The Ascending GLP-1 Road From Clinical Safety to Reduction of Cardiovascular Complications
Bibliographic record
Abstract
Glucagon-like peptide 1 (GLP-1) was originally identified as a gut-derived incretin hormone that lowered glycemia through potentiation of glucose-dependent insulin secretion. Subsequent studies expanded the actions of GLP-1 to include inhibition of glucagon secretion, gastric emptying, and appetite, collectively useful attributes for a glucose-lowering agent. The introduction of GLP-1 receptor (GLP-1R) agonists for the treatment of diabetes was associated with questions surrounding their safety, principally with regard to medullary thyroid cancer, pancreatitis, and pancreatic cancer, yet cardiovascular outcome trials subsequently revealed reductions in rates of stroke, myocardial infarction, and cardiovascular death with a paucity of major safety signals. We discuss the controversies, unanswered questions, and established use of GLP-1R agonists from a mechanistic and clinical perspective. We highlight methods for detection and cellular sites of GLP-1R expression, key uncertainties, recent insights, and experimental caveats surrounding the use of GLP-1R agonists for the treatment of diabetes and the reduction of diabetes-related complications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".