemia.

Objective Hypoglycemia can cause psychological distress in people with diabetes; however, less is understood about the emotional impact of hypoglycemia on their health care providers (HCPs). This article focuses on the experiences and emotions of HCPs caring for patients with diabetes. Methods This was a descriptive qualitative study from the InHypo-DM research program. Purposive sampling was used to recruit 20 HCPs from a variety of professions for 30- to 45-minute semi-structured interviews. An iterative analysis was conducted to identify the overarching themes. Results Three overarching themes encompassed the responses of participants when their patients experienced hypoglycemia. The first was a sense of professional responsibility, as participants felt they must have failed or inadequately fulfilled their professional duties. The second was a more personal range of emotions such as sadness and guilt. The final theme was how these emotions created a “call to action,” prompting participants to identify potential strategies to prevent future hypoglycemic events. Conclusion This qualitative study highlights the emotional impact of patients’ hypoglycemia on HCPs. Although it may have been expected that HCPs have a strong sense of professional responsibility, it was unexpected that these responses often became personal emotions. To ameliorate the negative impact of these responses on patient care, HCPs should engage in activities that enable them to anticipate and manage their own emotional responses. In addition, strategies to optimize hypoglycemia detection and prevention should be promoted.

Introduction The aim of the study was to examine glycaemic control and safety of insulin degludec (degludec) in patients with either type 1 diabetes (T1D) or type 2 diabetes (T2D) under routine care settings in Canada. Methods Data were extracted from medical records of adults with T1D or T2D who switched to degludec (± prandial insulin) from another basal insulin (± prandial insulin) ≥ 6 months prior to data collection. The primary endpoint was change in glycated haemoglobin (HbA1c) at 6 ± 3 months after degludec initiation. Secondary endpoints included change in hypoglycaemia rate in the 6 months before versus the 6 months after switching, and change in mean total daily insulin dose. Results Of 667 patients assessed for eligibility, 626 were included. After 6 ± 3 months, HbA1c decreased from baseline in patients with T1D (− 0.3% [− 0.42, − 0.14]95% CI; p

Background The treatment landscape for type 2 diabetes (T2D) is continually evolving; therefore, ongoing education of health care professionals (HCPs) is essential. There is growing interest in measuring the impact of educational activities, such as through use of the Moore framework; however, data on the benefits of continuing medical education (CME) in the management of T2D remain limited. Objective This study aimed to evaluate HCP satisfaction; measure improvements in knowledge, competence, and performance following short, case-based, multidisciplinary web-based CME activities; and identify the remaining educational gaps. Methods Two faculty-led, CME-accredited, web-based educational activities on T2D and obesity, touchIN CONVERSATION and touch MultiDisciplinary Team, were developed and made available on a free-to-access medical education website. Each activity comprised 3 videos lasting 10 to 15 minutes, which addressed learning objectives developed based on a review of published literature and faculty feedback. Participant satisfaction (Moore level 2) was evaluated using a postactivity questionnaire. For both activities, changes in knowledge and competence (Moore levels 3 and 4) were assessed using questionnaires completed by representative HCPs before or after participation in the activities. A second set of HCPs completed a questionnaire before and after engaging in activities that assessed changes in self-reported performance (Moore level 5). Results Each activity was viewed by approximately 6000 participants within 6 months. The participants expressed high levels of satisfaction (>80%) with both activities. Statistically significant improvements from baseline in knowledge and competence were reported following participation in touchIN CONVERSATION (mean score, SD before vs after activity: 4.36, 1.40 vs 5.42, 1.37; P Conclusions Short, case-based, web-based CME activities designed for HCPs to fit their clinical schedules achieved improvements in knowledge, competence, and self-reported performance in T2D management. Ongoing educational needs identified included setting individualized glycemic targets and the potential benefits of sodium-glucose cotransporter 2 inhibitor therapies.

Introduction: Therapeutic inertia is a major contributor to people with diabetes not achieving glycemic goals. We assessed for patients with T2D the impact of using the FreeStyle Libre system (FSL) vs. blood glucose monitoring (BGM) on treatment intensification. Method: We carried out a matched retrospective cohort study using secondary private payer claims data including >30 million diabetes drug and device claims filled by over 850,000 patients with T2D >18 in Canada over 24 months. Each month, patients were classified by level of therapy progression: 1. No diabetes drug therapy; 2. Mono Oral Antihyperglycemic Agents (OHAs) ; 3. Dual OHAs; 4. Triple OHAs; 5. Quad or more OHAs; 6. Injectable GLP1-RA (±concomitant OHAs) ; 7. Basal insulin (±concomitant OHAs) ; 8. MDI insulin (±concomitant OHAs) . Results: A total of 373,871 patients met the inclusion criteria. Across all treatment cohorts, the FSL treatment groups were found to have a statistically higher probability of treatment intensification relative to BGM: Conclusion: Reimbursement of FSL for patients with T2D in Canada is associated with decreased time lag for glucose lowering therapy compared to those using BGM alone. These findings suggest that FSL data impact clinicians to facilitate earlier and more intensive therapy modifications and thus reduce treatment inertia. Disclosure S.B.Harris: Consultant; Abbott, AstraZeneca, Eli Lilly and Company, Novo Nordisk, Sanofi, Other Relationship; Abbott, AstraZeneca, Bayer Inc., Dexcom, Eli Lilly and Company, HLS Therapeutics, Janssen Pharmaceuticals, Inc., Novo Nordisk, Sanofi, Research Support; Applied Therapeutics Inc., AstraZeneca, Canadian Institutes of Health Research, Juvenile Diabetes Research Foundation (JDRF) , Novo Nordisk, Sanofi, The Lawson Foundation. F.Levrat-guillen: Employee; Abbott. Funding Funded by Abbott Diabetes Care

