Occurrence of Gastrointestinal Adverse Events Upon GLP-1 Receptor Agonist Initiation With Concomitant Metformin Use: A Post Hoc Analysis of LEADER, STEP 2, SUSTAIN-6, and PIONEER 6.

Objective: To assess the impact of concomitant metformin use on gastrointestinal adverse events during the initiation and titration of a glucagon-like peptide 1 receptor agonist (GLP-1RA).

Research Design And Methods: Using data from four clinical trials of liraglutide and semaglutide (Liraglutide Effect and Action in Diabetes: Evaluation of Cardiovascular Outcome Results [LEADER], Semaglutide Treatment Effect in People with Obesity [STEP 2], Trial to Evaluate Cardiovascular and Other Long-Term Outcomes With Semaglutide in Subjects With Type 2 Diabetes [SUSTAIN-6], and Peptide Innovation for Early Diabetes Treatment [PIONEER] 6), we compared the incidence of gastrointestinal adverse events during GLP-1RA initiation and titration in participants with and without concomitant metformin use.

Results: Of 16,996 participants, 12,928 (76%) were treated with metformin.

Kidney function loss and albuminuria progression with GLP-1 receptor agonists versus basal insulin in patients with type 2 diabetes: real-world evidence.

Background: In clinical trials enrolling patients with type 2 diabetes (T2D) at high cardiovascular risk, many glucagon-like peptide-1 receptor agonists (GLP-1 RAs) improved albuminuria status and possibly mitigated kidney function loss. However, limited data are available regarding the effects of GLP-1 RAs on albuminuria status and kidney function in real-world settings, including populations with a lower baseline cardiovascular and kidney risk. We assessed the association of GLP-1 RAs initiation with long-term kidney outcomes in the Maccabi Healthcare Services database, Israel.

Diabetes medications and associations with Covid-19 outcomes in the N3C database: A national retrospective cohort study.

Background: While vaccination is the most important way to combat the SARS-CoV-2 pandemic, there may still be a need for early outpatient treatment that is safe, inexpensive, and currently widely available in parts of the world that do not have access to the vaccine. There are in-silico, in-vitro, and in-tissue data suggesting that metformin inhibits the viral life cycle, as well as observational data suggesting that metformin use before infection with SARS-CoV2 is associated with less severe COVID-19. Previous observational analyses from single-center cohorts have been limited by size.

Association Between Glucagon-Like Peptide 1 Receptor Agonist and Sodium-Glucose Cotransporter 2 Inhibitor Use and COVID-19 Outcomes.

Objective: To determine the respective associations of premorbid glucagon-like peptide-1 receptor agonist (GLP1-RA) and sodium-glucose cotransporter 2 inhibitor (SGLT2i) use, compared with premorbid dipeptidyl peptidase 4 inhibitor (DPP4i) use, with severity of outcomes in the setting of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

Research Design And Methods: We analyzed observational data from SARS-CoV-2-positive adults in the National COVID Cohort Collaborative (N3C), a multicenter, longitudinal U.S.

An indirect treatment comparison of the efficacy of insulin degludec/liraglutide (IDegLira) and insulin glargine/lixisenatide (iGlarLixi) in patients with type 2 diabetes uncontrolled on basal insulin.

Aims: To obtain estimates of the relative treatment effects between insulin degludec/liraglutide (IDegLira) and insulin glargine U100/lixisenatide (iGlarLixi) in patients with type 2 diabetes mellitus (T2DM) uncontrolled on basal insulin therapy.

Materials And Methods: Data from phase 3 trials providing evidence for estimating the relative efficacy and safety of IDegLira vs iGlarLixi in patients uncontrolled on basal insulin-only regimens were used in this analysis. Outcomes of interest were changes in HbA, body weight and insulin dose, and rate ratio of hypoglycemia.

Nonlinear denoising and analysis of neuroimages with kernel principal component analysis and pre-image estimation.

We investigate the use of kernel principal component analysis (PCA) and the inverse problem known as pre-image estimation in neuroimaging: i) We explore kernel PCA and pre-image estimation as a means for image denoising as part of the image preprocessing pipeline. Evaluation of the denoising procedure is performed within a data-driven split-half evaluation framework. ii) We introduce manifold navigation for exploration of a nonlinear data manifold, and illustrate how pre-image estimation can be used to generate brain maps in the continuum between experimentally defined brain states/classes.