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Oluwasolape Olawore,1 Lindsey E Turner,2,3 Michael D Evans,3 Steven G Johnson,4 Jared D Huling,2 Carolyn T Bramante,5 John B Buse,6 Til Stürmer1 On behalf of the N3C Consortium1Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; 2Division of Biostatistics and Health Data Science, University of Minnesota School of Public Health, Minneapolis, MN, USA; 3Clinical and Translational Science Institute, University of Minnesota, Minneapolis, MN, USA; 4Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA; 5Division of General Internal Medicine, Department of Medicine, University of Minnesota Medical School, Minneapolis, MN, USA; 6Division of Endocrinology, Department of Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USACorrespondence: Oluwasolape Olawore, Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, McGavran-Greenberg Hall, 135 Dauer Drive, Chapel Hill, NC, 27599, USA, Email oolawore@unc.eduBackground: Observed activity of metformin in reducing the risk of severe COVID-19 suggests a potential use of the anti-hyperglycemic in the prevention of post-acute sequelae of SARS-CoV-2 infection (PASC). We assessed the 3-month and 6-month risk of PASC among patients with type 2 diabetes mellitus (T2DM) comparing metformin users to sulfonylureas (SU) or dipeptidyl peptidase-4 inhibitors (DPP4i) users.Methods: We used de-identified patient level electronic health record data from the National Covid Cohort Collaborative (N3C) between October 2021 and April 2023. Participants were adults ≥ 18 years with T2DM who had at least one outpatient healthcare encounter in health institutions in the United States prior to COVID-19 diagnosis. The outcome of PASC was defined based on the presence of a diagnosis code for the illness or using a predicted probability based on a machine learning algorithm. We estimated the 3-month and 6-month risk of PASC and calculated crude and weighted risk ratios (RR), risk differences (RD), and differences in mean predicted probability.Results: We identified 5596 (mean age: 61.1 years; SD: 12.6) and 1451 (mean age: 64.9 years; SD 12.5) eligible prevalent users of metformin and SU/DPP4i respectively. We did not find a significant difference in risk of PASC at 3 months (RR = 0.86 [0.56; 1.32], RD = − 3.06 per 1000 [− 12.14; 6.01]), or at 6 months (RR = 0.81 [0.55; 1.20], RD = − 4.91 per 1000 [− 14.75, 4.93]) comparing prevalent users of metformin to prevalent users of SU/ DPP4i. Similar observations were made for the outcome definition using the ML algorithm.Conclusion: The observed estimates in our study are consistent with a reduced risk of PASC among prevalent users of metformin, however the uncertainty of our confidence intervals warrants cautious interpretations of the results. A standardized clinical definition of PASC is warranted for thorough evaluation of the effectiveness of therapies under assessment for the prevention of PASC.Plain Language Summary: Previous research suggests that metformin, due to its anti-viral, anti-inflammatory, and anti-thrombotic properties may reduce the risk of severe COVID-19. Given the shared etiology of COVID-19 and the post-acute sequelae of SARS-CoV-2 (PASC), and the proposed inflammatory processes of PASC, metformin may also be a beneficial preventive option. We investigated the benefit of metformin for PASC prevention in a population of type 2 diabetes mellitus patients with a COVID-19 diagnosis who were on metformin or two other anti-hyperglycemic medications prior to infection with SARS-CoV-2. Our results were consistent with a reduction in the risk of PASC with the use of metformin, however, the imprecise confidence intervals obtained warrants further investigation of this association of the potential beneficial effect of metformin for preventing PASC in patients with medication-managed diabetes.Keywords: COVID-19, Long COVID, Type 2 diabetes Mellitus, Metformin

Objective: Studies show metformin use before and during SARS-CoV-2 infection reduces severe COVID-19 and postacute sequelae of SARS-CoV-2 (PASC) in adults. Our objective was to describe the incidence of PASC and possible associations with prevalent metformin use in adults with type 2 diabetes mellitus (T2DM)., Research Design and Methods: This is a retrospective cohort analysis using the National COVID Cohort Collaborative (N3C) and Patient-Centered Clinical Research Network (PCORnet) electronic health record (EHR) databases with an active comparator design that examined metformin-exposed individuals versus nonmetformin-exposed individuals who were taking other diabetes medications. T2DM was defined by HbA1c ≥6.5 or T2DM EHR diagnosis code. The outcome was death or PASC within 6 months, defined by EHR code or computable phenotype., Results: In the N3C, the hazard ratio (HR) for death or PASC with a U09.9 diagnosis code (PASC-U09.0) was 0.79 (95% CI 0.71-0.88; P < 0.001), and for death or N3C computable phenotype PASC (PASC-N3C) was 0.85 (95% CI 0.78-0.92; P < 0.001). In PCORnet, the HR for death or PASC-U09.9 was 0.87 (95% CI 0.66-1.14; P = 0.08), and for death or PCORnet computable phenotype PASC (PASC-PCORnet) was 1.04 (95% CI 0.97-1.11; P = 0.58). Incident PASC by diagnosis code was 1.6% metformin vs. 2.0% comparator in the N3C, and 2.1% metformin vs. 2.5% comparator in PCORnet. By computable phenotype, incidence was 4.8% metformin and 5.2% comparator in the N3C and 24.7% metformin vs. 26.1% comparator in PCORnet., Conclusions: Prevalent metformin use is associated with a slightly lower incidence of death or PASC after SARS-CoV-2 infection. PASC incidence by computable phenotype is higher than by EHR code, especially in PCORnet. These data are consistent with other observational analyses showing prevalent metformin is associated with favorable outcomes after SARS-CoV-2 infection in adults with T2DM., (© 2024 by the American Diabetes Association.)

Rationale: Although recent evidence suggested that glucagon-like peptide 1 receptor agonists (GLP1RAs) might reduce the risk of asthma exacerbations, it remains unclear which subpopulations might derive the most benefit from GLP1RA treatment. Objectives: To identify characteristics of patients with asthma that predict who might benefit the most from GLP1RA treatment using real-world data. Methods: We implemented an active-comparator, new-user design analysis using commercially ensured patients 18-65 years of age from MarketScan data for 2007-2019 and identified two cohorts: GLP1RAs versus thiazolidinediones and GLP1RAs versus sulfonylureas. The outcome was acute exacerbation of asthma (hospital admission or emergency department visit for asthma) within 180 days after initiation. We applied iterative causal forest, a novel causal machine learning subgrouping algorithm, to assess heterogeneous treatment effects. In identified subgroups, we predicted propensity score, conducted propensity score trimming, and then estimated adjusted risk differences for the effect of GLP1RAs relative to comparators on asthma exacerbation using inverse probability treatment weighting in the propensity score-trimmed subpopulation. Results: Among 10,989 patients initiating GLP1RAs or thiazolidinediones and 17,088 patients initiating GLP1RAs versus sulfonylurea, GLP1RA initiators had fewer exacerbations, with adjusted risk differences of -0.5% (95% confidence interval [CI], -1.1% to 0.1%) and -1.6% (95% CI, -2.2% to -1.1%), respectively. In the GLP1RA versus sulfonylurea cohort, in which we observed a beneficial effect, our iterative causal forest analysis identified five subgroups with different treatment effects, defined by the number of emergency department visits, the number of prescriptions for short-acting β 2 -agonists, the number of prescriptions for inhaled steroids and long-acting β-agonists (either combination therapy or concurrent use), and age ≥ 50 years. Among these, patients with two or more emergency department visits during the 12-month baseline period had the largest absolute exacerbation risk reduction, with a decrease of 2.8% for GLP1RAs (95% CI, -4.8% to -0.9%). Conclusions: GLP1RAs demonstrated a beneficial effect on reducing asthma exacerbation relative to sulfonylureas. Patients with asthma with two or more emergency department visits (a proxy for disease severity) benefit most from GLP1RAs. Emergency department visit frequency, the number of maintenance and reliever inhalers, and age might help individualize prediction of the short-term benefit of GLP1RAs on asthma exacerbation.

Introduction: We investigated the genetic determinants of variation in the hemoglobin glycation index (HGI), an emerging biomarker for the risk of diabetes complications., Methods: We conducted a genome-wide association study (GWAS) for HGI in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial ( N = 7,913) using linear regression and additive genotype encoding on variants with minor allele frequency greater than 3%. We conducted replication analyses of top findings in the Atherosclerosis Risk in Communities (ARIC) study with inverse variance-weighted meta-analysis. We followed up with stratified GWAS analyses by sex and self-reported race., Results: In ACCORD, we identified single nucleotide polymorphisms (SNPs) associated with HGI, including a peak with the strongest association at the intergenic SNP rs73407935 (7q11.22) ( P = 5.8e-10) with a local replication in ARIC. In black individuals, the variant rs10739419 on chromosome 9 in the Whirlin ( WHRN ) gene formally replicated (meta- P = 2.2e-9). The SNP-based heritability of HGI was 0.39 ( P < 1e-10). HGI had significant sex-specific associations with SNPs in or near GALNT11 in women and HECW2 in men. Finally, in Hispanic participants, we observed genome-wide significant associations with variants near USF1 and NXNL2/SPIN1 ., Discussion: Many HGI-associated SNPs were distinct from those associated with fasting plasma glucose or HbA1c, lending further support for HGI as a distinct biomarker of diabetes complications. The results of this first evaluation of the genetic etiology of HGI indicate that it is highly heritable and point to heterogeneity by sex and race., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 House, Breeyear, Akhtari, Evans, Buse, Hempe, Doria, Mychaleckyi, Fonseca, Shi, Li, Liu, Kelly, Rotroff and Motsinger-Reif.)

Objective: The coronavirus 2019 (COVID-19) pandemic has evolved over time by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant, disease severity, treatment, and prevention. There is evidence of an elevated risk of incident diabetes after COVID-19; our objective was to evaluate whether this association is consistent across time and with contemporary viral variants., Research Design and Methods: We conducted a retrospective cohort study using National COVID Cohort Collaborative (N3C) data to evaluate incident diabetes risk among COVID-positive adults compared with COVID-negative patients or control patients with acute respiratory illness (ARI). Cohorts were weighted on demographics, data site, and Charlson comorbidity index score. The primary outcome was the cumulative incidence ratio (CIR) of incident diabetes for each viral variant era., Results: Risk of incident diabetes 1 year after COVID-19 was increased for patients with any viral variant compared with COVID-negative control patients (ancestral CIR 1.16 [95% CI 1.12-1.21]; Alpha CIR 1.14 [95% CI 1.11-1.17]; Delta CIR 1.17 [95% CI 1.13-1.21]; Omicron CIR 1.13 [95% CI 1.10-1.17]) and control patients with ARI (ancestral CIR 1.17 [95% CI 1.11-1.22]; Alpha CIR 1.14 [95% CI 1.09-1.19]; Delta CIR 1.18 [95% CI 1.11-1.26]; Omicron CIR 1.20 [95% CI 1.13-1.27]). There was latency in the timing of incident diabetes risk with the Omicron variant; in contrast with other variants, the risk presented after 180 days., Conclusions: Incident diabetes risk after COVID-19 was similar across different SARS-CoV-2 variants. However, there was greater latency in diabetes onset in the Omicron variant era., (© 2024 by the American Diabetes Association.)

Aim: The decline in estimated glomerular filtration rate (eGFR), a significant predictor of cardiovascular disease (CVD), occurs heterogeneously in people with diabetes because of various risk factors. We investigated the role of eGFR decline in predicting CVD events in people with type 2 diabetes in both primary and secondary CVD prevention settings., Materials and Methods: Bayesian joint modelling of repeated measures of eGFR and time to CVD event was applied to the Exenatide Study of Cardiovascular Event Lowering (EXSCEL) trial to examine the association between the eGFR slope and the incidence of major adverse CV event/hospitalization for heart failure (MACE/hHF) (non-fatal myocardial infarction, non-fatal stroke, CV death, or hospitalization for heart failure). The analysis was adjusted for age, sex, smoking, systolic blood pressure, baseline eGFR, antihypertensive and lipid-lowering medication, diabetes duration, atrial fibrillation, high-density cholesterol, total cholesterol, HbA1c and treatment allocation (once-weekly exenatide or placebo)., Results: Data from 11 101 trial participants with (n = 7942) and without (n = 3159) previous history of CVD were analysed. The mean ± SD eGFR slope per year in participants without and with previous CVD was -0.68 ± 1.67 and -1.03 ± 2.13 mL/min/1.73 m 2 , respectively. The 5-year MACE/hHF incidences were 7.5% (95% CI 6.2, 8.8) and 20% (95% CI 19, 22), respectively. The 1-SD decrease in the eGFR slope was associated with increased MACE/hHF risks of 48% (HR 1.48, 95% CI 1.12, 1.98, p = 0.007) and 33% (HR 1.33, 95% CI 1.18,1.51, p < 0.001) in participants without and with previous CVD, respectively., Conclusions: eGFR trajectories over time significantly predict incident MACE/hHF events in people with type 2 diabetes with and without existing CVD, with a higher hazard ratio for MACE/hHF in the latter group., (© 2024 The Author(s). Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.)