The PIONEER 8 (NCT03021187) trial demonstrated significant glucose-lowering efficacy of oral semaglutide vs. placebo (pbo) in patients (pts) with T2D inadequately controlled with insulin. Additionally, those assigned to oral semaglutide (7 or 14 mg daily) had a lower total daily insulin dose at end of treatment (week 52) relative to baseline, vs. those treated with pbo, suggesting an insulin-sparing effect. This post-hoc analysis of PIONEER 8 aimed to characterize the transition of adding a GLP-1RA to insulin therapy and to quantify reductions in total insulin dose seen with the addition of oral semaglutide. A 20% reduction in total daily insulin dose was recommended at randomization up to week 8. Total daily insulin was not to exceed pre-randomization dose between weeks 8 and 26 but was freely adjustable at the investigator’s discretion from week 26 to 52. For all doses of oral semaglutide, a greater proportion of pts were able to maintain a greater level of insulin dose reduction vs. pbo at week 26 (Figure) . Greater proportions of pts on oral semaglutide 3, 7, and 14 mg achieved ≥20% reductions in insulin vs. those in the pbo group at both weeks 26 and 52 (Treatment policy estimand; 27.5%, 28.9%, 31.2% vs. 12.4% and 19.5%, 25.0%, 32.0% vs 5.7%, respectively; P Disclosure V.R.Aroda: Consultant; Applied Therapeutics, Fractyl Health, Inc., Novo Nordisk, Pfizer Inc., Sanofi, Other Relationship; Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Research Support; Applied Therapeutics, Fractyl Health, Inc., Novo Nordisk, Sanofi. M.T.Abildlund: Employee; Novo Nordisk A/S, Stock/Shareholder; Novo Nordisk A/S. R.Agesen: Employee; Novo Nordisk A/S. S.B.Harris: Consultant; Abbott, AstraZeneca, Eli Lilly and Company, Novo Nordisk, Sanofi, Other Relationship; Abbott, AstraZeneca, Bayer Inc., Dexcom, Eli Lilly and Company, HLS Therapeutics, Janssen Pharmaceuticals, Inc., Novo Nordisk, Sanofi, Research Support; Applied Therapeutics Inc., AstraZeneca, Canadian Institutes of Health Research, Juvenile Diabetes Research Foundation (JDRF) , Novo Nordisk, Sanofi, The Lawson Foundation. B.Zahedi: Employee; Novo Nordisk A/S. B.Zinman: Advisory Panel; Abbott Diabetes, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk Canada Inc., Sanofi K.K. E.Araki: Other Relationship; Astellas Pharma Inc., Daiichi Sankyo, Eli Lilly and Company, Kowa Company, Ltd., Merck & Co., Inc., Mitsubishi Tanabe Pharma Corporation, Nippon Boehringer Ingelheim Co. Ltd., Novartis Pharma K.K., Novo Nordisk, Sanofi K.K., Taisho Pharmaceutical Holdings Co., Ltd., Takeda Pharmaceutical Company Limited, Terumo Corporation, Speaker's Bureau; Abbott, AstraZeneca, Kyowa Kirin Co., Ltd., Ono Pharmaceutical Co., Ltd., Sanwa Kagaku Kenkyusho. Funding Funded by Novo Nordisk A/S

Most prediction models for diabetes-related iatrogenic severe hypoglycemia (SH) have derived from trial/administrative records subject to poor generalizability, ascertainment bias, and incomplete data capture. Redressing this gap, iNPHORM leveraged the clinical and methodological advantages of prospective self-report to develop and internally validate a 1-year SH prediction model for use in real-world clinical contexts. Adults (18-90 years old) with insulin- and/or secretagogue-treated type 1 or 2 diabetes (T1D, T2D) were recruited from a US-wide probability-based internet panel and followed for one year. Monthly emailed questionnaires assessed SH incidence and related factors. To model recurrent 1-year SH (daytime + nocturnal) , Andersen-Gill Cox proportional hazards regression was performed on participants completing ≥1 follow-up. Missing data were multiply imputed with chained equations. Machine learning penalized regression with lasso was used to select clinically plausible predictors. A total of 986 (T1D: 17%) participants were analyzed (retention rate: 86.2%) . The mean age was 51 (SD: 14.3) years, 49.6% were male, and the median duration of T1D/T2D was 12 (IQR: 14) years. Among T2D participants, 38% were on insulin (without secretagogues) , 38% on secretagogues (without insulin) , and 24% on insulin plus secretagogues. Across follow-up, 35.1% (95% CI: 32.2-38.1%) reported ≥1 SH, and the annual rate was 4.97 (95% CI: 4.13-5.99) . Combination insulin-secretagogue therapy; use of an insulin pump and continuous glucose monitoring; decreased age; increased previous SH requiring healthcare utilization; chronic kidney disease; and food insecurity predicted 1-year SH risk. The optimism adjusted c-statistic was 0.75. iNPHORM is the first long-term, prospective study on SH prediction in the general US population with T1D and T2D. Our 7-variable model can be used to identify patients at high-risk of SH, leading to more valid, cost-effective prevention strategies in the real world. Disclosure A.Ratzki-leewing: Consultant; Eli Lilly and Company, Other Relationship; Sanofi. S.B.Harris: Consultant; Abbott, AstraZeneca, Eli Lilly and Company, Novo Nordisk, Sanofi, Other Relationship; Abbott, AstraZeneca, Bayer Inc., Dexcom, Eli Lilly and Company, HLS Therapeutics, Janssen Pharmaceuticals, Inc., Novo Nordisk, Sanofi, Research Support; Applied Therapeutics Inc., AstraZeneca, Canadian Institutes of Health Research, Juvenile Diabetes Research Foundation (JDRF) , Novo Nordisk, Sanofi, The Lawson Foundation. J.E.Black: None. G.Zou: None. S.Webster-bogaert: None. B.L.Ryan: None. Funding Sanofi Global

Background: This study describes the impact of the pandemic on the management of people with type 2 diabetes (PwT2D) in a primary care network with existing virtual care capabilities in Ontario, Canada. Methods: Using de-identified primary care electronic medical records, PwT2D who had at least one healthcare touchpoint between March 1, 2018 and February 28, 2021 were analyzed by time period (baseline: 2018-19, pre-COVID-19: 2019-20, COVID-19: 2020-21) . The primary outcome measures include the number of people with at least one visit, number of people with vital measurements or lab tests, and the vital or lab results. Results: The three time periods had a similar average age and gender distribution (Table 1) . Compared to the pre-COVID-period, fewer people had any healthcare touchpoint (17% reduction) . In-person visits were reduced while more people had virtual visits. Fewer people had test results recorded during the COVID-vs. two pre-COVID-time periods, however, average results were similar across all three time periods. Conclusion: Our study described the immediate impact of the COVID-pandemic on patterns of primary care for PwT2D. While the total number people getting tests remains below pre-pandemic levels, of those who sought care, the mean A1c, LDL-c and eGFR were comparable across the three time periods. 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, Other Relationship; Diabetes Canada, Speaker's Bureau; Bausch Health, Canada, Merck & Co., Inc. S.B.Harris: Consultant; Abbott, AstraZeneca, Eli Lilly and Company, Novo Nordisk, Sanofi, Other Relationship; Abbott, AstraZeneca, Bayer Inc., Dexcom, Eli Lilly and Company, HLS Therapeutics, Janssen Pharmaceuticals, Inc., Novo Nordisk, Sanofi, Research Support; Applied Therapeutics Inc., AstraZeneca, Canadian Institutes of Health Research, Juvenile Diabetes Research Foundation (JDRF) , Novo Nordisk, Sanofi, The Lawson Foundation. I.E.Krawchenko: Speaker's Bureau; Janssen Pharmaceuticals, Inc. R.Tytus: Other Relationship; Banty , Boehringer Ingelheim International GmbH, Canadian Health Research Company, Merck & Co., Inc., Novo Nordisk, Pfizer Inc. J.Hahn: Employee; Novo Nordisk Canada Inc. A.R.Liu: Employee; Novo Nordisk A/S, Novo Nordisk Canada Inc. Y.Wang: Other Relationship; Novo Nordisk Canada Inc. S.Golden: Other Relationship; Novo Nordisk Canada Inc. R.Goldenberg: Consultant; IQVIA Inc., Speaker's Bureau; Amgen Canada, AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Novo Nordisk Canada Inc., Sanofi.

