The Efficacy and Safety of SGLT2 Inhibitors and GLP1 Receptor Agonists in Kidney Transplant Recipients
Bibliographic record
Abstract
Background: Sodium-glucose cotransporter 2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP1RA) decrease adverse cardiorenal outcomes in the general population. We aimed to evaluate the efficacy and safety of SGLT2i and GLP1RA monotherapy and combination therapy in kidney transplant recipients (KTR). Methods: This was a retrospective cohort study of all adult KTR started on SGLT2i and/or GLP1RA between January 1, 2000 and December 31, 2021. Baseline characteristics, drug safety/tolerability, estimated glomerular filtration rate (eGFR), and cardiorenal outcomes were collected. Results: Of 227 patients analyzed, 78 were on SGLT2i, 79 on GLP1RA and 70 on combination therapy. 120 patients had pretransplant diabetes (DM) (53.6%) and 103 had post-transplant DM (46.0%). Compared to the period before drug initiation, there were no differences in rates of CV events and graft failure with either monotherapy or combination therapy. After one month, SGLT2 inhibition resulted in a median eGFR decline of 6 ml/min/1.73m2 (interquartile range -11 to 3.5) (Figure 1). Drug discontinuation was high, with 19.2% of SGLT2i users, 28.7% of GLP1RA and 41.4% on combination therapy stopping therapy - ‘hospitalization' with SGLT2i and ‘intolerance' with GLP1RA and combination therapy were the most frequent causes of discontinuation. However, compared to the period before drug initiation, rates of urinary tract infections, ketoacidosis, acute kidney injury and hepato-pancreato-biliary complications were not significantly different.Figure 1:: Individual patient trends in eGFR over 1 month after drug initiationConclusions: SGLT2i, GLP-1RA and combination therapy appear to be safe in KTR, though drug discontinuation is relatively common. The acute eGFR ‘dip' observed with SGLT2 inhibition suggests tubular-glomerular mechanisms are intact in this unique population.
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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 | 0.004 |
| 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 | 0.001 |
| 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".