Glucose-responsive formulations of insulin can increase its therapeutic index and reduce the burden of its administration. However, it has been difficult to develop single-dosage formulations that can release insulin in both a sustained and glucose-responsive manner. Here we report the development of a subcutaneously injected glucose-responsive formulation that nearly does not trigger the formation of a fibrous capsule and that leads to week-long normoglycaemia and negligible hypoglycaemia in mice and minipigs with type 1 diabetes. The formulation consists of gluconic acid-modified recombinant human insulin binding tightly to poly-L-lysine modified by 4-carboxy-3-fluorophenylboronic acid via glucose-responsive phenylboronic acid-diol complexation and electrostatic attraction. When the insulin complex is exposed to high glucose concentrations, the phenylboronic acid moieties of the polymers bind rapidly to glucose, breaking the complexation and reducing the polymers' positive charge density, which promotes the release of insulin. The therapeutic performance of this long-acting single-dose formulation supports its further evaluation and clinical translational studies., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

We recently developed a machine-learning subgrouping algorithm, iterative causal forest (iCF), to identify subgroups with heterogeneous treatment effects (HTEs) using predefined covariates. However, such predefined covariates may miss or poorly define important features leading to inaccurate subgrouping. To address such limitations, we developed a new semi-automatic subgrouping algorithm, hdiCF, which adapts methodology from high-dimensional propensity score for feature recognition in claims data. The hdiCF algorithm has 3 steps: 1) high-dimensional feature identification by International Classification of Diseases, Current Procedural Terminology, and Anatomical Therapeutic Chemical codes (in/outpatient diagnoses, procedures, prescriptions) and creation of ordinal variables by frequency of occurrence; 2) propensity score trimming and high-dimensional feature preparation; 3) iCF implementation to identify subgroups. We applied hdiCF in a 20% random sample of fee-for-service Medicare beneficiaries who initiated sodium-glucose cotransporter-2 inhibitors (SGLT2i) or glucagon-like peptide-1 receptor agonists to identify subgroups with HTEs for incidence of hospitalized heart failure. HdiCF findings were consistent with studies suggesting SGLT2i to be more beneficial for patients with pre-existing heart failure or chronic kidney disease. HdiCF is not dependent on prior hypotheses about HTEs and identifies subgroups with markers for potential HTEs in real-world evidence studies where active-comparator, new-user study designs limit the potential for unmeasured confounding., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Contrary to current insulin formulations, endogenous insulin has direct access to the portal vein, regulating glucose metabolism in the liver with minimal hypoglycaemia. Here we report the synthesis of an amphiphilic diblock copolymer comprising a glucose-responsive positively charged segment and polycarboxybetaine. The mixing of this polymer with insulin facilitates the formation of worm-like micelles, achieving highly efficient absorption by the gastrointestinal tract and the creation of a glucose-responsive reservoir in the liver. Under hyperglycaemic conditions, the polymer triggers a rapid release of insulin, establishing a portal-to-peripheral insulin gradient-similarly to endogenous insulin-for the safe regulation of blood glucose. This insulin formulation exhibits a dose-dependent blood-glucose-regulating effect in a streptozotocin-induced mouse model of type 1 diabetes and controls the blood glucose at normoglycaemia for one day in non-obese diabetic mice. In addition, the formulation demonstrates a blood-glucose-lowering effect for one day in a pig model of type 1 diabetes without observable hypoglycaemia, showing promise for the safe and effective management of type 1 diabetes., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

One obstacle to adopting instrumental variable (IV) methods in pharmacoepidemiology is their reliance on strong, unverifiable assumptions. We can falsify IV assumptions by leveraging the causal structure, which can strengthen or refute their plausibility and increase the validity of effect estimates. We illustrate a systematic approach to evaluate calendar time IV assumptions in estimating the known effect of thiazolidinediones on hospitalized heart failure. Using cohort entry time before and after 09/2010, when the U.S. Food and Drug Administration issued a safety communication as a proposed IV, we estimated IV and propensity score-weighted 2-year risk differences (RDs) using Medicare data (2008-2014). We (i) performed inequality tests, (ii) identified the negative control IV/outcome using causal assumptions, (iii) estimated RDs after narrowing the calendar time range and excluding patients likely associated with unmeasured confounding, (iv) derived bounds for RDs, and (v) estimated the proportion of compliers and their characteristics. The findings revealed that IV assumptions were violated and RDs were extreme, but the assumptions became more plausible upon narrowing the calendar time range and restricting the cohort by excluding prevalent heart failure (the strongest measured predictor of outcome). Systematically evaluating IV assumptions could help detect bias in IV estimators and increase their validity., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Insulin replacement therapy is indispensable in the treatment of type 1 and advanced type 2 diabetes. However, insulin's clinical application is challenging due to its narrow therapeutic index. To mitigate acute and chronic risks of glucose excursions, glucose-responsive insulin (GRI) has long been pursued for clinical application. By integrating GRI with glucose-sensitive elements, GRI is capable of releasing or activating insulin in response to plasma or interstitial glucose levels without external monitoring, thereby improving glycemic control and reducing hypoglycemic risk. In this Perspective, we first introduce the history of GRI development and then review major glucose-responsive components that can be leveraged to control insulin delivery. Subsequently, we highlight the recent advances in GRI delivery carriers and insulin analogs. Finally, we provide a look to the future and the challenges of clinical application of GRI., (© 2024 by the American Diabetes Association.)

Diabetes complications occur at higher rates in individuals of African ancestry. Glucose-6-phosphate dehydrogenase deficiency (G6PDdef), common in some African populations, confers malaria resistance, and reduces hemoglobin A1c (HbA1c) levels by shortening erythrocyte lifespan. In a combined-ancestry genome-wide association study of diabetic retinopathy, we identified nine loci including a G6PDdef causal variant, rs1050828 -T (Val98Met), which was also associated with increased risk of other diabetes complications. The effect of rs1050828 -T on retinopathy was fully mediated by glucose levels. In the years preceding diabetes diagnosis and insulin prescription, glucose levels were significantly higher and HbA1c significantly lower in those with versus without G6PDdef. In the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial, participants with G6PDdef had significantly higher hazards of incident retinopathy and neuropathy. At the same HbA1c levels, G6PDdef participants in both ACCORD and the Million Veteran Program had significantly increased risk of retinopathy. We estimate that 12% and 9% of diabetic retinopathy and neuropathy cases, respectively, in participants of African ancestry are due to this exposure. Across continentally defined ancestral populations, the differences in frequency of rs1050828 -T and other G6PDdef alleles contribute to disparities in diabetes complications. Diabetes management guided by glucose or potentially genotype-adjusted HbA1c levels could lead to more timely diagnoses and appropriate intensification of therapy, decreasing the risk of diabetes complications in patients with G6PDdef alleles., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Objective: A new generation of basal insulin analogs enabling once-weekly administration is currently under development. Weekly basal insulins have the potential to overcome limitations exhibited by current daily basal insulins. The pharmacokinetic and glucodynamic characteristics differ significantly between weekly and daily basal insulins and will require paradigm shifts in how basal insulins are dosed., Methods: An overview of pharmacokinetic and glucodynamic principles of basal insulins is presented. Specifically, the pharmacokinetic and glucodynamic properties of daily basal insulins and how these differ for the new weekly basal insulins are discussed. Finally, models and simulations are used to describe the impact of weekly insulin properties on dosing., Results: Two approaches have been used to extend the half-lives of these insulins, creating fusion proteins with reduced clearance and reduced receptor-mediated degradation of the insulin. The resulting prolonged exposure-response profiles affect dosing and the impact of dosing errors. Specifically, the impact of loading doses, missed doses, and double doses, and the effect on glycemic variability of a once weekly basal insulin option are demonstrated using pharmacokinetic/glucodynamic models and simulations., Conclusions: The transition from daily to weekly basal insulin dosing requires an understanding of the implications of the prolonged exposure-response profiles to effectively and confidently incorporate these weekly basal insulins into clinical practice. By reviewing the application of pharmacokinetic and glucodynamic principles to daily basal insulin analogs, the differences with weekly basal insulins, and the impact of these properties on dosing, this review intends to explain the principles behind weekly basal insulin dosing., Competing Interests: Disclosure J.L., J.B.V., J.C., and K.S. are employees and shareholders in Eli Lilly and Company. T.R.P. reports grant support paid the Medical University of Graz by Arecor, AstraZeneca, Novo Nordisk and Sanofi; personal compensation for consultation from Arecor, AstraZeneca, Eli Lilly, Novo Nordisk and Sanofi. R.J. was an Executive Director of Diabetes Global Medical Affairs at Lilly, during which he contributed to this article. R.J. is currently a Senior Director, Clinical Development Strategy, at Novo Nordisk Inc, which provided no review of, or other support for, this article. J.B.B. reports contracted fees and travel support for contracted activities for consulting work paid to the University of North Carolina by Novo Nordisk; grant support by Dexcom, NovaTarg, Novo Nordisk, Sanofi, Tolerion and vTv Therapeutics; personal compensation for consultation from Alkahest, Altimmune, Anji, AstraZeneca, Bayer, Biomea Fusion Inc, Boehringer-Ingelheim, CeQur, Cirius Therapeutics Inc, Corcept Therapeutics, Eli Lilly, Fortress Biotech, GentiBio, Glycadia, Glyscend, Janssen, MannKind, Mellitus Health, Moderna, Pendulum Therapeutics, Praetego, Sanofi, Stability Health, Terns Inc, Valo and Zealand Pharma; stock/options in Glyscend, Mellitus Health, Pendulum Therapeutics, PhaseBio, Praetego, and Stability Health; and board membership of the Association of Clinical and Translational Science., (Copyright © 2024 AACE. Published by Elsevier Inc. All rights reserved.)

Objective: To compare postprandial glucose excursions following a bolus with inhaled technosphere insulin (TI) or subcutaneous rapid-acting analog (RAA) insulin., Research Design and Methods: A meal challenge was completed by 122 adults with type 1 diabetes who were using multiple daily injections (MDI), a nonautomated pump, or automated insulin delivery (AID) and who were randomized to bolus with their usual RAA insulin (n = 61) or TI (n = 61)., Results: The primary outcome, the treatment group difference in area under the curve for glucose >180 mg/dL over 2 h, was less with TI versus RAA (adjusted difference -12 mg/dL, 95% CI -22 to -2, P = 0.02). With TI, the glucose excursion was smaller (P = 0.01), peak glucose lower (P = 0.01), and time to peak glucose shorter (P = 0.006). Blood glucose <70 mg/dL occurred in one participant in each group., Conclusions: Postmeal glucose excursion was smaller with TI than with RAA insulin in a cohort that included both AID and MDI users., (© 2024 by the American Diabetes Association.)

