Retour en dialyse après échec de transplantation : comment améliorer les résultats dans cette population fragile ?
Bibliographic record
Abstract
Ten to 15 % of transplant recipients will return to dialysis, or require another transplantation within 5years, rising to 23 % by 10years, and failed transplantation is now one of the major indications for starting dialysis, accounting for almost 5 % of incident dialysis patients in the US and 10 % in France. Patients who resume dialysis post-transplantation have usually experienced an extended period of uraemia and long-term immunosuppressive therapy, and exhibit high rates of anaemia and erythropoietin resistance, hypoalbuminaemia and persistent chronic inflammation from the failed graft. These factors may increase mortality risk during the first year of dialysis, as observed in the US, but not in Canada or France. When compared to a control group of transplant-naive patients followed in the same institution in France, patients with transplant failure have a higher rate of usable arteriovenous fistula or graft, a similar rate of non-planned dialysis, and initiate dialysis with a higher glomerular filtration rate. We suggest that patient survival in dialysis after graft loss is influenced by both patient characteristics and quality of care, and this may explain the favourable outcome of this specific dialysis population in France.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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 teacher head, 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".