Background: COVID-public health measures may have impacted diabetes care through delayed care and reduced medication access. This study describes antihyperglycemic medication prescription patterns among adults with type 2 diabetes (T2D) before and during the COVID-pandemic in Canada. Methods: Using IQVIA’s longitudinal pharmacy based prescription data, antihyperglycemic prescriptions from March 1, 2018 to February 28, 2021 were analyzed among adults who had ≥1 prescription for a non-insulin antihyperglycemic drug. The number of people who: 1) had antihyperglycemic prescriptions,2) were newly started on antihyperglycemic drugs, and3) were newly diagnosed with T2D (inferred from prescriptions) were reported. Results: The number of people who had ≥1 antihyperglycemic prescription was comparable in the year of the COVID-pandemic (March 2020 to February 2021) and the year prior (March 20to February 2020) . The number of people who newly initiated a GLP-1RA, SGLT2i or second-generation basal insulin analogue decreased for the first few months of the pandemic (April to September 2020) with recovery thereafter. The number of people who were newly diagnosed with T2D decreased by 7% in the COVID-year. Conclusion: Fewer people initiated newer antihyperglycemic medications and fewer people were newly diagnosed with T2D in the first few months for the pandemic which may reflect reduced health care access. 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, Other Relationship; Diabetes Canada, Speaker's Bureau; Bausch Health, Canada, Merck & Co., Inc. R.Goldenberg: Consultant; IQVIA Inc., Speaker's Bureau; Amgen Canada, AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Novo Nordisk Canada Inc., Sanofi. I.E.Krawchenko: Speaker's Bureau; Janssen Pharmaceuticals, Inc. R.Tytus: Other Relationship; Banty , Boehringer Ingelheim International GmbH, Canadian Health Research Company, Merck & Co., Inc., Novo Nordisk, Pfizer Inc. J.Hahn: Employee; Novo Nordisk Canada Inc. A.R.Liu: Employee; Novo Nordisk A/S, Novo Nordisk Canada Inc. T.Lan: Other Relationship; Novo Nordisk Canada Inc. B.Millson: Other Relationship; Novo Nordisk Canada Inc. S.B.Harris: Consultant; Abbott, AstraZeneca, Eli Lilly and Company, Novo Nordisk, Sanofi, Other Relationship; Abbott, AstraZeneca, Bayer Inc., Dexcom, Eli Lilly and Company, HLS Therapeutics, Janssen Pharmaceuticals, Inc., Novo Nordisk, Sanofi, Research Support; Applied Therapeutics Inc., AstraZeneca, Canadian Institutes of Health Research, Juvenile Diabetes Research Foundation (JDRF) , Novo Nordisk, Sanofi, The Lawson Foundation.

Introduction: Hypoglycemia after BI initiation can negatively impact patient adherence to titration and glycemic target achievement. We report on 2 surveys to better understand patient and physician perspectives/experiences of hypoglycemia during BI titration. Methods: Adults with T2D and ≥2 claims (≥30 days apart in last 12 months) in the Optum Research Database who initiated BI (February-April 2021) , and physicians who treated ≥30 patients with T2D, ≥1 initiating BI (October 2020-March 2021) , completed a mailed survey. Results: Responders were 416 patients (51% male, 71% white, mean age 70 years, 72% >years T2D duration) and 386 physicians (45% general practice) . Most physicians reported discussing hypoglycemia signs/symptoms (93%) and how to titrate BI in response to blood glucose (BG) levels (81%) with patients. Among patients who experienced hypoglycemia (49%; Table) , 57% felt very/extremely confident titrating BI during hypoglycemia. Only 35% met fasting BG (FBG) targets. Diabetes Treatment Satisfaction Questionnaire hypoglycemia score (1.34/6) suggests patients felt hypoglycemia was infrequent. Conclusion: While physicians educate patients on hypoglycemia awareness and BI titration, nearly half of patients surveyed experienced hypoglycemia during titration, and only a third met FBG targets, suggesting new strategies and tools are needed for effective BI titration. Disclosure S.B.Harris: Consultant; Abbott, AstraZeneca, Eli Lilly and Company, Novo Nordisk, Sanofi, Other Relationship; Abbott, AstraZeneca, Bayer Inc., Dexcom, Eli Lilly and Company, HLS Therapeutics, Janssen Pharmaceuticals, Inc., Novo Nordisk, Sanofi, Research Support; Applied Therapeutics Inc., AstraZeneca, Canadian Institutes of Health Research, Juvenile Diabetes Research Foundation (JDRF) , Novo Nordisk, Sanofi, The Lawson Foundation. K.Mohammedi: Board Member; Lilly, Novo Nordisk, Sanofi, Research Support; Cyclerion Therapeutics, Inc., Speaker's Bureau; Abbott, AstraZeneca. M.Bertolini: Employee; Sanofi. V.Walker: Consultant; Sanofi-Aventis U.S. M.H.Carlyle: None. F.L.Zhou: Employee; Sanofi, Stock/Shareholder; Sanofi. 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. J.E.Anderson: Advisory Panel; Abbott Diabetes, Consultant; AstraZeneca, Bayer AG, Boehringer Ingelheim International GmbH, Gelesis, Novo Nordisk, Sanofi, Speaker's Bureau; Eli Lilly and Company. Funding Sanofi

Iatrogenic non-severe hypoglycemia (NSH) is a common and known precursor of severe hypoglycemia. Still, virtually no valid risk estimators exist to predict daytime and nocturnal NSH (NSDH, NSNH) in the general US population with diabetes. To redress this gap, we analyzed primary, self-reported data from the 1-year, prospective iNPHORM study. Adults (18-90 years old) with insulin- and/or secretagogue-treated type 1 or 2 diabetes (T1D, T2D) were recruited from a US-wide probability-based internet panel. Twelve monthly emailed questionnaires assessed NSH risk. Prognostic models were built for recurrent 30-day NSDH and NSNH using negative binomial and machine learning penalized regression with lasso. Missing data were multiply imputed with chained equations. N=986 were analyzed (T1D: 17%; age: 51 [SD: 14.3] years; male: 49.6%; T1D/T2D duration: 12 [IQR: 14] years; retention rate: 86.2%) . Among T2D respondents, 38% were on insulin alone, 38% secretagogues alone, and 24% insulin plus secretagogues. Follow-up incidence proportions and 30-day rates of NSDH and NSNH were 79.6% (95% CI: 77.0-82.0%) and 1.70 (95% CI: 1.59-1.82) , and 53.7% (95% CI: 50.5-56.7%) and 0.69 (95% CI: 0.64-0.75) , respectively. Risks of 30-day NSDH and NSNH increased with insulin+secretagogue therapy; A1C≤7%; insulin pump, continuous glucose monitoring, beta blockers, and antibiotics use; decreased number of medications; T1D and diabetes education; increased past severe hypoglycemia requiring healthcare; chronic kidney disease; depression; food insecurity; lack of insurance; younger age; female sex; and White race; risks decreased with A1C≥7.1%, cognitive impairment, hypoglycemia unawareness, and insurance. As well, higher income predicted NSNH risk. The optimism adjusted c-statistics for NSDH and NSNH risks were 0.78 and 0.77, respectively. As the first US study to prospectively estimate real-world NSDH and NSNH risk, iNPHORM provides important insight into individual-level event detection and prevention. Disclosure A.Ratzki-leewing: Consultant; Eli Lilly and Company, Other Relationship; Sanofi. S.B.Harris: Consultant; Abbott, AstraZeneca, Eli Lilly and Company, Novo Nordisk, Sanofi, Other Relationship; Abbott, AstraZeneca, Bayer Inc., Dexcom, Eli Lilly and Company, HLS Therapeutics, Janssen Pharmaceuticals, Inc., Novo Nordisk, Sanofi, Research Support; Applied Therapeutics Inc., AstraZeneca, Canadian Institutes of Health Research, Juvenile Diabetes Research Foundation (JDRF) , Novo Nordisk, Sanofi, The Lawson Foundation. J.E.Black: None. G.Zou: None. S.Webster-bogaert: None. B.L.Ryan: None. Funding Sanofi Global