Background: Metformin has antiviral activity against RNA viruses including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The mechanism appears to be suppression of protein translation via targeting the host mechanistic target of rapamycin pathway. In the COVID-OUT randomized trial for outpatient coronavirus disease 2019 (COVID-19), metformin reduced the odds of hospitalizations/death through 28 days by 58%, of emergency department visits/hospitalizations/death through 14 days by 42%, and of long COVID through 10 months by 42%., Methods: COVID-OUT was a 2 × 3 randomized, placebo-controlled, double-blind trial that assessed metformin, fluvoxamine, and ivermectin; 999 participants self-collected anterior nasal swabs on day 1 (n = 945), day 5 (n = 871), and day 10 (n = 775). Viral load was quantified using reverse-transcription quantitative polymerase chain reaction., Results: The mean SARS-CoV-2 viral load was reduced 3.6-fold with metformin relative to placebo (-0.56 log10 copies/mL; 95% confidence interval [CI], -1.05 to -.06; P = .027). Those who received metformin were less likely to have a detectable viral load than placebo at day 5 or day 10 (odds ratio [OR], 0.72; 95% CI, .55 to .94). Viral rebound, defined as a higher viral load at day 10 than day 5, was less frequent with metformin (3.28%) than placebo (5.95%; OR, 0.68; 95% CI, .36 to 1.29). The metformin effect was consistent across subgroups and increased over time. Neither ivermectin nor fluvoxamine showed effect over placebo., Conclusions: In this randomized, placebo-controlled trial of outpatient treatment of SARS-CoV-2, metformin significantly reduced SARS-CoV-2 viral load, which may explain the clinical benefits in this trial. Metformin is pleiotropic with other actions that are relevant to COVID-19 pathophysiology., Clinical Trials Registration: NCT04510194., Competing Interests: Potential conflicts of interest. J. B. B. reports contracted fees and travel support for contracted activities for consulting work paid to the University of North Carolina by Novo Nordisk; grant support by NIH, PCORI, Bayer, Boehringer-Ingelheim, Carmot, Corcept, Dexcom, Eli Lilly, Insulet, MannKind, Novo Nordisk, and vTv Therapeutics; personal compensation for consultation from Alkahest, Altimmune, Anji, Aqua Medical Inc, AstraZeneca, Boehringer-Ingelheim, CeQur, Corcept Therapeutics, Eli Lilly, embecta, GentiBio, Glyscend, Insulet, Mellitus Health, Metsera, Moderna, Novo Nordisk, Pendulum Therapeutics, Praetego, Stability Health, Tandem, Terns Inc, and Vertex.; personal compensation for expert testimony from Medtronic MiniMed; participation on advisory boards for Altimmune, AstraZeneca, and Insulet; a leadership role for the Association of Clinical and Translational Science; and stock/options in Glyscend, Mellitus Health, Pendulum Therapeutics, Praetego, and Stability Health. M. A. P. receives consulting fees from Opticyte and Cytovale. A. B. K. has served as an external consultant for Roche Diagnostics; received speaker honoraria from Siemens Healthcare Diagnostics, the American Kidney Fund, the National Kidney Foundation, the American Society of Nephrology, and Yale University Department of Laboratory Medicine; research support unrelated to this work from Siemens Healthcare Diagnostics, Kyowa Kirin Pharmaceutical Development, the Juvenile Diabetes Research Foundation, and the NIH; support for travel from College of American Pathologists Point-Of-Care Testing Committee; participation on an advisory board for the Minnesota Newborn Screening Advisory Committee; grants from NIH and JDRF for multiple unrelated clinical research projects and Kyowa Kirin Pharmaceutical Development and Siemens Healthcare Diagnostics for unrelated clinical research studies; and leadership roles for the American Board of Clinical Chemistry, Association for Diagnostics and Laboratory Medicine (ADLM) Evidence-Based Laboratory Medicine Subcommittee, and ADLM Academy Test Utilization Committee. M. R. R. reports consulting fees from 20/20 Gene Systems for coronavirus disease 2019 testing. D. B. R. reports grants from the NIH NCATS ACTIV-6 Steering Committee Chair. K. C. reports stock or stock options for United Health Group. C. T. B. reports consulting fees from NCATS/DCRI and the ACTIV-6 Executive Committee and support for travel from Academic Medical Education. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Introduction: Even with recent treatment advances, type 2 diabetes (T2D) remains poorly controlled for many patients, despite the best efforts to adhere to therapies and lifestyle modifications. Although estimates vary, studies indicate that in >10% of individuals with difficult-to-control T2D, hypercortisolism may be an underlying contributing cause. To better understand the prevalence of hypercortisolism and the impact of its treatment on T2D and associated comorbidities, we describe the two-part Hyper c ortisolism in P at ients with Difficult to Control Type 2 Di a betes Despite Receiving Standard-of-Care Therapies: Preva l ence and Treatment with Korl y m ® (Mifepri st one) (CATALYST) trial., Methods and Analysis: In part 1, approximately 1000 participants with difficult-to-control T2D (haemoglobin A1c (HbA1c) 7.5%-11.5% despite multiple therapies) are screened with a 1 mg dexamethasone suppression test (DST). Those with post-DST cortisol >1.8 µg/dL and dexamethasone level ≥140 ng/dL are identified to have hypercortisolism (part 1 primary endpoint), have morning adrenocorticotropic hormone (ACTH) and dehydroepiandrosterone sulfate (DHEAS) measured and undergo a non-contrast adrenal CT scan. Those requiring evaluation for elevated ACTH are referred for care outside the study; those with ACTH and DHEAS in the range may advance to part 2, a randomised, double-blind, placebo-controlled trial to evaluate the impact of treating hypercortisolism with the competitive glucocorticoid receptor antagonist mifepristone (Korlym ® ). Participants are randomised 2:1 to mifepristone or placebo for 24 weeks, stratified by the presence/absence of an abnormal adrenal CT scan. Mifepristone is dosed at 300 mg once daily for 4 weeks, then 600 mg daily based on tolerability and clinical improvement, with an option to increase to 900 mg. The primary endpoint of part 2 assesses changes in HbA1c in participants with hypercortisolism with or without abnormal adrenal CT scan. Secondary endpoints include changes in antidiabetes medications, cortisol-related comorbidities and quality of life., Ethics and Dissemination: The study has been approved by Cleveland Clinic IRB (Cleveland, Ohio, USA) and Advarra IRB (Columbia, Maryland, USA). Findings will be presented at scientific meetings and published in peer-reviewed journals., Trial Registration Number: NCT05772169., Competing Interests: Competing interests: RAF reports: advisory board with AstraZeneca, Novo Nordisk, Boehringer Ingelheim, Intarcia, Renalytix, Corcept Therapeutics; research support from Boehringer Ingelheim, AstraZeneca; speaker's bureau with AstraZeneca. RJA reports: research support from Neurocrine Biosciences and Diurnal, Spruce Biosciences, Corcept Therapeutics, Sparrow Pharmaceuticals; consulting fees from Quest Diagnostics, Corcept Therapeutics, Xeris Pharmaceuticals, Crinetics Pharmaceuticals, Adrenas Therapeutics, PhaseBio Pharmaceuticals, Novo Nordisk, Recordati Rare Diseases, H Lundbeck A/S, OMass Therapeutics, Sparrow Pharmaceuticals. IB reports: consulting and/or advisory board with Corcept, HRA Pharma, Recordati, Sparrow, Neurocrine, Diurnal, Spruce; data safety monitoring board with Adrenas; funding for investigator initiated award from Recordati. LB reports: contracted fees paid to the Ochsner Clinic Foundation by Novo Nordisk for consulting work, and to Corcept Therapeutics for both speaking and consulting services. RSB reports: grant funding from Corcept pharmaceuticals; research funding from Novo, Lilly and Novartis; and speaker bureaus for Novo, Lilly, AstraZeneca, Amgen,and Bayer. JBB reports: contracted fees and travel support for contracted activities for consulting work paid to the University of North Carolina by Novo Nordisk; grant support from Dexcom, Insulet, NovaTarg, Novo Nordisk, Sanofi, Tolerion and vTv Therapeutics; personal compensation for consultation from Alkahest, Altimmune, Anji, AstraZeneca, Bayer, Biomea Fusion, Boehringer Ingelheim, CeQur, Cirius Therapeutics, Corcept Therapeutics, Eli Lilly, Fortress Biotech, GentiBio, Glycadia, Glyscend, Janssen, MannKind, Medtronic, Mellitus Health, Moderna, Pendulum Therapeutics, Praetego, Sanofi, Stability Health, Terns, Valo and Zealand Pharma; stock/options in Glyscend, Mellitus Health, Pendulum Therapeutics, PhaseBio, Praetego, Stability Health. JWF reports: consultant and investigator for Corcept, Recordati. VAF reports: research support (to Tulane): grants from Fractyl, Jaguar Gene Therapy, Corcept; honoraria for consulting and lectures from Asahi, Bayer, Abbott, Boehringer Ingelheim, Corcept; stock options in Mellitus Health, BRAVO4Health; stock in Amgen, Abbott; patents pending for 1) BRAVO risk engine for predicting diabetes complications, 2) PAX4 gene therapy for type 1 diabetes. JPF reports: research support from Akero, Altimmune, Boehringer Ingelheim, 89bio, Eli Lilly, Intercept, IONIS, Janssen, Madrigal, Merck, NorthSea Therapeutics, Novartis, Novo Nordisk, Oramed, Pfizer, Sanofi, Shionogi, Corcept Therapeutics; advisory boards and consulting with Akero, Altimmune, Boehringer Ingelheim, Carmot Therapeutics, Echosens, 89bio, Eli Lilly, Gilead, Intercept, Merck, Novo Nordisk, Pfizer, Sanofi, Sun Pharma; speaker’s bureau with Eli Lilly; employment and stock ownership in Biomea Fusion. OH reports: scientific advisory board participation with Corcept Therapeutics, Strongbridge Pharma, Recordati Rare Diseases, Amryt Pharma, Neurocrine Biosciences, Lantheus, Xeris. YH reports: research grant from Amgen, Applied Therapeutic, Corcept, Ionis, Lilly, Merck, Regor; advisory/consultant role with Amgen, Applied Therapeutic, AZ, Bayer, BI, Corcept, Esperion, Mankind Pharma, Merck, Merck-Pfizer, Novartis, Novo Nordisk, Sanofi; speaker’s bureau with Bayer, Esperion, Novo Nordisk. REP reports: consulting fees from Bayer AG, Corcept Therapeutics Incorporated, Dexcom, Hanmi Pharmaceutical Co., Merck, Novo Nordisk, Pfizer, Sanofi, Scohia Pharma, Sun Pharmaceutical Industries; grants/research support from Hanmi Pharmaceutical Co., Janssen, Metavention, Novo Nordisk, Poxel SA, Sanofi. All funds are paid directly to REP’s employer, AdventHealth, a non-profit organisation that supports education and research. JR reports: advisory panels with Applied Therapeutics, Boehringer Ingelheim, Eli Lilly and Company, Hanmi, Intarcia, Novo Nordisk, Oramed, Sanofi, Scholar Rock, Structure Therapeutics, Terns Pharma and Zealand; research support from Applied Therapeutics, AstraZeneca, Boehringer Ingelheim, Eli Lilly and Company, Novartis, Intarcia, Merck, Novo Nordisk, Oramed, Pfizer, Sanofi. ICT, AGM and DE report: employed by and own stock in Corcept Therapeutics., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: Skeletal muscle density (SMD) measurements from imaging scans identify myosteatosis and could screen patients for geriatric assessment. We assessed SMD performance as a screening tool to identify older adults with cancer likely to be frail and who could benefit from in-depth assessment; we compared performance by sex and diabetes status., Materials and Methods: We analyzed patients in the Cancer & Aging Resilience Evaluation (CARE) Registry. Frailty and diabetes were captured using a patient-reported geriatric assessment (CARE tool). Frailty was defined using CARE frailty index (CARE-FI) based on principles of deficit accumulation. SMD was calculated from computed tomography scans (L3 vertebrae). Analyses were conducted by sex and diabetes status. Scatterplots and linear regression described crude associations between SMD and frailty score. Classification performance (frail vs. non-frail) was analyzed with (1) area under the receiver operating characteristic curves (AUC) and confidence intervals (CIs); and (2) sensitivity/specificity for sex-specific SMD quartile cut-offs (Q1, median, Q3). Performance was compared between patients with and without diabetes using differences and estimated CIs (2000 bootstrap replicates). We additionally calculated positive and negative likelihood ratios (LR+, LR-)., Results: The analytic cohort included 872 patients (39% female, median age 68 years, 27% with diabetes) with predominately stage III/IV gastrointestinal cancer; >60% planning to initiate first-line chemotherapy. SMD was negatively associated with frailty score; models were best fit in male patients with diabetes. AUC estimates for female (range: 0.58-0.62) and male (0.58-0.68) patients were low. Q3 cut-offs had high sensitivity (range: 0.76-0.89), but poor specificity (0.25-0.34). Diabetes did not impact estimates for female patients. Male patients with diabetes had greater sensitivity estimates compared to those without (sensitivity differences: 0.23 [0.07, 0.38], 0.08 [-0.07, 0.24], and 0.11 [0.00, 0.22] for Q1, median, Q3, respectively). LR estimates were most notable for male patients with diabetes (LR+ = 2.92, Q1 cut-off; LR- = 0.46, Q3 cut-off)., Discussion: Using SMD alone to screen older patients for geriatric assessment requires improvement. High-sensitivity cut-off points could miss 11-24% of patients with frailty, and many non-frail patients may be flagged. Screening with SMD is practical but work is needed to understand clinical andresource impacts of different cut-off points. Future research should evaluate performance with additional clinical data and in subgroups., Competing Interests: Declaration of Competing Interest ST received dissertation support through the Bristol Meyers Squibb Pre-Doctoral Fellowship in Worldwide Health Economics & Outcomes Research. TS receives investigator-initiated research funding and support as Principal Investigator [R01AG056479] from the National Institute on Aging; and as Co-Investigator [R01CA174453, R01HL118255, R01MD011680], National Institutes of Health. He also receives salary support as Director of Comparative Effectiveness Research (CER), NC TraCS Institute, UNC Clinical and Translational Science Award [UL1TR002489], the Center for Pharmacoepidemiology (current members: GlaxoSmithKline, UCB BioSciences, Takeda, AbbVie, Boehringer Ingelheim), from pharmaceutical companies (Novo Nordisk), and from a generous contribution from Dr. Nancy A. Dreyer to the Department of Epidemiology, UNC-CH. Dr. Stürmer does not accept personal compensation of any kind from any pharmaceutical company. He owns stock in Novartis, Roche, and Novo Nordisk. All other authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Introduction: We previously identified a genetic subtype (C4) of type 2 diabetes (T2D), benefitting from intensive glycemia treatment in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. Here, we characterized the population of patients that met the C4 criteria in the UKBiobank cohort., Research Design and Methods: Using our polygenic score (PS), we identified C4 individuals in the UKBiobank and tested C4 status with risk of developing T2D, cardiovascular disease (CVD) outcomes, and differences in T2D medications., Results: C4 individuals were less likely to develop T2D, were slightly older at T2D diagnosis, had lower HbA1c values, and were less likely to be prescribed T2D medications (P < .05). Genetic variants in MAS1 and IGF2R, major components of the C4 PS, were associated with fewer overall T2D prescriptions., Conclusion: We have confirmed C4 individuals are a lower risk subpopulation of patients with T2D., (© 2024. The Author(s).)

