Pre‐transplant maintenance dialysis duration and outcomes after kidney transplantation: A multicenter population‐based cohort study
Bibliographic record
Abstract
The association between pre-transplant dialysis duration and post-transplant outcomes may vary by the population and endpoints studied. We conducted a population-based cohort study using linked healthcare databases from Ontario, Canada including kidney transplant recipients (n = 4461) from 2004 to 2014. Our primary outcome was total graft failure (i.e., death, return to dialysis, or pre-emptive re-transplant). Secondary outcomes included death-censored graft failure, death with graft function, mortality, hospitalization for cardiovascular events, hospitalization for infection, and hospital readmission. We presented results by pre-transplant dialysis duration (pre-emptive transplant, and .01-1.43, 1.44-2.64, 2.65-4.25, 4.26-6.45, and 6.46-36.5 years, for quintiles 1-5). After adjusting for clinical characteristics, pre-emptive transplantation was associated with a lower rate of total graft failure (adjusted hazard ratio [aHR] .68, 95% CI: .46, .99), while quintile 4 was associated with a higher rate (aHR 1.31, 95% CI: 1.01, 1.71), when compared to quintile 1. There was no significant relationship between dialysis duration and death-censored graft failure, cardiovascular events, or hospital readmission. For death with graft function and mortality, quintiles 3-5 had a significantly higher aHR compared to quintile 1, while for infection, quintiles 2-5 had a higher aHR. Longer time on dialysis was associated with an increased rate of several adverse post-transplant outcomes.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".