The Effect of Transplant Volume and Patient Case Mix on Center Variation in Kidney Transplantation Outcomes
Bibliographic record
Abstract
Background:Kidney transplantation is the optimal treatment for patients with end-stage renal disease; however, long-term outcomes remain suboptimal.Objective:The objectives of our study were to examine the variation in survival rates and determine whether center volume and case mix are associated with transplant outcomes and explain the variation across kidney transplant centers in Ontario, Canada.Design:This was a population-based cohort study using health care administrative databases.Setting:A total of 5 transplant centers across Ontario, Canada.Patients:We included adults (≥18 years) undergoing primary, solitary kidney transplantation between January 1, 2000 to December 31, 2013.Measurements:The co-primary outcomes were death-censored graft loss and total mortality.Methods:Multivariable Cox proportional hazards regression was used to assess potential associations and describe variation, using hazard ratios (HRs) with 95% confidence intervals (CIs) for each center relative to the average across all centers.Results:The study cohort included 5037 patients followed for a median of 5.3 years, interquartile range (2.7-8.6). In multivariable models, recipient age, body mass index, Charlson Index, time on dialysis, donor type, and age were found to be significantly associated with death-censored graft loss, and recipient age and sex, Charlson Index, time on dialysis, donor age, and time era of transplant were associated with total mortality. There was statistically significant variation across centers observed for death-censored graft loss (<i>P</i> = .04) with HRs ranging from 0.72 to 1.22. However, neither adjusting for case mix nor center volume meaningfully changed the HRs reflecting each center-specific effect. There was a tendency toward reduced risk of graft loss (HR, per additional 25 patients, 0.90 [95% CI, 0.78-1.04]) in centers with higher volumes. For total mortality, there was statistically significant variation across centers with HRs ranging from 0.82 to 1.13 (<i>P</i> = .04); however, neither adjusting for case mix or center volume meaningfully changed the HRs. Center volume was not significantly associated with total mortality (HR, per additional 25 patients, 1.04 [95% CI, 0.90-1.20]).Limitations:This study was limited by the small number of centers included.Conclusions:Outcomes differ across the 5 transplant centers in Ontario. We did not find any strong support for our hypotheses that case mix or center volume is responsible for these differences.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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 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".