Background & Aims: Glucagon-like peptide-1-receptor agonists (GLP1-RAs) have been associated with greater retention of gastric contents, however, there is minimal controlled, population-based data evaluating the potential adverse effects of GLP1-RA in the periprocedural setting. We aimed to determine if there is increased risk of aspiration and aspiration-related complications after upper endoscopy in patients using GLP1-RAs., Methods: We used a nationwide commercial administrative claims database to conduct a retrospective cohort study of patients aged 18 to 64 with type 2 diabetes who underwent outpatient upper endoscopy from 2005 to 2021. We identified 6,806,046 unique upper endoscopy procedures. We compared claims for aspiration and associated pulmonary adverse events in the 14 days after upper endoscopy between users of GLP1-RAs, dipeptidyl peptidase 4 inhibitors (DPP4is), and chronic opioids. We adjusted for age, sex, Charlson Comorbidity score, underlying respiratory disease, and gastroparesis., Results: We found that pulmonary adverse events after upper endoscopy are rare, ranging from 6 to 25 events per 10,000 procedures. When comparing GLP1-RAs with DPP4i, crude relative risks of aspiration (0.67; 95% CI, 0.25-1.75), aspiration pneumonia (0.95; 95% CI, 0.40-2.29), pneumonia (1.07; 95% CI, 0.62-1.86), or respiratory failure (0.75; 95% CI, 0.38-1.48) were not higher in patients prescribed a GLP1-RA. When comparing GLP1-RAs with opioids, crude relative risks were 0.42 (95% CI, 0.15-1.16) for aspiration, 0.60 (95% CI, 0.24-1.52) for aspiration pneumonia, 0.30 (95% CI, 0.19-0.49) for pneumonia, and 0.24 (95% CI, 0.13-0.45) for respiratory failure. These results were consistent across several sensitivity analyses., Conclusions: GLP1-RA use is not associated with an increased risk of pulmonary complications after upper endoscopy compared with DPP4i use in patients with type 2 diabetes., (Copyright © 2024 AGA Institute. Published by Elsevier Inc. All rights reserved.)

Precisely and efficiently identifying subgroups with heterogeneous treatment effects (HTEs) in real-world evidence studies remains a challenge. Based on the causal forest (CF) method, we developed an iterative CF (iCF) algorithm to identify HTEs in subgroups defined by important variables. Our method iteratively grows different depths of the CF with important effect modifiers, performs plurality votes to obtain decision trees (subgroup decisions) for a family of CFs with different depths, and then finds the cross-validated subgroup decision that best predicts the treatment effect as a final subgroup decision. We simulated 12 different scenarios and showed that the iCF outperformed other machine learning methods for interaction/subgroup identification in the majority of scenarios assessed. Using a 20% random sample of fee-for-service Medicare beneficiaries initiating sodium-glucose cotransporter-2 inhibitors or glucagon-like peptide-1 receptor agonists, we implemented the iCF to identify subgroups with HTEs for hospitalized heart failure. Consistent with previous studies suggesting patients with heart failure benefit more from sodium-glucose cotransporter-2 inhibitors, iCF successfully identified such a subpopulation with HTEs and additive interactions. The iCF is a promising method for identifying subgroups with HTEs in real-world data where the potential for unmeasured confounding can be limited by study design., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Introduction: After colectomy with ileoanal pouch anastomosis (IPAA), many patients develop high bowel frequency (BF) refractory to antimotility agents, despite normal IPAA morphology. Low circulating levels of glucagon-like protein-1 (GLP-1), a modulator of gastroduodenal motility, have been reported after colectomy., Methods: Double-blind crossover study of 8 IPAA patients with refractory high BF treated with daily administration of the GLP-1 receptor agonist liraglutide or placebo., Results: Liraglutide, but not placebo, reduced daily BF by more than 35% ( P < 0.03)., Discussion: Larger randomized controlled studies are warranted to delineate the treatment potential of GLP-1 receptor agonists in IPAA patients suffering from noninflammatory high BF., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of The American College of Gastroenterology.)

Introduction: People with type 2 diabetes are at heightened risk for severe outcomes related to COVID-19 infection, including hospitalization, intensive care unit admission, and mortality. This study was designed to examine the impact of premorbid use of glucagon-like peptide-1 receptor agonist (GLP-1RA) monotherapy, sodium-glucose cotransporter-2 inhibitor (SGLT-2i) monotherapy, and concomitant GLP1-RA/SGLT-2i therapy on the severity of outcomes in individuals with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection., Methods: Utilizing observational data from the National COVID Cohort Collaborative through September 2022, we compared outcomes in 78,806 individuals with a prescription of GLP-1RA and SGLT-2i versus a prescription of dipeptidyl peptidase 4 inhibitors (DPP-4i) within 24 months of a positive SARS-CoV-2 PCR test. We also compared concomitant GLP-1RA/SGLT-2i therapy to GLP-1RA and SGLT-2i monotherapy. The primary outcome was 60-day mortality, measured from the positive test date. Secondary outcomes included emergency room (ER) visits, hospitalization, and mechanical ventilation within 14 days. Using a super learner approach and accounting for baseline characteristics, associations were quantified with odds ratios (OR) estimated with targeted maximum likelihood estimation (TMLE)., Results: Use of GLP-1RA (OR 0.64, 95% confidence interval [CI] 0.56-0.72) and SGLT-2i (OR 0.62, 95% CI 0.57-0.68) were associated with lower odds of 60-day mortality compared to DPP-4i use. Additionally, the OR of ER visits and hospitalizations were similarly reduced with GLP1-RA and SGLT-2i use. Concomitant GLP-1RA/SGLT-2i use showed similar odds of 60-day mortality when compared to GLP-1RA or SGLT-2i use alone (OR 0.92, 95% CI 0.81-1.05 and OR 0.88, 95% CI 0.76-1.01, respectively). However, lower OR of all secondary outcomes were associated with concomitant GLP-1RA/SGLT-2i use when compared to SGLT-2i use alone., Conclusion: Among adults who tested positive for SARS-CoV-2, premorbid use of either GLP-1RA or SGLT-2i is associated with lower odds of mortality compared to DPP-4i. Furthermore, concomitant use of GLP-1RA and SGLT-2i is linked to lower odds of other severe COVID-19 outcomes, including ER visits, hospitalizations, and mechanical ventilation, compared to SGLT-2i use alone. Graphical abstract available for this article., (© 2024. The Author(s).)

Background: Many older adults with cancer have ≥2 impairments on geriatric assessment, which affects present and future frailty status, treatment tolerability, and outcomes. Our objective was to identify and describe distinct geriatric assessment impairment classes using latent class analysis (LCA) in older patients with gastrointestinal malignancies and assess 1-year mortality., Methods: We used the Cancer & Aging Resilience Evaluation (CARE) Study, a registry of older adults (≥60 years) at University of Alabama at Birmingham. The analytic cohort included patients with gastrointestinal malignancies who completed a self-administered geriatric assessment (CARE tool) before chemotherapy and had ≥1 geriatric assessment impairment. Thirteen geriatric assessment impairments were used as indicators in LCA. Resultant classes were described, mortality was estimated, and risk contrasts (differences and hazard ratios) were calculated with 95% confidence intervals. For comparison, estimates were provided for frailty categories (robust, prefrail, and frail) determined from 44 items in the CARE tool. Stratified analyses included high-risk (pancreatic, hepatobiliary, and esophageal) versus low-risk gastrointestinal cancers, and stage (IV vs I-III)., Results: Six geriatric assessment impairment classes were identified: Mild impairment (LC1); Social support impairment (LC2); Weight loss alone (LC3); Impaired, low anxiety/depression (LC4); Impaired with anxiety/depression (LC5); and Global impairment (LC6). One-year mortality was 14%, 22%, 29%, 34%, 50%, and 50% for LC1-LC6, respectively. For frailty categories, estimates ranged from 18% (robust) to 40% (frail). In stratified analyses, LC4-LC6 consistently had higher mortality estimates compared to LC1., Conclusions: The 6 geriatric assessment impairment classes showed a wider spread of mortality estimates compared to frailty categories and could be used to identify vulnerable patients and to plan interventions., (© The Author(s) 2023. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Aims: Type 2 diabetes (T2D) is a risk factor for cardiovascular and non-cardiovascular mortality. However, global distribution of cause-specific deaths in T2D is poorly understood. We characterized cause-specific deaths by geographic region among individuals with T2D at risk for cardiovascular disease (CVD)., Methods and Results: The international EXSCEL trial included 14,752 participants with T2D (73% with established CVD). We identified the proportion of deaths over 5-year follow-up attributed to cardiovascular and non-cardiovascular causes, and associated risk factors. During median 3.2-year follow-up, 1,091 (7.4%) participants died. Adjudicated causes of death were 723 cardiovascular (66.3% of deaths), including 252 unknown, and 368 non-cardiovascular (33.7%). Most deaths occurred in North America (N = 356/9.6% across region) and Eastern Europe (N = 326/8.1%), with fewest in Asia/Pacific (N = 68/4.4%). The highest proportional cause-specific deaths by region were sudden cardiac in Asia/Pacific (23/34% of regional deaths) and North America (86/24%); unknown in Eastern Europe (90/28%) and Western Europe (39/21%); and non-malignant non-cardiovascular in Latin America (48/31%). Cox proportional hazards model for adjudicated causes of death showed prognostic risk factors (hazard ratio [95% CI]) for cardiovascular and non-cardiovascular deaths, respectively: heart failure 2.04 (1.72-2.42) and 1.86 (1.46-2.39); peripheral artery disease 1.83 (1.54-2.18) and 1.78 (1.40-2.26); and current smoking status 1.61 (1.29-2.01) and 1.77 (1.31-2.40)., Conclusions: In a contemporary T2D trial population, with and without established CVD, leading causes of death varied by geographic region. Underlying mechanisms leading to variability in cause of death across geographic regions and its impact on clinical trial endpoints warrant future research., (Copyright © 2024. Published by Elsevier Inc.)

Objective: We report mortality outcomes in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE) among people with type 2 diabetes diagnosed within 10 years and no recent history of cardiovascular events or cancer., Research Design and Methods: Overall mortality rates and major causes of death were assessed over an average of 5 years of follow-up. Cause of death was adjudicated centrally by a committee masked to treatment assignment. We examined baseline covariates and the 10-year Framingham Risk Score for associations., Results: Mortality rate was low (0.59 per 100 participant-years). Participants who died during follow-up were likely to be older, be male, have a history of hypertension, have a history of smoking, and have moderate albuminuria. The two most common underlying causes of death were "cardiovascular-cause" (a composite of underlying causes) (38.6%) and cancer (26.8%). There were no differences by treatment group., Conclusions: Among people with diabetes of relatively short duration, cause of death was varied. Attention to health risks beyond cardiovascular diseases is warranted., (© 2024 by the American Diabetes Association.)

