A Propensity Score–weighted Comparison of Outcomes Between Living and Standard Criteria Deceased Donor Kidney Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: Consider a theoretical situation in which 2 patients with similar baseline characteristics receive a kidney transplant on the same day: 1 from a standard criteria deceased donor, the other from a living donor. Which kidney transplant will last longer? METHODS: We conducted a population-based cohort study using linked administrative healthcare databases from Ontario, Canada, from January 1, 2005, to March 31, 2014, to evaluate several posttransplant outcomes in individuals who received a kidney transplant from a standard criteria deceased donor (n = 1523) or from a living donor (n = 1373). We used PS weighting using overlap weights, a novel weighting method that emphasizes the population of recipients with the most overlap in baseline characteristics. RESULTS: Compared with recipients of a living donor, the rate of all-cause graft failure was not statistically higher for recipients of a standard criteria deceased donor (hazard ratio, 1.1; 95% confidence interval [CI], 0.8-1.6). Recipients of a standard criteria deceased donor, compared with recipients of a living donor had a higher rate of delayed graft function (23.6% versus 18.7%; odds ratio, 1.3; 95% CI, 1.0-1.6) and a longer length of stay for the kidney transplant surgery (mean difference, 1.7 d; 95% CI, 0.5-3.0). CONCLUSIONS: After accounting for many important donor and recipient factors, we failed to observe a large difference in the risk of all-cause graft failure for recipients of a standard criteria deceased versus living donor. Some estimates were imprecise, which meant we could not rule out the presence of smaller clinically important effects.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".