Patients' satisfaction is a key determinant of treatment adherence and persistence, for optimal management of T2D. ATOS, a 12-month prospective observational study conducted in Asia, Middle East, North Africa, Latin America, and Eastern Europe, showed that initiation of Gla-300 in insulin-naïve people with T2D resulted in improved glycemic control with low rates of hypoglycemia. This analysis evaluated changes in treatment satisfaction and health status among participants. Data was collected using PRO questionnaires - Diabetes Treatment Satisfaction Questionnaire status (DTSQs) and change versions (DTSQc) , EuroQoL 5-dimension scale version 3L (EQ-5D-3L) at baseline, Month 3, 6 and 12. Overall, 3931 participants completed the questionnaires. Mean ±SD age was 57.5 ±10.6 years, duration of diabetes was 10.1 ±6.2 years and baseline HbA1c was 9.3 ±1.0 %. Treatment satisfaction improved over time (DTSQs score of 21.7 at baseline to 29.8 and 31.3 at Month 6 and 12, respectively) and perceived frequency of hyperglycemia decreased over 12 months. DTSQc results were aligned with DTSQs. EQ-5D-3L results showed that proportion of people with better health status increased over time (Table) . Results showed that initiating Gla-300 in insulin-naïve people with T2D across multiple geographic regions improved treatment satisfaction and health status. Disclosure N.Khan: None. G.R.Galstyan: n/a. A.Tirosh: Advisory Panel; Abbott Diagnostics, AstraZeneca, Boehringer Ingelheim International GmbH, Merck & Co., Inc., Novo Nordisk, Sanofi, Consultant; Bayer AG, DreaMed Diabetes, Ltd., Research Support; Medtronic, Speaker's Bureau; Eli Lilly and Company. A.Bhansali: None. H.Vargas-uricoechea: Advisory Panel; Sanofi, Speaker's Bureau; Abbott. S.B.Harris: Consultant; Abbott, AstraZeneca, Eli Lilly and Company, Novo Nordisk, Sanofi, Other Relationship; Abbott, AstraZeneca, Bayer Inc., Dexcom, Eli Lilly and Company, HLS Therapeutics, Janssen Pharmaceuticals, Inc., Novo Nordisk, Sanofi, Research Support; Applied Therapeutics Inc., AstraZeneca, Canadian Institutes of Health Research, Juvenile Diabetes Research Foundation (JDRF) , Novo Nordisk, Sanofi, The Lawson Foundation. A.Roborel de climens: Employee; IQVIA Inc., Sanofi. M.N.Mabunay: Employee; Sanofi. M.Coudert: Employee; Sanofi. V.Pilorget: None. Funding Sanofi

Background: First Nations (FN) peoples in Canada face spiraling rates of type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD). Data on the extent of CVD risk-factor management in FN peoples with T2DM in Canada are scarce. Methods: A T2DM registry with data from 7 FN communities in Canada was utilized to identify individuals eligible for primary and secondary CVD prevention. Proportions of individuals meeting clinical practice guideline–specified targets (hemoglobin A1c ≤7.0%; blood pressure ≤130/80 mm Hg; low-density lipoprotein ≤2 mmol/L) were calculated. Prescription of recommended cardioprotective medications (antithrombotic medication, lipid-lowering agents, renin-angiotensin-aldosterone system inhibitors, and beta-blockers) among those with CVD was assessed. χ2 tests were employed to evaluate differences between CVD prevention groups and sexes. Results: Of the 2098 individuals in the registry, 18% had documented CVD (female: male = 1.12). Overall

Objective To examine diabetes remission following a short-term intensive metabolic intervention combining lifestyle and glucose-lowering approaches. Methods We conducted an open-label, randomized controlled trial in 154 patients with type 2 diabetes up to 8 years in duration on 0 to 2 glucose-lowering medications. Participants were randomized to (a) a 12-week intensive intervention comprising lifestyle approaches and treatment with insulin glargine, metformin, and dapagliflozin or (b) standard diabetes care. At 12 weeks, diabetes medications were discontinued in participants with hemoglobin A1c (HbA1C) Results The primary outcome was achieved in 19 (24.7%) intervention group participants and 13 (16.9%) control group participants at 24 weeks (relative risk [RR] 1.5; 95% confidence interval [CI], 0.8-2.7). The relative risks of remission at 36, 48, and 64 weeks were 2.4 (95% CI, 1.2-5.0), 2.1 (95% CI, 1.0-4.4), and 1.8 (95% CI, 0.7-4.7), respectively. In an exploratory analysis, the intervention reduced the hazard of diabetes relapse with overt hyperglycemia by 43% (hazard ratio 0.57; 95% CI, 0.39-0.81). Conclusions Our primary outcome of diabetes remission at 24 weeks was not statistically significantly different. However, our overall results suggest that some patients with early type 2 diabetes are able to achieve sustained diabetes remission following a short-term intensive intervention. Further studies are needed to optimize the combined therapeutic approach used.

Primary care providers are well-positioned to help patients with type 2 diabetes achieve glycemic control while reducing their risks of serious complications such as atherosclerotic cardiovascular disease, heart failure, and chronic kidney disease. Recent outcomes trials of glucagon-like peptide 1 receptor agonists and sodium– glucose cotransporter 2 inhibitors have revealed that these agents offer cardiorenal benefits beyond their glucose-lowering effects. The American Diabetes Association and the European Association for the Study of Diabetes now recommend a person-centered approach to type 2 diabetes treatment through which a patient’s multimorbidities, preferences, characteristics, and barriers are considered alongside A1C in individualizing the diabetes management plan. Here, we review the evidence supporting this guidance and describe how to implement the new holistic approach. Research has demonstrated the potential for offering a continuum of benefit from primary through tertiary prevention of microvascular and macrovascular disease while also achieving glycemic targets. The new outcomes-based guidelines provide a roadmap for integrating this newfound knowledge into clinical practice.