Background: Tirzepatide, a once-weekly GIP/GLP-1 receptor agonist, reduces blood glucose and body weight in people with type 2 diabetes. The cardiovascular (CV) safety and efficacy of tirzepatide have not been definitively assessed in a cardiovascular outcomes trial., Methods: Tirzepatide is being studied in a randomized, double-blind, active-controlled CV outcomes trial. People with type 2 diabetes aged ≥40 years, with established atherosclerotic CV disease, HbA1c ≥7% to ≤10.5%, and body mass index ≥25 kg/m 2 were randomized 1:1 to once weekly subcutaneous injection of either tirzepatide up to 15 mg or dulaglutide 1.5 mg. The primary outcome is time to first occurrence of any major adverse cardiovascular event (MACE), defined as CV death, myocardial infarction, or stroke. The trial is event-driven and planned to continue until ≥1,615 participants experience an adjudication-confirmed component of MACE. The primary analysis is noninferiority for time to first MACE of tirzepatide vs dulaglutide by demonstrating an upper confidence limit <1.05, which will also confirm superiority vs a putative placebo, and also to determine whether tirzepatide produces a greater CV benefit than dulaglutide (superiority analysis)., Results: Over 2 years, 13,299 people at 640 sites in 30 countries across all world regions were randomized. The mean age of randomized participants at baseline was 64.1 years, diabetes duration 14.7 years, HbA1c 8.4%, and BMI 32.6 kg/m 2 . Overall, 65.0% had coronary disease, of whom 47.3% reported prior myocardial infarction and 57.4% had prior coronary revascularization. 19.1% of participants had a prior stroke and 25.3% had peripheral artery disease. The trial is fully recruited and ongoing., Conclusion: SURPASS-CVOT will provide definitive evidence as to the CV safety and efficacy of tirzepatide as compared with dulaglutide, a GLP-1 receptor agonist with established CV benefit., Competing Interests: Conflict of interest SJN reports grants or contracts from Amgen, Anthera Pharmaceuticals, AstraZeneca, Cerenis Therapeutics, CSL Behring, Eli Lilly and Company, Esperion Therapeutics, Infraredx, New Amsterdam Pharma, Novartis, Resverlogix, and Sanofi Regeneron; consulting fees from Akcea Therapeutics, Amgen, AstraZeneca, Boehringer Ingelheim, CSL Behring, Eli Lilly and Company, Esperion Therapeutics, Kowa, Merck, Novo Nordisk, Pfizer, Sanofi Regeneron, Takeda, Vaxxinity, Silence Therapeutics, and CSL Sequiris; is a named inventor on a patent planned, issued or pending with Amgen; and is President of Cardiac Society of Australia and New Zealand. DLB reports grants or contracts from Abbott, Acesion Pharma, Afimmune, Aker Biomarine, Amarin, Amgen, AstraZeneca, Bayer, Beren, Boehringer Ingelheim, Boston Scientific, Bristol-Myers Squibb, Cardax, CellProthera, Cereno Scientific, Chiesi, Cincor, Cleerly, CSL Behring, Eisai, Ethicon, Faraday Pharmaceuticals, Ferring Pharmaceuticals, Forest Laboratories, Fractyl, Garmin, HLS Therapeutics, Idorsia, Ironwood, Ischemix, Janssen, Javelin, Lexicon, Eli Lilly and Company, Medtronic, Merck, Moderna, MyoKardia, NirvaMed, Novartis, Novo Nordisk, Owkin, Pfizer Inc, PhaseBio, PLx Pharma, Recardio, Regeneron, Reid Hoffman Foundation, Roche, Sanofi, Stasys, Synaptic, The Medicines Company, Youngene, 89bio, Otsuka, and Alnylam; royalties from Elsevier; consulting fees from Broadview Ventures, Hims, and McKinsey; payment or honoraria from American College of Cardiology, Baim Institute for Clinical Research, Belvoir Publications, Boston Scientific, Cleveland Clinic, Duke Clinical Research Institute, Mayo Clinic, Mount Sinai School of Medicine, Novartis, Population Health Research Institute, Rutgers University, Canadian Medical and Surgical Knowledge Translation Research Group, Cowen and Company, HMP Global, Journal of the American College of Cardiology, K2P, Level Ex, Medtelligence/ReachMD, MJH Life Sciences, Oakstone CME, Piper Sandler, Population Health Research Institute, Slack Publications, WebMD, Wiley, Society of Cardiovascular Patient Care, and CSL Behring; payment for expert testimony from Arnold and Porter law firm; meeting/travel support from American College of Cardiology, Society of Cardiovascular Patient Care, and American Heart Association; a pending patent for Sotagliflozin; participation on data monitoring or advisory boards for Acesion Pharma, Assistance Publique-Hôpitaux de Paris, AngioWave, Baim Institute, Bayer, Boehringer Ingelheim, Boston Scientific, Cardax, CellProthera, Cereno Scientific, Cleveland Clinic, Contego Medical, Duke Clinical Research Institute, Elsevier Practice Update Cardiology, Janssen, Level Ex, Mayo Clinic, Medscape Cardiology, Merck, Mount Sinai School of Medicine, MyoKardia, NirvaMed, Novartis, Novo Nordisk, PhaseBio, PLx Pharma, Regado Biosciences, Population Health Research Institute, and Stasys; leadership or fiduciary roles with American College of Cardiology, AngioWave, Boston VA Research Institute, Bristol Myers Squibb, DRS.LINQ, High Enroll, Society of Cardiovascular Patient Care, TobeSoft, and AHA NYC Chapter; stock or stock options in AngioWave, Bristol Myers Squibb, DRS.LINQ, and High Enroll; and other financial or non-financial interests in Clinical Cardiology (Deputy Editor), NCDR-ACTION Registry Steering Committee (Chair), American Heart Association Quality Oversight Committee (Chair), VA CART Research and Publications Committee (Chair), Contego Medical (Chair, PERFORMANCE 2), conducts unfunded research with FlowCo and Takeda, and is site co-investigator for Abbott, Biotronik, Boston Scientific, CSI, St. Jude Medical (now Abbott), Phillips SpectraWAVE, Svelte, and Vascular Solutions. JBB reports grant support from Dexcom, Insulet, MannKind, NovaTarg, Novo Nordisk, Sanofi, Tolerion, and vTv Therapeutics; consulting fees from Novo Nordisk, Alkahest, Altimmune, Anji, AstraZeneca, Bayer, Biomea Fusion Inc, Boehringer Ingelheim, CeQur, Cirius Therapeutics Inc, Corcept Therapeutics, CultHealth, Eli Lilly and Company, embecta, GentiBio, Glycadia, Glyscend, Janssen, Mellitus Health, Metsera, Moderna, Pendulum Therapeutics, Praetego, Sanofi, Stability Health, Tandem, Terns Inc, Valo, and Zealand Pharma; payment for expert testimony from Medtronic; participation on data monitoring or advisory boards for Alkahest, Altimmune, AstraZeneca, and Tandem; a leadership or fiduciary role with Association of Clinical and Translational Science; stock or stock options in Glyscend, Mellitus Health, Pendulum Therapeutics, PhaseBio, Praetego and Stability Health; and other financial or other non-financial interests in Dasman Diabetes Center, Kuwait City (scientific advisory board), and ReachMD and Mediflix (audiovisual content development). SDP reports consultation for Abbott, Amarin, Applied Therapeutics, AstraZeneca, Boehringer Ingelheim, Eli Lilly and Company, Hengrui Pharmaceuticals, Menarini International, MSD, Novo Nordisk, and Sanofi; grant support from AstraZeneca and Boehringer Ingelheim; and speaker fees from AstraZeneca, Boehringer Ingelheim, Eli Lilly and Company, Laboratori Guidotti, MSD, Novartis, Novo Nordisk, and Sanofi.. SEK reports consulting fees from Anji Pharamceuticals, Eli Lilly and Company, Merck, and Novo Nordisk; and payment or honoraria from Novo Nordisk. AML reports grants or contracts from Eli Lilly and Company; consulting fees from Eli Lilly and Company, Novo Nordisk, and Novartis; and meeting/travel support from Novo Nordisk and Eli Lilly and Company. DKM reports research support for clinical trials leadership from Boehringer Ingelheim, Merck & Co, Pfizer, AstraZeneca, Novo Nordisk, Esperion, Lilly USA, Lexicon, CSL Behring, and New Amsterdam; and honoraria for consultancy from Lilly USA, Boehringer Ingelheim, Merck & Co, Novo Nordisk, Applied Therapeutics, Altimmune, CSL Behring, Bayer, and Intercept. MAN reports grants or contracts from Merck, Sharp & Dohme; consulting fees from Boehringer Ingelheim, Berlin-Chemie/Menarini, Eli Lilly and Company, Medtronic, Merck, Sharp & Dohme, Novo Nordisk, Pfizer, Regor, Structure Therapeutics (Gasherbrum), and Sun Pharma; payment or honoraria from Berlin-Chemie/Menarini, Eli Lilly and Company, Medical Learning Institute, Medscape, Merck, Sharp & Dohme, Novo Nordisk, Sanofi, and Sun Pharma; and participation on a data monitoring or advisory board with Inventiva. SEN reports that the Cleveland Clinic Center for Clinical Research has received funding to perform clinical trials from Abbvie, AstraZeneca, Arrowhead, Amgen, Bristol Myers Squibb, Eli Lilly, Medtronic, MyoKardia, New Amsterdam Pharmaceuticals, Novartis, and Silence Therapeutics. NS reports grants and personal fees from AstraZeneca, Boehringer Ingelheim, and Novartis; a grant from Roche Diagnostics; and personal fees from Abbott Laboratories, Amgen, Eli Lilly and Company, Hanmi Pharmaceuticals, Janssen, Merck Sharp & Dohme, Novartis, Novo Nordisk, Pfizer, and Sanofi. BZ reports consulting fees from Eli Lilly and Company. SZ reports grants or contracts from NHMRC, Australian Government Department of Health and Aged Care, JDRF Centre of Excellence, and MRFF; consulting fees from Eli Lilly Australia, Boehringer-Ingelheim, MSD Australia, Astra Zeneca, Novo Nordisk, and Sanofi; payment or honoraria from Heart Foundation; meeting/travel support from Australian Diabetes Society 2022, International Diabetes Federation 2022, and KDIGO Implementation Summit on Diabetes Management in CKD; and leadership or fiduciary roles with Melanoma and Skin Cancer Trials Ltd., Australian Clinical Trials Alliance, and Victorian Institute of Forensic Medicine. JB reports consulting fees from Eli Lilly and Company, ReCor, and Medtronic; and participation on advisory boards for ReCor, Medtronic, and Eli Lilly and Company. AB, DM, HN, IP, GW, and RJW are employees and shareholders in Eli Lilly and Company. DD reports consulting fees from Eli Lilly and Company, Sun Pharmaceuticals, and Structure Therapeutics; payment or honoraria from University of Chicago, University of Iowa, and Korean Diabetes Association; meeting/travel support from American Diabetes Association; and stock or stock options in MBX Biosciences., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

The COVID-19 pandemic accelerated the development of decentralized clinical trials (DCT). DCT's are an important and pragmatic method for assessing health outcomes yet comprise only a minority of clinical trials, and few published methodologies exist. In this report, we detail the operational components of COVID-OUT, a decentralized, multicenter, quadruple-blinded, randomized trial that rapidly delivered study drugs nation-wide. The trial examined three medications (metformin, ivermectin, and fluvoxamine) as outpatient treatment of SARS-CoV-2 for their effectiveness in preventing severe or long COVID-19. Decentralized strategies included HIPAA-compliant electronic screening and consenting, prepacking investigational product to accelerate delivery after randomization, and remotely confirming participant-reported outcomes. Of the 1417 individuals with the intention-to-treat sample, the remote nature of the study caused an additional 94 participants to not take any doses of study drug. Therefore, 1323 participants were in the modified intention-to-treat sample, which was the a priori primary study sample. Only 1.4% of participants were lost to follow-up. Decentralized strategies facilitated the successful completion of the COVID-OUT trial without any in-person contact by expediting intervention delivery, expanding trial access geographically, limiting contagion exposure, and making it easy for participants to complete follow-up visits. Remotely completed consent and follow-up facilitated enrollment., Competing Interests: The fluvoxamine placebo tablets were donated by the Apotex pharmacy. The ivermectin placebo and active tablets were donated by the Edenbridge pharmacy. The funders had no influence on the design or conduct of the trial and were not involved in data collection or analysis, writing of the manuscript, or decision to submit for publication. The authors assume responsibility for trial fidelity and the accuracy and completeness of the data and analyses., (© The Author(s) 2023.)

