CADAVERIC RENAL TRANSPLANTATION AND EXPANDED CRITERIA DONORS: SHOULD WE REASSESS THEIR USE?
Bibliographic record
Abstract
O230 Aims: Renal Transplant waiting lists continue to grow. Living donation has helped but is unavailable for many recipients. The use of expanded criteria cadaveric donors may be an alternative. Since 1997 we have liberalized our cadaveric donor criteria and assessed our results using a standard immunosuppression protocol. Methods: Between January 1st, 1997 to September 30th, 2003 we performed 172 cadaveric renal transplants using induction with Thymoglobulin (Thy), Mycophenolate Mofetil (MMF) and Predinisone. Calcineurin inhibitors (80% tacrolimus (TAC), 20% Cyclosporine Neoral (CsA)) were introduced only when serum creatinine was < 250 μmoles/L (3.0mg/dl). We divided the patients into 2 groups according to the scoring system described by Nyberg et al. (American Journal of Transplantation 2003 (2; 3:715) which was based on donor age, history of hypertension, creatinine clearance before procurement, cause of death, and HLA mismatch. Group 1 (optimal donors) had a score of 0-19 and group 2 (extended criteria donors) had a score of 20-39. We compared the 2 groups for graft survival, acute rejection rate (ACR), creatinine at 1year, delayed graft function (DGF= need for hemodialysis or creatinine >250μmol/L on day 5). Death with a functioning graft was considered to be a graft loss. Results:FigureOverall, graft survival for all 172 patients was 92.2 and 81.8% at 1 & 5 years. Patients in Group 2 had a higher rate of DGF and a higher creatinine at 1 year, however graft survival at 5 years was still relatively good (78 vs 83% p=ns). Patients with DGF (n=61) had a lower 1 and 5 year graft survival compared to patients without DGF (86 vs 98 % and 72 vs 88% p<0.004) irrespective of the group they belong to. DGF had an equally bad impact on “ideal” donors and “extended criteria” donors. All patients with DGF had a renal biopsy in the 1st 4 weeks after transplant and none had rejection. Conclusions: A protocol with Thymoglobulin, MMF, Predinisone and TAC or CsA results in very low acute rejection rate and excellent graft survival. Extended criteria donors had a higher risk for DGF. DGF resulted in poorer 5 year graft survival in both groups. Extended criteria donors without DGF had an excellent 5 year graft survival. Extended criteria donors should be used, and strategies to minimize DGF should result in excellent graft survival
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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 | 0.023 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".