BACKGROUND Hypoglycemia prognostic models contingent on prospective, self-reported survey data offer a powerful avenue for determining real-world event susceptibility and interventional targets. OBJECTIVE This protocol describes the design and implementation of the 1-year iNPHORM (Investigating Novel Predictions of Hypoglycemia Occurrence Using Real-world Models) study, which aims to measure real-world self-reported severe and nonsevere hypoglycemia incidence (daytime and nocturnal) in American adults with type 1 or 2 diabetes mellitus prescribed insulin and/or secretagogues, and develop and internally validate prognostic models for severe, nonsevere daytime, and nonsevere nocturnal hypoglycemia. As a secondary objective, iNPHORM aims to quantify the effects of different antihyperglycemics on hypoglycemia rates. METHODS iNPHORM is a prospective, 12-wave internet-based panel survey that was conducted across the United States. Americans (aged 18-90 years) with self-reported type 1 or 2 diabetes mellitus prescribed insulin and/or secretagogues were conveniently sampled via the web from a pre-existing, closed, probability-based internet panel (sample frame). A sample size of 521 baseline responders was calculated for this study. Prospective data on hypoglycemia and potential prognostic factors were self-assessed across 14 closed, fully automated questionnaires (screening, baseline, and 12 monthly follow-ups) that were piloted using semistructured interviews (n=3) before fielding; no face-to-face contact was required as part of the data collection. Participant responses will be analyzed using multivariable count regression and machine learning techniques to develop and internally validate prognostic models for 1-year severe and 30-day nonsevere daytime and nocturnal hypoglycemia. The causal effects of different antihyperglycemics on hypoglycemia rates will also be investigated. RESULTS Recruitment and data collection occurred between February 2020 and March 2021 (ethics approval was obtained on December 17, 2019). A total of 1694 participants completed the baseline questionnaire, of whom 1206 (71.19%) were followed up for 12 months. Most follow-up waves (10,470/14,472, 72.35%) were completed, translating to a participation rate of 179% relative to our target sample size. Over 70.98% (856/1206) completed wave 12. Analyses of sample characteristics, quality metrics, and hypoglycemia incidence and prognostication are currently underway with published results anticipated by fall 2022. CONCLUSIONS iNPHORM is the first hypoglycemia prognostic study in the United States to leverage prospective, longitudinal self-reports. The results will contribute to improved real-world hypoglycemia risk estimation and potentially safer, more effective clinical diabetes management. CLINICALTRIAL ClinicalTrials.gov NCT04219514; https://clinicaltrials.gov/ct2/show/NCT04219514 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/33726

Main objectiveTo determine how and to what extent COVID-19 has affected real-world, self-reported glycaemic management in Americans with type 1 or type 2 diabetes taking insulin and/or secretagogues, with or without infection.DesignA cross-sectional substudy using data from the Investigating Novel Predictions of Hypoglycemia Occurrence using Real-world Models panel survey.SettingUSA.ParticipantsAmericans 18–90 years old with type 1 or 2 diabetes taking insulin and/or secretagogues were conveniently sampled from a probability-based internet panel.Primary outcome measureA structured, COVID-19-specific questionnaire was administered to assess the impact of the pandemic (irrespective of infection) on socioeconomic, behavioural/clinical and psychosocial aspects of glycaemic management.ResultsData from 667 respondents (type 1 diabetes: 18%; type 2 diabetes: 82%) were analysed. Almost 25% reported A1c values ≥8.1%. Rates of severe and non-severe hypoglycaemia were 0.68 (95% CI 0.5 to 0.96) and 2.75 (95% CI 2.4 to 3.1) events per person-month, respectively. Ten respondents reported a confirmed or probable COVID-19 diagnosis. Because of the pandemic, 24% of respondents experienced difficulties affording housing; 28% struggled to maintain sufficient food to avoid hypoglycaemia; and 19% and 17% reported challenges accessing diabetes therapies and testing strips, respectively. Over one-quarter reported issues retrieving antihyperglycaemics from the pharmacy and over one-third reported challenges consulting with diabetes providers. The pandemic contributed to therapeutic non-adherence (14%), drug rationing (17%) and reduced monitoring (16%). Many struggled to keep track, and in control, of hypoglycaemia (12%–15%) and lacked social support to help manage their risk (19%). Nearly half reported decreased physical activity. Few statistically significant differences were observed by diabetes type.ConclusionsCOVID-19 was found to cause substantial self-reported deficiencies in glycaemic management. Study results signal the need for decisive action to restabilise routine diabetes care in the USA.Trial registration numberNCT04219514.

Therapeutic inertia is a prevalent problem in people with type 2 diabetes in primary care and affects clinical outcomes. It arises from a complex interplay of patient-, clinician-, and health system–related factors. Ultimately, clinical practice guidelines have not made an impact on improving glycemic targets over the past decade. A more proactive approach, including focusing on optimal combination agents for early glycemic durability, may reduce therapeutic inertia and improve clinical outcomes.

Achieving target glycaemic control is essential in people with diabetes to minimize the risk of long‐term complications, and many people with type 2 diabetes will ultimately require basal insulin (BI) therapy to achieve their individualized glycaemic targets. Usually, the first 12 weeks following initiation of BI therapy represents the period when the greatest dose increases and glycaemic reductions occur. Effective glycaemic control combined with minimizing the risk of hypoglycaemia is important to enable the achievement of glycaemic control in the longer term. However, substantial therapeutic inertia exists in clinical practice, both in initiation and up‐titration of BI, owing to patient‐, physician‐ and healthcare system‐related barriers, including fear of hypoglycaemia and the perception of a burdensome regimen. The more prolonged duration of action, reduced glycaemic variability and lower risk of hypoglycaemia seen with second‐generation versus first‐generation BI analogues may help alleviate patients’ and physicians’ concerns and facilitate titration. In turn, optimal BI titration and subsequent metabolic benefits may help improve therapy adherence and self‐management. This review details the clinical implications of prompt titration of BI to achieve early glycaemic control, and the importance of minimizing hypoglycaemia risk within the initial titration period. Facilitation of patients’ self‐management of BI is also addressed.

Aim To further investigate glycaemic control and hypoglycaemia in BRIGHT, focusing on the titration period. Materials and Methods BRIGHT was a multicentre, open‐label, randomized, active‐controlled, two‐arm, parallel‐group, 24‐week study in insulin‐naïve patients with uncontrolled type 2 diabetes initiated on glargine 300 U/mL (Gla‐300) (N = 466) or degludec (IDeg‐100) (N = 463). Predefined efficacy and safety outcomes were investigated during the initial 12‐week titration period. In addition, patients’ characteristics and clinical outcomes were assessed descriptively, stratified by confirmed (≤3.9 mmol/L) hypoglycaemia incidence during the initial titration period. Results At week 12, HbA1c was comparable between Gla‐300 (7.32%) and IDeg‐100 (7.23%), with similar least squares (LS) mean reductions from baseline (−1.37% and − 1.39%, respectively; LS mean difference of 0.02; 95% confidence interval: −0.08 to 0.12). Patients who experienced hypoglycaemia during the initial titration period had numerically greater HbA1c reductions by week 12 than patients who did not (−1.46% vs. −1.28%), and higher incidence of anytime (24 hours; 73.3% vs. 35.7%) and nocturnal (00:00–06:00 hours; 30.0% vs. 11.9%) hypoglycaemia between weeks 13–24. Conclusions The use of Gla‐300 resulted in similar glycaemic control as IDeg‐100 during the initial 12‐week titration period of the BRIGHT study, when less anytime (24 hours) hypoglycaemia with Gla‐300 versus IDeg‐100 has been reported. Experiencing hypoglycaemia shortly after initiating Gla‐300 or IDeg‐100 may be associated with hypoglycaemia incidence in the longer term, potentially impacting glycaemic management.