Introduction: Increasing interest in real-world evidence has fueled the development of study designs incorporating real-world data (RWD). Using the Causal Roadmap , we specify three designs to evaluate the difference in risk of major adverse cardiovascular events (MACE) with oral semaglutide versus standard-of-care: (1) the actual sequence of non-inferiority and superiority randomized controlled trials (RCTs), (2) a single RCT, and (3) a hybrid randomized-external data study., Methods: The hybrid design considers integration of the PIONEER 6 RCT with RWD controls using the experiment-selector cross-validated targeted maximum likelihood estimator. We evaluate 95% confidence interval coverage, power, and average patient time during which participants would be precluded from receiving a glucagon-like peptide-1 receptor agonist (GLP1-RA) for each design using simulations. Finally, we estimate the effect of oral semaglutide on MACE for the hybrid PIONEER 6-RWD analysis., Results: In simulations, Designs 1 and 2 performed similarly. The tradeoff between decreased coverage and patient time without the possibility of a GLP1-RA for Designs 1 and 3 depended on the simulated bias. In real data analysis using Design 3, external controls were integrated in 84% of cross-validation folds, resulting in an estimated risk difference of -1.53%-points (95% CI -2.75%-points to -0.30%-points)., Conclusions: The Causal Roadmap helps investigators to minimize potential bias in studies using RWD and to quantify tradeoffs between study designs. The simulation results help to interpret the level of evidence provided by the real data analysis in support of the superiority of oral semaglutide versus standard-of-care for cardiovascular risk reduction., Competing Interests: LED reports tuition and stipend support from a philanthropic gift from the Novo Nordisk corporation to the University of California, Berkeley to support the Joint Initiative for Causal Inference. JMT, KKBC, HR, and KK are full-time employees of Novo Nordisk A/S and own stocks in Novo Nordisk A/S. KKBC is partly funded by an Innovation Fund Denmark grant and also affiliated with Steno Diabetes Center Copenhagen, Denmark. EF was a previous full-time employee at Novo Nordisk A/S at the time of writing. JBB reports contracted fees and travel support for contracted activities for consulting work paid to the University of North Carolina by Novo Nordisk; grant support by Dexcom, NovaTarg, Novo Nordisk, Sanofi, Tolerion and vTv Therapeutics; personal compensation for consultation from Alkahest, Altimmune, Anji, AstraZeneca, Bayer, Biomea Fusion Inc, Boehringer-Ingelheim, CeQur, Cirius Therapeutics Inc, Corcept Therapeutics, Eli Lilly, Fortress Biotech, GentiBio, Glycadia, Glyscend, Janssen, MannKind, Mellitus Health, Moderna, Pendulum Therapeutics, Praetego, Sanofi, Stability Health, Terns Inc, Valo and Zealand Pharma; stock/options in Glyscend, Mellitus Health, Pendulum Therapeutics, PhaseBio, Praetego, and Stability Health; and board membership of the Association of Clinical and Translational Science. MvdL reports that he is a co-founder of the statistical software startup company TLrevolution, Inc. MvdL and MP report personal compensation for consultation from Novo Nordisk., (© The Author(s) 2023.)

Background: Post-COVID-19 condition (also known as long COVID) is an emerging chronic illness potentially affecting millions of people. We aimed to evaluate whether outpatient COVID-19 treatment with metformin, ivermectin, or fluvoxamine soon after SARS-CoV-2 infection could reduce the risk of long COVID., Methods: We conducted a decentralised, randomised, quadruple-blind, parallel-group, phase 3 trial (COVID-OUT) at six sites in the USA. We included adults aged 30-85 years with overweight or obesity who had COVID-19 symptoms for fewer than 7 days and a documented SARS-CoV-2 positive PCR or antigen test within 3 days before enrolment. Participants were randomly assigned via 2 × 3 parallel factorial randomisation (1:1:1:1:1:1) to receive metformin plus ivermectin, metformin plus fluvoxamine, metformin plus placebo, ivermectin plus placebo, fluvoxamine plus placebo, or placebo plus placebo. Participants, investigators, care providers, and outcomes assessors were masked to study group assignment. The primary outcome was severe COVID-19 by day 14, and those data have been published previously. Because the trial was delivered remotely nationwide, the a priori primary sample was a modified intention-to-treat sample, meaning that participants who did not receive any dose of study treatment were excluded. Long COVID diagnosis by a medical provider was a prespecified, long-term secondary outcome. This trial is complete and is registered with ClinicalTrials.gov, NCT04510194., Findings: Between Dec 30, 2020, and Jan 28, 2022, 6602 people were assessed for eligibility and 1431 were enrolled and randomly assigned. Of 1323 participants who received a dose of study treatment and were included in the modified intention-to-treat population, 1126 consented for long-term follow-up and completed at least one survey after the assessment for long COVID at day 180 (564 received metformin and 562 received matched placebo; a subset of participants in the metformin vs placebo trial were also randomly assigned to receive ivermectin or fluvoxamine). 1074 (95%) of 1126 participants completed at least 9 months of follow-up. 632 (56·1%) of 1126 participants were female and 494 (43·9%) were male; 44 (7·0%) of 632 women were pregnant. The median age was 45 years (IQR 37-54) and median BMI was 29·8 kg/m 2 (IQR 27·0-34·2). Overall, 93 (8·3%) of 1126 participants reported receipt of a long COVID diagnosis by day 300. The cumulative incidence of long COVID by day 300 was 6·3% (95% CI 4·2-8·2) in participants who received metformin and 10·4% (7·8-12·9) in those who received identical metformin placebo (hazard ratio [HR] 0·59, 95% CI 0·39-0·89; p=0·012). The metformin beneficial effect was consistent across prespecified subgroups. When metformin was started within 3 days of symptom onset, the HR was 0·37 (95% CI 0·15-0·95). There was no effect on cumulative incidence of long COVID with ivermectin (HR 0·99, 95% CI 0·59-1·64) or fluvoxamine (1·36, 0·78-2·34) compared with placebo., Interpretation: Outpatient treatment with metformin reduced long COVID incidence by about 41%, with an absolute reduction of 4·1%, compared with placebo. Metformin has clinical benefits when used as outpatient treatment for COVID-19 and is globally available, low-cost, and safe., Funding: Parsemus Foundation; Rainwater Charitable Foundation; Fast Grants; UnitedHealth Group Foundation; National Institute of Diabetes, Digestive and Kidney Diseases; National Institutes of Health; and National Center for Advancing Translational Sciences., Competing Interests: Declaration of interests CTB was supported by grants (KL2TR002492 and UL1TR002494) from the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health (NIH) and by a grant (K23 DK124654–01-A1) from the National Institute of Diabetes and Digestive and Kidney Diseases of the NIH. JBB was supported by grants (UL1TR002489 and UM1TR004406) from NCATS and reports contracted fees and travel support for contracted activities for consulting work paid to the University of North Carolina by Novo Nordisk; grant support by Dexcom, NovaTarg, Novo Nordisk, Sanofi, Tolerion, and vTv Therapeutics; personal compensation for consultation from Alkahest, Altimmune, Anji, AstraZeneca, Bayer, Biomea Fusion, Boehringer Ingelheim, CeQur, Cirius Therapeutics, Corcept Therapeutics, Eli Lilly, Fortress Biotech, GentiBio, Glycadia, Glyscend, Janssen, MannKind, Mellitus Health, Moderna, Pendulum Therapeutics, Praetego, Sanofi, Stability Health, Terns, Valo, and Zealand Pharma; and stock or stock options in Glyscend, Mellitus Health, Pendulum Therapeutics, PhaseBio, Praetego, and Stability Health. JMN was supported by a grant (K23HL133604) from the National Heart, Lung, and Blood Institute of the NIH. DJO was supported by the Institute for Engineering in Medicine, University of Minnesota Office of Academic and Clinical Affairs COVID-19 Rapid Response Grant, the Earl E Bakken Professorship for Engineering in Medicine, and by grants (U54 CA210190 and P01 CA254849) from the National Cancer Institute of the NIH. TAM was supported in part by the Medtronic Faculty Fellowship. DML receives funding from NIH RECOVER (OT2HL161847). LKS was supported by NIH grants (18X107CF6 and 18X107CF5) through a contract with Leidos Biomedical and by grants from the National Heart, Lung, and Blood Institute of the NIH (T32HL129956), and the NIH (R01LM012982 and R21LM012744). MAP receives grants from the Bill & Melinda Gates Foundation (INV-017069), Minnesota Partnership for Biotechnology and Medical Genomics (00086722), and the National Heart, Lung, and Blood Institute of the NIH (OT2HL156812); and consulting fees from Opticyte and Cytovale. All other authors declare no competing interests., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background/aims: We present and describe recruitment strategies implemented from 2013 to 2017 across 45 clinical sites in the United States, participating in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study, an unmasked, randomized controlled trial evaluating four glucose-lowering medications added to metformin in individuals with type 2 diabetes mellitus (duration of diabetes <10 years). We examined the yield of participants recruited through Electronic Health Records systems compared to traditional recruitment methods to leverage access to type 2 diabetes patients in primary care., Methods: Site selection criteria included availability of the study population, geographic representation, the ability to recruit and retain a diverse pool of participants including traditionally underrepresented groups, and prior site research experience in diabetes clinical trials. Recruitment initiatives were employed to support and monitor recruitment, such as creation of a Recruitment and Retention Committee, development of criteria for Electronic Health Record systems queries, conduct of remote site visits, development of a public screening website, and other central and local initiatives. Notably, the study supported a dedicated recruitment coordinator at each site to manage local recruitment and facilitate screening of potential participants identified by Electronic Health Record systems., Results: The study achieved the enrollment goal of 5000 participants, meeting its target with Black/African American (20%), Hispanic/Latino (18%), and age ≧60 years (42%) subgroups but not with women (36%). Recruitment required 1 year more than the 3 years originally planned. Sites included academic hospitals, integrated health systems, and Veterans Affairs Medical Centers. Participants were enrolled through Electronic Health Record queries (68%), physician referral (13%), traditional mail outreach (7%), TV, radio, flyers, and Internet (7%), and other strategies (5%). Early implementation of targeted Electronic Health Record queries yielded a greater number of eligible participants compared to other recruitment methods. Efforts over time increasingly emphasized engagement with primary care networks., Conclusion: Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness successfully recruited a diverse study population with relatively new onset of type 2 diabetes mellitus, relying to a large extent on the use of Electronic Health Record to screen potential participants. A comprehensive approach to recruitment with frequent monitoring was critical to meet the recruitment goal.

