Posttransplant Calcineurin Inhibitors Levels and Intrapatient Variability Are Not Associated With Long-term Outcomes Following Liver Transplantation
Bibliographic record
Abstract
BACKGROUND: There is an interest in understanding the association between early calcineurin inhibitors exposure post-liver transplantation (LT) and long-term outcomes. We aimed to analyze this association exploring median calcineurin inhibitor levels and intrapatient variability (IPV) in a multicenter, retrospective cohort. METHODS: Tacrolimus (Tac) and Cyclosporine (CsA) levels obtained during the first 15 days post-LT were collected. High immunosuppression (IS) was considered as a median of Tac, CsA blood trough levels 12 hours after drug administration, or blood levels 2 hours after drug administration higher than 10, 250, or 1200 ng/mL, respectively, or a peak of Tac >20 ng/mL. Optimal IS was defined as a median of Tac, CsA blood trough levels 12 hours after drug administration, or blood levels 2 hours after drug administration levels between 7 and 10, 150 and 250, or 800 and 1200 ng/mL. Low IS was defined as below the thresholds of optimal IS. IPV was estimated during the first 15 days post-LT. RESULTS: The study included 432 patients with a median follow-up of 8.65 years. IS regimen was based on either Tac or CsA in 243 (56.3%) and 189 (43.8%), respectively. There were no differences in terms of graft loss among low versus optimal and high IS groups (P = 0.812 and P = 0.451) nor in high versus low IPV (P = 0.835). Only viral hepatitis and arterial hypertension were independently associated with higher graft loss (hazard ratio = 1.729, P = 0.029 and hazard ratio = 1.570, P = 0.021). CONCLUSIONS: In contrast to what has previously been reported, no association was found between very early postoperative over IS or high IPV and long-term outcome measures following LT. Strategies aimed at reducing these long-term events should likely focus on other factors or on a different IS time window.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".