Summary: Background: Historical, colonial, and racist policies continue to influence the health of Indigenous people, and they continue to have higher rates of chronic diseases and reduced life expectancy compared with non-Indigenous people. We determined factors accounting for variations in cardiovascular risk factors among First Nations communities in Canada. Methods: Men and women (n=1302) aged 18 years or older from eight First Nations communities participated in a population-based study. Questionnaires, physical measures, blood samples, MRI of preclinical vascular disease, and community audits were collected. In this cross-sectional analysis, the main outcome was the INTERHEART risk score, a measure of cardiovascular risk factor burden. A multivariable model was developed to explain the variations in INTERHEART risk score among communities. The secondary outcome was MRI-detected carotid wall volume, a measure of subclinical atherosclerosis. Findings: The mean INTERHEART risk score of all communities was 17·2 (SE 0·2), and more than 85% of individuals had a risk score in the moderate to high risk range. Subclinical atherosclerosis increased significantly across risk score categories (p

Context Chronic inflammation arising from adipose tissue macrophage (ATM) activation may be central in type 2 diabetes etiology. Our objective was to assess the longitudinal associations of soluble CD163 (sCD163), a novel biomarker of ATM activation, with insulin sensitivity, β-cell function, and dysglycemia in high-risk subjects. Methods Adults at risk for type 2 diabetes in the Prospective Metabolism and Islet Cell Evaluation (PROMISE) study had 3 assessments over 6 years (n = 408). Levels of sCD163 were measured using fasting serum. Insulin sensitivity was assessed by HOMA2-%S and the Matsuda index (ISI). β-cell function was determined by insulinogenic index (IGI) over HOMA-IR and insulin secretion-sensitivity index-2 (ISSI-2). Incident dysglycemia was defined as the onset of impaired fasting glucose, impaired glucose tolerance, or type 2 diabetes. Generalized estimating equations (GEE) evaluated longitudinal associations of sCD163 with insulin sensitivity, β-cell function, and incident dysglycemia adjusting for demographic and lifestyle covariates. Areas under receiver-operating-characteristic curve (AROC) tested whether sCD163 improved dysglycemia prediction in a clinical model. Results Longitudinal analyses showed significant inverse associations between sCD163 and insulin sensitivity (% difference per standard deviation increase of sCD163 for HOMA2-%S (β = −7.01; 95% CI, −12.26 to −1.44) and ISI (β = −7.60; 95% CI, −11.09 to −3.97) and β-cell function (ISSI-2 (β = −4.67; 95 %CI, −8.59 to −0.58) and IGI/HOMA-IR (β = −8.75; 95% CI, −15.42 to −1.56)). Increased sCD163 was associated with greater risk for incident dysglycemia (odds ratio = 1.04; 95% CI, 1.02-1.06; P < 0.001). Adding sCD163 data to a model with clinical variables improved prediction of incident dysglycemia (AROC=0.6731 vs 0.638; P < 0.05). Conclusions sCD163 was longitudinally associated with core disorders that precede the onset of type 2 diabetes.

Circulating fatty acids (FA) derived largely from dairy consumption have most commonly been measured in total human serum or phospholipid (PL) fractions, and have been used as validated biomarkers of dairy intake in a growing number of epidemiological studies. Nevertheless, measurement and characterization of a wider spectrum of FA biomarkers of dairy across the four major serum lipid fractions is lacking. This study aimed to (1) quantify FA biomarkers of dairy in PL, triacylglycerol (TAG), cholesteryl ester (CE), and unesterified fatty acid (FFA) serum lipid fractions; and (2) identify potential demographic and metabolic factors that may modify the proportions of these FA across serum fractions. Baseline data from 444 adults in the PROMISE cohort were analyzed. FA biomarkers, 15:0, t16:1n-7, 18:2-c9,t11, and t18:1n-7 were quantified from serum. Dairy intake was estimated using the validated Canadian Diet History Questionnaire. Our results show that t18:1n-7 was the most abundant FA biomarker in all fractions except CE, where 18:2-c9,t11 was the most abundant. Positive correlations within fractions, and across FA in the PL, CE, and FFA fractions were found, however, TAG FA were negatively correlated with the other fractions. PL and CE FA were positively associated with dairy intake, and negatively associated with markers of dysmetabolism while, in contrast, these markers were predictors of higher TAG dairy FA. This study is the first to demonstrate distinct proportions of dairy FA in different serum lipid fractions. PL and CE FA marked dairy intake in this cohort, while TAG FA appeared to be markers of dysmetabolism.

Hypoglycemia is one of the most common adverse events for people living with type 1 or type 2 diabetes. To gain a deeper understanding of patients’ emotions regarding hypoglycemia, we conducted a descriptive qualitative study. Purposive sampling was used to recruit participants for a 30- to 45-minute semi-structured interview. The 16 participants included both women and men with either type 1 or type 2 diabetes, with a mean age of 53 years and mean time since diagnosis of 21 years. All participants had experienced more than one hypoglycemia event in the past year, ranging from nonsevere to severe. Data collection and analysis occurred in an iterative manner. Individual and team analyses of interviews were conducted to identify overarching themes and sub-themes. Thematic analysis revealed the unique interconnection among the emotions experienced by participants, including fear, anxiety, frustration, confidence, and hope. Time, experience, and reflection helped to build participants’ confidence in their ability to manage a hypoglycemia event. Patients’ emotions regarding hypoglycemia provide valuable insights into life with diabetes. Although hypoglycemia continues to evoke feelings of fear and anxiety, the role of hope may temper these emotions. Understanding the complex interplay of emotions concerning hypoglycemia can guide health care providers in improving clinical practice and promoting patient-centered interventions. Ultimately, health care providers can build patients’ hypoglycemia-related confidence by using a strengths-based approach.

OBJECTIVE To investigate the efficacy, safety, and tolerability of oral semaglutide added to insulin with or without metformin. RESEARCH DESIGN AND METHODS Patients with type 2 diabetes uncontrolled on insulin with or without metformin were randomized to oral semaglutide 3 mg (N = 184), 7 mg (N = 182), or 14 mg (N = 181) or to placebo (N = 184) in a 52-week, double-blind trial. End points were change from baseline to week 26 in HbA1c (primary) and body weight (confirmatory secondary). Two estimands were defined: treatment policy (effect regardless of trial product discontinuation or rescue medication) and trial product (effect assuming trial product continuation without rescue medication) in randomized patients. RESULTS Oral semaglutide was superior to placebo in reducing HbA1c (estimated treatment difference [ETD] –0.5% [95% CI –0.7, –0.3], –0.9% [–1.1, –0.7], and –1.2% [–1.4, –1.0] for 3, 7, and 14 mg, respectively; P < 0.001) and body weight (ETD −0.9 kg [95% CI −1.8, −0.0], −2.0 kg [−3.0, −1.0], and −3.3 kg [−4.2, −2.3]; P = 0.0392 for 3 mg, P ≤ 0.0001 for 7 and 14 mg) at week 26 (treatment policy estimand). Significantly greater dose-dependent HbA1c and body weight reductions versus placebo were achieved with oral semaglutide at weeks 26 and 52 (both estimands). The most frequent adverse event with oral semaglutide was nausea (11.4–23.2% of patients vs. 7.1% with placebo; mostly mild to moderate). CONCLUSIONS Oral semaglutide was superior to placebo in reducing HbA1c and body weight when added to insulin with or without metformin in patients with type 2 diabetes. The safety profile was consistent with other glucagon-like peptide 1 receptor agonists.