Increasing emphasis on the use of real-world evidence (RWE) to support clinical policy and regulatory decision-making has led to a proliferation of guidance, advice, and frameworks from regulatory agencies, academia, professional societies, and industry. A broad spectrum of studies use real-world data (RWD) to produce RWE, ranging from randomized trials with outcomes assessed using RWD to fully observational studies. Yet, many proposals for generating RWE lack sufficient detail, and many analyses of RWD suffer from implausible assumptions, other methodological flaws, or inappropriate interpretations. The Causal Roadmap is an explicit, itemized, iterative process that guides investigators to prespecify study design and analysis plans; it addresses a wide range of guidance within a single framework. By supporting the transparent evaluation of causal assumptions and facilitating objective comparisons of design and analysis choices based on prespecified criteria, the Roadmap can help investigators to evaluate the quality of evidence that a given study is likely to produce, specify a study to generate high-quality RWE, and communicate effectively with regulatory agencies and other stakeholders. This paper aims to disseminate and extend the Causal Roadmap framework for use by clinical and translational researchers; three companion papers demonstrate applications of the Causal Roadmap for specific use cases., Competing Interests: The contents are those of the author(s) and do not necessarily represent the official views of, nor an endorsement by, FDA/HHS, the US Government, or the authors’ affiliations. LED reports tuition and stipend support from a philanthropic gift from the Novo Nordisk corporation to the University of California, Berkeley, to support the Joint Initiative for Causal Inference. IJD is the principal investigator of a research agreement between Harvard University and Sanofi and reports consulting fees from Moderna. EK is employed by Microsoft. DA is employed by Pfizer Inc. and holds stocks in Pfizer Inc. CYV and RAH are employed by Syneos Health. CYV reports that her husband is employed by Galapagos. HR and KK are employed by Novo Nordisk A/S and own stocks in Novo Nordisk A/S. RP has received the following (directed to his institution): speaker fees from Merck and Novo Nordisk; consulting fees from Bayer AG, Corcept Therapeutics Incorporated, Dexcom, Endogenex, Inc., Gasherbrum Bio, Inc., Hanmi Pharmaceutical Co., Hengrui (USA) Ltd., Lilly, Merck, Novo Nordisk, Pfizer, Rivus Pharmaceuticals Inc., Sanofi, Scohia Pharma Inc., and Sun Pharmaceutical Industries; and grants from Hanmi Pharmaceuticals Co., Metavention, Novo Nordisk, and Poxel SA. DM is employed by Moderna. CEB is co-founder of Adaptic Health Inc., Managing Director of Pivotal Strategic Consulting, LLC, and receives consulting fees from Graticule Inc. and Sophic Alliance Inc. MA is employed by Novartis Pharma AG. JBB reports contracted fees and travel support for contracted activities for consulting work paid to the University of North Carolina by Novo Nordisk; grant support by Dexcom, NovaTarg, Novo Nordisk, Sanofi, Tolerion and vTv Therapeutics; personal compensation for consultation from Alkahest, Altimmune, Anji, AstraZeneca, Bayer, Biomea Fusion Inc., Boehringer-Ingelheim, CeQur, Cirius Therapeutics Inc., Corcept Therapeutics, Eli Lilly, Fortress Biotech, GentiBio, Glycadia, Glyscend, Janssen, MannKind, Mellitus Health, Moderna, Pendulum Therapeutics, Praetego, Sanofi, Stability Health, Terns Inc., Valo and Zealand Pharma; stock/options in Glyscend, Mellitus Health, Pendulum Therapeutics, PhaseBio, Praetego, and Stability Health; and board membership of the Association of Clinical and Translational Science. MvdL and SG report that they are co-founders of the statistical software start-up company TLrevolution, Inc. MvdL and MP report personal compensation for consultation from Novo Nordisk., (© The Author(s) 2023.)

Metabolic mechanisms underlying the heterogeneity of major adverse cardiovascular (CV) event (MACE) risk in individuals with type 2 diabetes mellitus (T2D) remain unclear. We hypothesized that circulating metabolites reflecting mitochondrial dysfunction predict incident MACE in T2D. Targeted mass-spectrometry profiling of 60 metabolites was performed on baseline plasma samples from the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS; discovery cohort) and Exenatide Study of Cardiovascular Event Lowering (EXSCEL; validation cohort) biomarker substudy cohorts. A principal components analysis metabolite factor comprising medium-chain acylcarnitines (MCACs) was associated with MACE in TECOS and validated in EXSCEL, with higher levels associated with higher MACE risk. Meta-analysis showed that long-chain acylcarnitines (LCACs) and dicarboxylacylcarnitines were also associated with MACE. Metabolites remained associated with MACE in multivariate models and favorably changed with exenatide therapy. A third cohort (Cardiac Catheterization Genetics [CATHGEN]) with T2D was assessed to determine whether these metabolites improved discriminative capability of multivariate models for MACE. Nine metabolites (MCACs and LCACs and 1 dicarboxylacylcarnitine) were associated with time to MACE in the CATHGEN cohort. Addition of these metabolites to clinical models minimally improved the discriminative capability for MACE but did significantly down reclassify risk. Thus, metabolites reporting on dysregulated mitochondrial fatty acid oxidation are present in higher levels in individuals with T2D who experience subsequent MACE. These biomarkers may improve CV risk prediction models, be therapy responsive, and highlight emerging risk mechanisms.

Background: Once-daily oral semaglutide is an effective type 2 diabetes treatment. We aimed to investigate a new formulation of oral semaglutide at higher investigational doses versus the approved 14 mg dose in adults with inadequately controlled type 2 diabetes., Methods: This global, multicentre, randomised, double-blind, phase 3b trial, carried out at 177 sites in 14 countries, enrolled adults with type 2 diabetes, glycated haemoglobin (HbA 1c ) 8·0-10·5% (64-91 mmol/mol), a BMI of 25·0 kg/m 2 or greater, receiving stable daily doses of one to three oral glucose-lowering drugs. Participants were randomly assigned (1:1:1), by means of an interactive web response system, to once-daily oral semaglutide 14 mg, 25 mg, or 50 mg for 68 weeks. Investigators, site personnel, trial participants, and trial sponsor staff were masked to dose assignment throughout the trial. The primary endpoint was change in HbA 1c from baseline to week 52, evaluated with a treatment policy estimand in the intention-to-treat population. Safety was assessed in all participants who received at least one dose of trial drug. This trial is registered with ClinicalTrials.gov, NCT04707469, and the European Clinical Trials register, EudraCT 2020-000299-39, and is complete., Findings: Between Jan 15 and Sept 29, 2021, of 2294 people screened, 1606 (n=936 [58·3%] male; n=670 [41·7%] female; mean [SD] age 58·2 [10·8] years) received oral semaglutide 14 mg (n=536), 25 mg (n=535), or 50 mg (n=535). At baseline, mean (SD) HbA 1c was 9·0% (0·8; 74·4 mmol/L [SD 8·3]) and mean bodyweight was 96·4 kg (21·6). Mean changes (SE) in HbA 1c at week 52 were -1·5 percentage points (SE 0·05) with oral semaglutide 14 mg, -1·8 percentage points (0·06) with 25 mg (estimated treatment difference [ETD] -0·27, 95% CI -0·42 to -0·12; p=0·0006), and -2·0 percentage points (0·06) with 50 mg (ETD -0·53, -0·68 to -0·38; p<0·0001). Adverse events were reported by 404 (76%) participants in the oral semaglutide 14 mg group, 422 (79%) in the 25 mg group, and 428 (80%) in the 50 mg group. Gastrointestinal disorders, which were mostly mild to moderate, occurred more frequently with oral semaglutide 25 mg and 50 mg than with 14 mg. Ten deaths occurred during the trial; none were judged to be treatment related., Interpretation: Oral semaglutide 25 mg and 50 mg were superior to 14 mg in reducing HbA 1c and bodyweight in adults with inadequately controlled type 2 diabetes. No new safety concerns were identified., Funding: Novo Nordisk., Competing Interests: Declaration of interests VRA reports receiving consultancy fees from Applied Therapeutics, Fractyl, Novo Nordisk, Pfizer, and Sanofi, and research grant support (to their institution) from Applied Therapeutics, Eli Lilly, Fractyl, Novo Nordisk, and Sanofi. LB, EC, and SG are employees and shareholders in Novo Nordisk. JA reports consulting fees or speaking honoraria from Astra Zeneca, Boehringer Ingelheim, Lilly, and Novo Nordisk. FKK reports participating in scientific advisory panels or speakers' bureaus for, consulting fees, or receiving research support from Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Carmot Therapeutics, Eli Lilly, Gubra, Lupin, MedImmune, MSD–Merck, Mundipharma, Norgine, Novo Nordisk, Pharmacosmos, Sanofi, ShouTi, Zealand Pharma, and Zucara; is a minority shareholder in Antag Therapeutics, and co-owner of the weight loss clinic Medicinsk Vægttabsbehandling ApS. SDP reports consulting fees or speaking honoraria from Abbott, AstraZeneca, Bausch, Bayer, Boehringer Ingelheim, Dexcom, HLS, Janssen, Lilly, Merck, Novo Nordisk, Pfizer, and Sanofi; and research studies for AstraZeneca, Boehringer Ingelheim, Lilly, Medpace, and Novo Nordisk. JBB contracted consulting fees and travel support for contracted activities that are paid to the University of North Carolina by Novo Nordisk and vTv Therapeutics; has received grant support from Dexcom, NovaTarg, Novo Nordisk, Sanofi, Tolerion, and vTv Therapeutics; has received personal compensation for consultation from Alkahest, Altimmune, Anji, AstraZeneca, Bayer, Boehringer Ingelheim, Carmot Therapeutics, CeQur, Cirius Therapeutics, Corcept Therapeutics, Dasman Diabetes Institute (Kuwait), Eli Lilly, Fortress Biotech, GentiBio, Glycadia, Glyscend, Janssen, Mellitus Health, Moderna, Pendulum Therapeutics, Praetego, Sanofi, Stability Health, Terns, and Valo; has received payment for expert testimony from Medtronic; and in lieu of payment for consultation he has received stock or options in Glyscend, Mellitus Health, Pendulum Therapeutics, PhaseBio, Praetego, and Stability Health., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background: Observational and preclinical data suggest metformin may prevent severe coronavirus disease 2019 (COVID-19) outcomes., Purpose: We conducted a systematic review of randomized, placebo-controlled clinical trials of metformin treatment for COVID-19 to determine whether metformin affects clinical or laboratory outcomes in individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and present a structured summary of preclinical data., Study Selection: Two independent reviewers searched PubMed, Scopus, Cochrane COVID-19 Study Register, and ClinicalTrials.gov on 1 February 2023 with no date restrictions for trials where investigators randomized adults with COVID-19 to metformin versus control and assessed clinical and/or laboratory outcomes of interest. The Cochrane Risk of Bias 2 tool was used to assess bias., Data Extraction: Two reviewers extracted data pertaining to prespecified outcomes of each interest from each included trial., Data Synthesis: The synthesis plan was developed a priori and was guided by Synthesis Without Meta-analysis (SWiM) guidelines. Summary tables and narrative synthesis were used (PROSPERO, 2022, CRD42022349896). Three randomized trials met inclusion criteria. In two of the trials investigators found that metformin improved clinical outcomes (prevented need for oxygen and prevented need for acute health care use), and in the third trial a larger portion of adults with diabetes were enrolled but results did show a direction of benefit similar to that of the other trials in the per-protocol group. In the largest trial, subjects were enrolled during the delta and omicron waves and vaccinated individuals were included. The certainty of evidence that metformin prevents health care use due to COVID-19 was moderate per Grading of Recommendations Assessment, Development and Evaluation (GRADE) criteria. Many preclinical studies have shown metformin to be effective against SARS-CoV-2., Limitations: Limitations include inclusion of only three trials and heterogeneity between trials., Conclusions: Future trials will help define the role of metformin in COVID-19 treatment guidelines., (© 2023 by the American Diabetes Association.)

Aim: To describe the design of the SOUL trial (Semaglutide cardiOvascular oUtcomes triaL) and the baseline clinical data of its participants., Materials and Methods: In SOUL, the effects of oral semaglutide, the first oral glucagon-like peptide-1 receptor agonist, on the risk of cardiovascular (CV) events in individuals with type 2 diabetes and established atherosclerotic CV disease (ASCVD) and/or chronic kidney disease (CKD) will be assessed. SOUL is a randomized, double-blind, parallel-group, placebo-controlled CV outcomes trial comparing oral semaglutide (14 mg once daily) with placebo, both in addition to standard of care, in individuals aged ≥50 years with type 2 diabetes and evidence of ASCVD (coronary artery disease [CAD], cerebrovascular disease, symptomatic peripheral arterial disease [PAD]) and/or CKD (estimated glomerular filtration rate <60 mL/min/1.73 m 2 ). The primary outcome is time from randomization to first occurrence of a major adverse CV event (MACE; a composite of CV death, nonfatal myocardial infarction or nonfatal stroke). This event-driven trial will continue until 1225 first adjudication-confirmed MACEs have occurred. Enrolment has been completed., Results: Overall, 9650 participants were enrolled between June 17, 2019 and March 24, 2021 (men 71.1%, White ethnicity 68.9%, mean age 66.1 years, diabetes duration 15.4 years, body mass index 31.1 kg/m 2 , glycated haemoglobin 63.5 mmol/mol [8.0%]). The most frequently used antihyperglycaemic medications at baseline were metformin (75.7%), insulin and insulin analogues (50.5%), sulphonylureas (29.1%), sodium-glucose cotransporter-2 inhibitors (26.7%) and dipeptidyl peptidase-4 inhibitors (23.0%). At randomization, 70.7% of participants had CAD, 42.3% had CKD, 21.1% had cerebrovascular disease and 15.7% had symptomatic PAD (categories not mutually exclusive). Prevalent heart failure was reported in 23.0% of participants., Conclusion: SOUL will provide evidence regarding the CV effects of oral semaglutide in individuals with type 2 diabetes and established ASCVD and/or CKD., (© 2023 The Authors. Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.)

