Chronic liraglutide therapy induces an enhanced endogenous glucagon‐like peptide‐1 secretory response in early type 2 diabetes
Bibliographic record
Abstract
Sustained exogenous stimulation of a hormone‐specific receptor can affect endogenous hormonal regulation. In this context, little is known about the impact of chronic treatment with glucagon‐like peptide‐1 ( GLP ‐1) agonists on the endogenous GLP ‐1 response. We therefore evaluated the impact of chronic liraglutide therapy on endogenous GLP ‐1 and glucose‐dependent insulinotropic polypeptide ( GIP ) response to an oral glucose challenge. A total of 51 people with type 2 diabetes of 2.6 ± 1.9 years’ duration were randomized to daily subcutaneous liraglutide or placebo injection and followed for 48 weeks, with an oral glucose tolerance test ( OGTT ) every 12 weeks. GLP ‐1 and GIP responses were assessed according to their respective area under the curve ( AUC ) from measurements taken at 0, 30, 60, 90 and 120 minutes during each OGTT . There were no differences in AUC GIP between the groups. By contrast, although fasting GLP ‐1 was unaffected, the liraglutide arm had ~2‐fold higher AUC GLP ‐1 at 12 weeks ( P < .001), 24 weeks ( P < .001), 36 weeks ( P = .03) and 48 weeks ( P = .03), as compared with placebo. Thus, chronic liraglutide therapy induces a previously unrecognized, robust and durable enhancement of the endogenous GLP ‐1 response, highlighting the need for further study of the long‐term effects of incretin mimetics on L ‐cell physiology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".