Hypoglycaemia is a common side‐effect of diabetes therapies, particularly insulin, and imposes a substantial burden on individuals and healthcare systems. Consequently, regulatory approval of newer basal insulin (BI) therapies has relied on demonstration of a balance between achievement of good glycaemic control and less hypoglycaemia. Randomized controlled trials (RCTs) are the gold standard for assessing efficacy and safety, including hypoglycaemia risk, of BIs and are invaluable for obtaining regulatory approval. However, their highly selected patient populations and their conditions lead to results that may not be representative of real‐life situations. Real‐world evidence (RWE) studies are more representative of clinical practice, but they also have limitations. As such, data both from RCTs and RWE studies provide a fuller picture of the hypoglycaemia risk with BI therapies. However, substantial differences exist in the way hypoglycaemia is reported across these studies, which confounds comparisons of hypoglycaemia frequency among different BIs. This problem is ongoing and persists in recent trials of second‐generation BI analogues. Although they provide a lower risk of hypoglycaemia when compared with earlier BIs, they do not eliminate it. This review describes differences in the way hypoglycaemia is reported across RCTs and RWE studies of second‐generation BI analogues and examines potential reasons for these differences. For studies of BIs, there is a need to standardize aspects of design, analysis and methods of reporting to better enable interpretation of the efficacy and safety of such insulins among studies; such aspects include length of follow‐up, glycaemic targets, hypoglycaemia definitions and time intervals for determining nocturnal events.

Aims: Clinical inertia behaviour affects family physicians managing chronic disease such as diabetes. Literature addressing clinical inertia in the management of hypoglycemia is scarce. The objectives of this study were to create a measurement for physician clinical inertia in managing hypoglycemia (ClinInert_InHypoDM), and to determine physicians’ characteristics associated with clinical inertia. Methods: The study was a secondary analysis of data provided by family physicians from the InHypo-DM Study, applying exploratory factor analysis. Principal axis factoring with an Oblimin rotation was employed to detect underlying factors associated with physician behaviors. Multiple linear regression was used to determine association between the ClinInert_InHypoDM scores and physician characteristics. Results: Factor analysis identified a statistically sound 12-item one-factor scale for clinical inertia behavior. No statistically significant differences in clinical inertia score for the studied independent variables were found. Conclusions: This study provides a scale for assessing clinical inertia in the management of hypoglycemia. Further testing this scale in other family physician populations will provide deeper understanding about the characteristics and factors that influence clinical inertia. The knowledge derived from better understanding clinical inertia in primary care has potential to improve outcomes for patients with diabetes.

Background: Individual and societal determinants can affect the need and propensity for healthcare utilization (HCU) following diabetes-related severe hypoglycemia (SH). This is the first US study to explore the real-world risk factors of HCU- versus non HCU-based SH. Methods: Data were collected online from a generalized cohort of Americans (≥18 years old) with type 1 or type 2 diabetes (T1D, T2D) on insulin and/or secretagogues. Multivariable logistic regression using backward selection was performed to identify the socio-demographic/clinical risk factors of past-year HCU- versus non HCU-based SH (daytime/nocturnal SH resulting in hospital or paramedical services). Results: Results are based on 642 (T1D: 22.7%; female: 46.3%) of 1694 baseline respondents who experienced ≥1 SH events (past year). People with T1D were 40.9 (SD:12.5) years old, while those with T2D were 45.4 (SD: 13.3) years old. Among T2D respondents, 42.5% were on insulin and secretagogues, 31.1% were on insulin alone, and 26.4% on secretagogues alone. Almost half (44.6%) of participants (T1D: 29.9%; T2D: 49.0%) reported ≥1 HCU-based SH events (past year). In the final backward logistic model, the odds of past-year HCU-based SH decreased significantly with female sex, increasing age, decreasing income, and suburban or rural (versus urban) living. Diabetes type did not have an independent effect. However, for individuals on combination insulin-secretagogue therapy, the adjusted odds of HCU-based SH were 2- and 3-times that of those on insulin alone and secretagogues alone, respectively. High A1C (versus Conclusion: Our study reveals several factors that can promote or reduce the odds of HCU-based SH. Therapeutic optimizations to mitigate non-essential HCU should prioritize patients on combination insulin-secretagogue therapy and those with poor glycemic control. Disclosure A. Ratzki-leewing: Consultant; Self; Eli Lilly and Company, Novo Nordisk, Other Relationship; Self; Sanofi. J. E. Black: None. B. L. Ryan: None. G. Zou: None. S. B. Harris: Advisory Panel; Self; Abbott Diabetes, Abvance Therapeutics, HLS Therapeutics Inc., Lilly Diabetes, Novo Nordisk A/S, Consultant; Self; Boehringer Ingelheim (Canada) Ltd., mdBriefCase, Other Relationship; Self; American Diabetes Association, AstraZeneca, Novo Nordisk Canada Inc., Sanofi. Funding Sanofi Global

Background: Diabetes remission due to non-surgical approaches has not been well studied. We investigated induction of diabetes remission following a short-term treatment with insulin glargine, lixisenatide and metformin and changes in exercise and dietary behaviours. Methods: We randomized 160 individuals with type 2 diabetes to (i) 12-week intensive treatment with insulin glargine, lixisenatide, metformin and lifestyle approaches or (ii) standard glycemic management. At 12 weeks, diabetes medications were stopped in patients with HbA1C Results: The intervention significantly reduced the hazard of diabetes relapse (HR 0.57, 95% CI 0.40-0.81; p=0.002). The proportion of participants with diabetes remission was significantly higher in the intervention group compared to the control group at 24 weeks (38% vs. 20%; relative risk RR 1.92 (1.14-3.24)) and at 36 weeks (32% vs. 17%; RR 1.83 (1.03-3.26)), but not at 48 and 64 weeks (RR 1.88 (1.00-3.53) and 2.05 (0.98-4.29), respectively). Conclusion: Short-term intensive treatment targeting normoglycemia and weight loss with insulin glargine, lixisenatide, metformin and lifestyle changes can induce sustained remission of type 2 diabetes. Disclosure N. Mcinnes: Other Relationship; Self; Merck & Co., Inc., Novo Nordisk, Sanofi. J. Yale: Advisory Panel; Self; Abbott, AstraZeneca, Boehringer Ingelheim (Canada) Ltd., Eli Lilly and Company, Novo Nordisk Canada Inc., Sanofi, Research Support; Self; Bayer Inc., Speaker’s Bureau; Self; Dexcom, Inc., Medtronic, Merck & Co., Inc., Omnipod. F. Sultan: Employee; Self; Abbott Diabetes. A. C. Smith: None. R. E. Otto: None. D. Sherifali: None. Y. Liu: None. H. C. Gerstein: Advisory Panel; Self; Novo Nordisk Inc., Pfizer Inc., Sanofi, Consultant; Self; Abbott, Covance Inc., Eli Lilly and Company, Kowa Company, Ltd., Sanofi, Other Relationship; Self; Boehringer Ingelheim (Canada) Ltd., DKSH, Eli Lilly and Company, Sanofi, Zuellig, Research Support; Self; AstraZeneca, Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk Inc., Sanofi. Remit-iglarlixi collaborative group: n/a. S. Hall: None. H. A. Lochnan: Research Support; Self; Novo Nordisk Inc., Sanofi. S. B. Harris: Advisory Panel; Self; Abbott Diabetes, Abvance Therapeutics, HLS Therapeutics Inc., Lilly Diabetes, Novo Nordisk A/S, Consultant; Self; Boehringer Ingelheim (Canada) Ltd., mdBriefCase, Other Relationship; Self; American Diabetes Association, AstraZeneca, Novo Nordisk Canada Inc., Sanofi. Z. Punthakee: Advisory Panel; Self; Abbott, AstraZeneca, Boehringer Ingelheim (Canada) Ltd., Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Novo Nordisk, Sanofi, Research Support; Self; AstraZeneca, Lexicon Pharmaceuticals, Inc., Novo Nordisk. R. J. Sigal: Advisory Panel; Self; Novo Nordisk, Research Support; Self; Lexicon Pharmaceuticals, Inc., Novo Nordisk. I. Hramiak: Advisory Panel; Self; AstraZeneca, Bayer Inc., BI-Lilly Joint Venture (Boehringer Ingelheim and Eli Lilly), Dexcom, Inc., Insulet Corporation, Medtronic, Research Support; Self; Eli Lilly and Company, Novo Nordisk, Sanofi. M. Azharuddin: Consultant; Self; Novo Nordisk Canada Inc. J. F. Liutkus: Advisory Panel; Self; Novo Nordisk Canada Inc., Research Support; Self; Bayer Inc., Boehringer Ingelheim (Canada) Ltd., IQVIA, Kowa Research Institute, Inc., Novo Nordisk Canada Inc., Sanofi, Speaker’s Bureau; Self; Novo Nordisk Canada Inc., Stock/Shareholder; Self; Bayer Inc., Novo Nordisk, Pfizer Inc., Stock/Shareholder; Spouse/Partner; Bayer Inc., Eisai Inc., Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk Canada Inc., Pfizer Inc. Funding Sanofi