Time spent in glycemic target range (time in range [TIR]; plasma glucose 70-180 mg/dL [3.9-10.0 mmol/L]) as a surrogate endpoint for long-term diabetes-related outcomes requires validation. This post hoc analysis investigated the association between TIR, derived from 8-point glucose profiles (derived TIR [dTIR]) at 12 months, and time to cardiovascular or severe hypoglycemic episodes in people with type 2 diabetes in the DEVOTE trial. At 12 months, dTIR was significantly negatively associated with time to first major adverse cardiovascular event ( P  = 0.0087), severe hypoglycemic episode ( P  < 0.0001), or microvascular event ( P  = 0.024). A nonsignificant trend was seen toward association between 12-month hemoglobin A1c (HbA1c) and these outcomes, but this was no longer seen after addition of dTIR to the model. The results support targeting TIR >70% and suggest dTIR could be used in addition to, or in some instances in place of, HbA1c as a clinical biomarker. Trial registration details: ClinicalTrials.gov, NCT01959529.

Clinical trial processes are unnecessarily inefficient and costly, slowing the translation of medical discoveries into treatments for people living with disease. To reduce redundancies and inefficiencies, a group of clinical trial experts developed a framework for clinical trial site readiness based on existing trial site qualifications from sponsors. The site readiness practices are encompassed within six domains: research team, infrastructure, study management, data collection and management, quality oversight, and ethics and safety. Implementation of this framework for clinical trial sites would reduce inefficiencies in trial conduct and help prepare new sites to enter the clinical trials enterprise, with the potential to improve the reach of clinical trials to underserved communities. Moreover, the framework holds benefits for trial sponsors, contract research organizations, trade associations, trial participants, and the public. For novice sites considering future trials, we provide a framework for site preparation and the engagement of stakeholders. For experienced sites, the framework can be used to assess current practices and inform and engage sponsors, staff, and participants. Details in the supplementary materials provide easy access to key regulatory documents and resources. Invited perspective articles provide greater depth from a systems, DEIA (diversity, equity, inclusion, and accessibility) and decentralized trials perspective., Competing Interests: JBB has contracted consulting fees and travel support for contracted activities paid to the University of North Carolina by Novo Nordisk; grant support paid to the University of North Carolina by Dexcom, NovaTarg, Novo Nordisk, Sanofi, Tolerion and vTv Therapeutics; payments for consultation from Alkahest, Altimmune, Anji, AstraZeneca, Bayer, Biomea Fusion Inc., Boehringer-Ingelheim, CeQur, Cirius Therapeutics Inc., Dasman Diabetes Center (Kuwait), Eli Lilly, Fortress Biotech, GentiBio, Glycadia, Glyscend, Janssen, MannKind, Mediflix, Medscape, Mellitus Health, Moderna, Pendulum Therapeutics, Praetego, ReachMD, Sanofi, Stability Health, Valo, Zealand Pharma; stock/options in Glyscend, Mellitus Health, Pendulum Therapeutics, PhaseBio, Praetego, and Stability Health., (© The Author(s) 2023.)

Introduction: Once-weekly subcutaneous semaglutide, a glucagon-like peptide-1 analog, is approved in the USA as an adjunct to diet and exercise for adults with inadequately controlled type 2 diabetes (T2D) to improve glycemic control and reduce the risk of major adverse cardiovascular events in people with T2D and established cardiovascular disease. The Semaglutide Unabated Sustainability in Treatment of Type 2 Diabetes (SUSTAIN) phase III clinical trial program demonstrated the efficacy and safety of once-weekly subcutaneous semaglutide; however, determining its effectiveness in a real-world setting could support decision-making by clinicians, payers and policy makers in routine clinical practice., Research Design and Methods: SEmaglutide PRAgmatic (SEPRA) is an ongoing open-label, randomized, pragmatic clinical trial designed to compare the effects of once-weekly subcutaneous semaglutide versus standard of care in US health-insured adults with T2D and physician-determined inadequate glycemic control. The primary end point is the proportion of participants achieving glycated hemoglobin (HbA1c) <7.0% at year 1; other key outcomes include glycemic control, weight loss, healthcare utilization, and patient-reported outcomes. Individual-level data will be collected from routine clinical practice and health insurance claims. The last patient last visit is expected by June 2023., Results: Between July 2018 and March 2021, 1278 participants were enrolled from 138 study sites across the USA. At baseline, 54% were male with mean±SD age 57.4±11.1 years and body mass index 35.7±8.0 kg/m 2 . Mean diabetes duration was 7.4±6.0 years and mean HbA1c was 8.5±1.6%. At baseline, concomitant antidiabetes medications included metformin, sulfonylureas, sodium-glucose co-transporter-2 inhibitors, and dipeptidyl peptidase-4 inhibitors. The majority of participants had hypertension and dyslipidemia. The trial design was self-assessed using the PRagmatic Explanatory Continuum Indicator Summary-2 tool by the study steering group and was scored 4-5 in all domains suggesting a highly pragmatic study., Conclusions: SEPRA, a highly pragmatic ongoing study, will provide data on the effects of once-weekly subcutaneous semaglutide in a real-world setting when used during routine management of T2D., Trial Registration Number: NCT03596450., Competing Interests: Competing interests: BPS received support for the present manuscript from Novo Nordisk as a full-time employee. Holds stock or stock options for Novo Nordisk as an employee and Bristol Myers Squibb as a former employee. JBB received support for the present manuscript from Novo Nordisk, funded the study, writing support, and fees to my institution. Received grants from NIH, Dexcom, NovaTarg, Novo Nordisk, Sanofi, Tolerion, and vTv Therapeutics for clinical trials. Consulting fees (personal) from Alkahest, Altimmune, Anji, AstraZeneca, Bayer, Biomea Fusion, Boehringer-Ingelheim, CeQur, Cirius Therapeutics, Dasman Diabetes Center (Kuwait), Eli Lilly, Fortress Biotech, GentiBio, Glycadia, Glyscend, Janssen, MannKind, Mediflix, Medscape, Mellitus Health, Moderna, Pendulum Therapeutics, Praetego, ReachMD, Sanofi, Stability Health, Valo, Zealand Pharma. Consulting fees (funds to institution) from Novo Nordisk. Support for attending meetings and/or travel from AstraZeneca, Boehringer-Ingelheim, Dasman Diabetes Institute, Eli Lilly, Novo Nordisk, Zealand in the context of consulting. Participation on a data safety monitoring board or advisory board from Alkahest, Altimmune, Anji, AstraZeneca, Bayer, Biomea Fusion, Boehringer Ingelheim, CeQur, Cirius Therapeutics, Eli Lilly, GentiBio, Glycadia, Glyscend, Janssen, MannKind, Mellitus Health, Moderna, Pendulum Therapeutics, Praetego, Sanofi, Stability Health, Valo, Zealand Pharma. Leadership or fiduciary role in other board, society, committee, or advocacy group, paid or unpaid from Association for Clinical and Translational Science. Holds stock or stock options for Glyscend, Mellitus Health, Pendulum Therapeutics, PhaseBio, Praetego, and Stability Health. Is a member of the Editorial Board of BMJ Open Diabetes Research & Care. MJC received support for the present manuscript from HealthCore. Employer HealthCore received funding from Novo Nordisk to perform the study services. Holds stock or stock options for Elevance Health as a stockholder in ELV, which is the parent company of HealthCore. EWZ received medical writing support from Spirit Medical Communications. Support for attending meetings and/or travel from Novo Nordisk as an employee. Other financial or non-financial interests from Novo Nordisk as an employee. BJH received support for the present manuscript from Novo Nordisk, as sponsor of the SEPRA trial, contracted with employer, HealthCore, to serve as the data coordinating center for the trial, performing all data collection and analysis, and supporting manuscript writing activities. HNC received support for the present manuscript from Novo Nordisk as an employee. Holds stock or stock options for Novo Nordisk. VW received support for the present manuscript from HealthCore. Employer HealthCore received funding from Novo Nordisk to perform the study services. Holds stock or stock options for Elevance Health as a stockholder in ELV, which is the parent company of HealthCore., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Long-term sequelae of severe acute respiratory coronavirus-2 (SARS-CoV-2) infection may include increased incidence of diabetes. Here we describe the temporal relationship between new type 2 diabetes and SARS-CoV-2 infection in a nationwide database. We found that while the proportion of newly diagnosed type 2 diabetes increased during the acute period of SARS-CoV-2 infection, the mean proportion of new diabetes cases in the 6 months post-infection was about 83% lower than the 6 months preinfection. These results underscore the need for further investigation to understand the timing of new diabetes after COVID-19, etiology, screening, and treatment strategies., Competing Interests: Dr. Buse’s contracted consulting fees and travel support for contracted activities are paid to the University of North Carolina by Adocia, AstraZeneca, Eli Lilly, Intarcia Therapeutics, MannKind, Novo Nordisk, Sanofi, Senseonics, and vTv Therapeutics; he reports grant support from AstraZeneca, Dexcom, Eli Lilly, Intarcia Therapeutics, Johnson & Johnson, Lexicon, NovaTarg, Novo Nordisk, Sanofi, Theracos, Tolerion, and vTv Therapeutics; he has received fees for consultation from Anji Pharmaceuticals, AstraZeneca, Boehringer Ingelheim, Cirius Therapeutics Inc, Eli Lilly, Fortress Biotech, Janssen, Mellitus Health, Moderna, Pendulum Therapeutics, Praetego, Stability Health, and Zealand Pharma; he holds stock/options in Mellitus Health, Pendulum Therapeutics, PhaseBio, Praetego, and Stability Health; and he is supported by grants from the National Institutes of Health, Patient Centered Outcomes Research Institute, Juvenile Diabetes Research Foundation International and the American Diabetes Association. Dr. Stürmer does not accept personal compensation of any kind from any pharmaceutical company. He owns stock in Novartis, Roche, and Novo Nordisk. The remaining authors have no conflicts of interest to declare., (© The Author(s) 2023.)

Background: Despite increased use of continuous glucose monitoring (CGM) systems, studies to quantify patterns of CGM use are limited. In December 2018, a policy change by a commercial insurer expanded coverage of CGM through the pharmacy benefit, creating an opportunity to evaluate the impact of this change on CGM utilization. Research Design and Methods: Pharmacy and medical claims from 2016 to 2020 were used to estimate the prevalence of CGM use among insulin users with type 1 diabetes mellitus (T1DM) or type 2 diabetes mellitus (T2DM) before and after the policy change. Change in CGM use was assessed using an interrupted time series design. Results: At the beginning of the study period, 18.8% of T1DM patients and 1.2% of T2DM patients used CGM. Use rose to 30.5% and 6.6% in the quarter before the policy change. The policy resulted in an immediate 9.5% ( P  < 0.0001) and 2.8% ( P  < 0.0001) change in use and increased the rate of quarterly change by 0.5% ( P  = 0.002) and 0.8% ( P  < 0.0001). At the end of the study period, 58.2% and 14.9% of T1DM and T2DM patients used CGM. Conclusion: CGM use significantly increased after addition to the pharmacy benefit. Rate of change in CGM use was lower in T1DM compared to the T2DM population, but overall use remained higher among patients with T1DM. Increased CGM use in the population studied aligns with those whose clinical guidelines suggest would most likely benefit. Additional work is needed to evaluate the impact of this benefit change on health care spending and outcomes.

Healthcare datasets obtained from Electronic Health Records have proven to be extremely useful for assessing associations between patients' predictors and outcomes of interest. However, these datasets often suffer from missing values in a high proportion of cases, whose removal may introduce severe bias. Several multiple imputation algorithms have been proposed to attempt to recover the missing information under an assumed missingness mechanism. Each algorithm presents strengths and weaknesses, and there is currently no consensus on which multiple imputation algorithm works best in a given scenario. Furthermore, the selection of each algorithm's parameters and data-related modeling choices are also both crucial and challenging. In this paper we propose a novel framework to numerically evaluate strategies for handling missing data in the context of statistical analysis, with a particular focus on multiple imputation techniques. We demonstrate the feasibility of our approach on a large cohort of type-2 diabetes patients provided by the National COVID Cohort Collaborative (N3C) Enclave, where we explored the influence of various patient characteristics on outcomes related to COVID-19. Our analysis included classic multiple imputation techniques as well as simple complete-case Inverse Probability Weighted models. Extensive experiments show that our approach can effectively highlight the most promising and performant missing-data handling strategy for our case study. Moreover, our methodology allowed a better understanding of the behavior of the different models and of how it changed as we modified their parameters. Our method is general and can be applied to different research fields and on datasets containing heterogeneous types., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Inc.)