ReviewHealthcare (Basel, Switzerland)2026
A Narrative Review of the Metabolic Benefits of GLP-1 and GIP Receptor Agonists in Obesity.
Review in Healthcare (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Glucagon-like peptide-1 (GLP-1) and dual GLP-1 and glucose-dependent insulinotropic polypeptide (GIP) receptor agonists are highly effective therapies for overweight and obesity due to their potent ability to provide significant amounts of weight loss. There is also increasing evidence in their medium- to long-term benefits to metabolic outcomes in those with obesity, due to improvements in weight and glycemia, as well as direct action of GLP-1 on multiple organ systems. This narrative review examines the literature behind the metabolic effects in those with overweight and obesity, as well as the implications of long-term use in regard to the safety and cost-effectiveness of these agents. Improvement and prevention of metabolic disease with GLP-1 therapies remains promising, although studies of longer duration are required to further expand indications and confirm safety of therapy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.