B-295 Lower Tacrolimus Trough Levels as a Predictor of Antibody-Mediated Rejection in Kidney Transplant Patients
Bibliographic record
Abstract
Abstract Background Successful kidney transplantation requires compatibility between the organ recipient and donor in Human Leukocyte Antigen (HLA) matching. If the donor and recipient are not compatible, the recipient’s immune system may attack the transplanted kidney, leading to antibody-mediated rejection (AMR) or cell-mediated rejection (CMR), the latter driven by T-cells. Even in well-matched transplants, immunosuppressive drugs, such as tacrolimus, are prescribed to minimize the risk of rejection. A recent study conducted in Manitoba, Canada, found that kidney transplant patients who develop donor-specific antibodies (DSA)—an indirect marker of AMR—exhibited lower tacrolimus trough levels compared to patients without DSA. However, not all patients with DSA develop AMR, and the gold standard for diagnosing AMR remains a biopsy. The aim of this study was to examine whether lower tacrolimus levels correlate with biopsy-confirmed AMR or CMR. Methods Tacrolimus levels from 329 kidney transplant patients in Saskatoon, Saskatchewan, Canada were extracted from the Laboratory Information System (LIS, SoftLab) between 2012 and 2024. Renal biopsy reports from the same period were reviewed to identify cases of AMR or CMR, and patients were classified into one of three groups: AMR group, CMR group, and No rejection (control) group. Median tacrolimus levels were analyzed at 0–3, 4–6, and 10–12 months post-transplant and within six months before the first documented AMR or CMR episode. Statistical significance between groups was assess by ANOVA and Šídák’s multiple comparisons test in GraphPad Prism. Results Overall, 32 patients developed AMR, and 90 patients developed CMR over the study period. No significant differences in median tacrolimus levels were observed during the first-year post-transplant, suggesting no immediate impact on rejection risk. However, in the six months leading up to AMR development, patients had significantly lower tacrolimus levels compared to those who did not develop AMR (P < 0.05). No significant differences in tacrolimus levels were observed between patients with or without CMR. These findings align with the Manitoba study, suggesting that lower tacrolimus trough levels may serve as a predictor for AMR development. Monitoring tacrolimus levels alongside renal function could help improve allograft outcome assessments. Conclusion Lower tacrolimus trough levels are associated with an increased risk of AMR but not CMR. Future studies w
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".