Centre-specific variation in renal transplant outcomes in Canada
Bibliographic record
Abstract
BACKGROUND: The 'centre effect' has accounted for significant variation in renal allograft outcomes in the United States and Europe. To determine whether similar variation exists in Canada, we analysed mortality and graft failure (GF) rates among Canadian end-stage renal disease patients who received a renal allograft from 1988 to 1997 (n = 5082) across 20 transplant centres. METHODS: Patients were followed from the date of transplantation to the time of GF and/or death. A Cox proportional hazards model was used to estimate mortality and GF hazard ratios (HRs) adjusted for relevant covariates, including centre volume. Centre-specific HRs were derived by comparing each centre's outcome rates against all others. RESULTS: Twenty centres were included in the analysis. There was significant centre-specific variation in recipient and transplant characteristics (e.g. age, diabetes mellitus, donor source and centre volume) as well as covariate-adjusted facility-specific outcome rates. Facility-specific HRs for GF (including death with a functioning graft) ranged from 0.51 to 1.77, while mortality HRs (including death beyond GF) showed a similar spread (0.44-1.84). These HRs represent a 3- to 4-fold difference in transplant outcomes among the 20 centres studied. Centres performing less than 200 transplants over the study period were associated with lower graft and patient survival. CONCLUSIONS: These findings demonstrate significant centre-specific variation in the success of renal transplantation in Canada. Further studies are needed to elucidate the causes of this variation, with the goal of developing strategies to minimize the centre effect and ensure the best possible outcomes for all renal transplant recipients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".