The combination of basal insulin with a GLP-1 RA may be helpful for people with T2DM to achieve and maintain HbA1c targets compared with each used individually. This randomized, 26-week, multicenter Phase 3 study (NCT03767543) in people with T2DM included participants with HbA1c ≥7.5% and ≤10.5%, and on basal insulin for ≥6 months (dose of ≤40 units/day). In addition to background oral glucose lowering medications, all participants received once-daily iGlarLixi, a fixed-ratio combination given within 1 hour prior to their first meal of the day, and were randomized 1:1 with instructions to titrate daily using a 1 unit per day algorithm or the traditional once-weekly titration (2 or 4 units per week) with target FPG of 4.4 to 5.6 mmol/L (79.2 to 100.8 mg/dL). Daily titration of iGlarLixi was superior to a weekly titration for the primary endpoint of change from baseline in HbA1c at week 26. The proportion of participants experiencing ≥1 gastrointestinal event(s) (27.9% daily vs. 27.8% weekly titration) and incidence of hypoglycemic events (84% daily vs. 81% weekly titration) were similar between the two arms. In this randomized trial, a daily titration algorithm for iGlarLixi was demonstrated as a safe alternative to the traditional weekly titration, while allowing patients to reach their maintenance dose earlier. Disclosure I. Hramiak: Advisory Panel; Self; AstraZeneca, Bayer Inc., BI-Lilly Joint Venture (Boehringer Ingelheim and Eli Lilly), Dexcom, Inc., Insulet Corporation, Medtronic, Research Support; Self; Eli Lilly and Company, Novo Nordisk, Sanofi. H. C. Gerstein: Advisory Panel; Self; Novo Nordisk Inc., Pfizer Inc., Sanofi, Consultant; Self; Abbott, Covance Inc., Eli Lilly and Company, Kowa Company, Ltd., Sanofi, Other Relationship; Self; Boehringer Ingelheim (Canada) Ltd., DKSH, Eli Lilly and Company, Sanofi, Zuellig, Research Support; Self; AstraZeneca, Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk Inc., Sanofi. L. A. Leiter: Advisory Panel; Self; Abbott Diabetes, Amgen Inc., AstraZeneca, Bayer Inc., Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Esperion, Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Novartis Pharmaceuticals Corporation, Novo Nordisk, Pfizer Inc., Sanofi, Other Relationship; Self; Applied Therapeutics, Research Support; Self; Amgen Inc., AstraZeneca, Esperion, Kowa Company, Ltd., Lexicon Pharmaceuticals, Inc., Medicines Company, Novartis Pharmaceuticals Corporation, Speaker’s Bureau; Self; Amgen Inc., AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Novo Nordisk Inc. J. Yale: Advisory Panel; Self; Abbott, AstraZeneca, Boehringer Ingelheim (Canada) Ltd., Eli Lilly and Company, Novo Nordisk Canada Inc., Sanofi, Research Support; Self; Bayer Inc., Speaker’s Bureau; Self; Dexcom, Inc., Medtronic, Merck & Co., Inc., Omnipod. H. S. Bajaj: Other Relationship; Self; Eli Lilly and Company, Novo Nordisk, Research Support; Self; Amgen Inc., AstraZeneca, Boehringer Ingelheim International GmbH, Gilead Sciences, Inc., Kowa Pharmaceuticals America, Inc., Merck & Co., Inc., Sanofi, Tricida, Inc. J. A. Stewart: Employee; Self; Sanofi. M. Toutounji: Employee; Self; Sanofi. S. B. Harris: Advisory Panel; Self; Abbott Diabetes, Abvance Therapeutics, HLS Therapeutics Inc., Lilly Diabetes, Novo Nordisk A/S, Consultant; Self; Boehringer Ingelheim (Canada) Ltd., mdBriefCase, Other Relationship; Self; American Diabetes Association, AstraZeneca, Novo Nordisk Canada Inc., Sanofi. Funding Sanofi Canada

Aim: Our objective was to determine the association of adipose tissue insulin resistance with longitudinal changes in biomarkers of adipose tissue function, circulating lipids, and dysglycemia. Research design and methods: Adults at-risk for type 2 diabetes in the Prospective Metabolism and Islet Cell Evaluation (PROMISE) cohort had up to four assessments over 9 years (n=468). Adipose tissue insulin resistance was determined using a novel validated index, Adipo-IR, calculated as the product of fasting insulin and non-esterified fatty acids measured at baseline. Fasting serum was used to measure biomarkers of adipose tissue function (adiponectin and sCD163), circulating lipids (total cholesterol, HDL, LDL, TG), and systemic inflammation (Il-6 and TNF-α). Incident dysglycemia was defined as the onset of impaired fasting glucose, impaired glucose tolerance, or type 2 diabetes at follow-up. Generalized estimating equation (GEE) models were used to assess the relationship of Adipo-IR with longitudinal outcomes. Results: GEE analyses showed that elevated Adipo-IR was longitudinally associated with adipose tissue dysfunction (adiponectin: -4.20% (95%CI, -6.40 to –1.95); sCD163: 4.36% (95%CI, 1.73 – 7.06), HDL (-3.87% (95%CI, -5.15 to -2.57)) and TG (9.26% (95%CI, 5.01 to 13.69)). Adipo-IR was associated with increased risk of incident dysglycemia (OR=1.59; 95%CI, 1.09 to 2.31, per SD increase). Associations remained significant after adjustment for waist circumference, and surrogate indices for insulin resistance. There were no significant longitudinal associations of Adipo-IR with Il-6, TNF-α, total cholesterol, or LDL. Conclusion: Our findings demonstrate that adipose tissue insulin resistance is prospectively associated with adipose tissue function, HDL, TG, and incident dysglycemia.