<scp>Glucagon‐like peptide</scp> ‐1 receptor agonists and <scp>sodium‐glucose cotransporter</scp> ‐2 inhibitors for the treatment of diabetes mellitus in liver transplant recipients
Bibliographic record
Abstract
Abstract Aim To investigate the efficacy and safety of glucagon‐like peptide‐1 receptor agonists (GLP‐1RAs) and sodium‐glucose cotransporter‐2 (SGLT2) inhibitors in liver transplant (LT) recipients with diabetes. Methods A single‐centre, retrospective analysis of prospectively collected data from an LT recipient database (1990–2023) was conducted. We included adults with pre‐existing diabetes and post‐transplant diabetes, newly started on GLP‐1RAs and/or SGLT2 inhibitors after LT. Metabolic and biochemical parameters and outcomes were collected for up to 12 months after starting medications and were compared to those in patients receiving dipeptidyl peptidase‐4 (DPP‐4) inhibitors. Statistical analysis included descriptive statistics and linear mixed models. Results We included participants on GLP‐1RAs ( n = 46), SGLT2 inhibitors ( n = 87), combination therapy ( n = 12), and a DPP‐4 inhibitor comparator ( n = 217). Both GLP‐1RAs and combination therapy decreased mean glycated haemoglobin (HbA1c) levels, and combination therapy remained significant when adjusted for DPP‐4 inhibitor treatment (−3.5%, 95% CI [−6.1, −0.95]; p = 0.0089) at 12 months. All three groups had significant decreases in mean weight and body mass index, but these remained significant in the GLP‐1RA (−5.2 kg, 95% CI [−8.7, −1.7], p = 0.0039 and 1.99 kg/m 2 , 95% CI [−3.4, −0.6], p = 0.0048) and combination therapy groups (−5.4 kg, 95% CI [−10.5, −0.36], p = 0.04 and −3.4 kg/m 2 , 95% CI [−5.5, −1.3], p = 0.0015) when adjusted for DPP‐4 inhibitor treatment at 12 months. Alanine aminotransferase levels decreased with GLP‐1RA and combination therapy. There were two (1.4%) cases of graft rejection. Conclusion We found that GLP‐1RAs, SGLT2 inhibitors, and their combination, led to significant weight loss in LT recipients with diabetes. Combination therapy, in particular, lowered HbA1c and alanine aminotransferase levels compared to DPP‐4 inhibitors. Further studies are needed to assess long‐term safety and efficacy.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".