Comparison of Mortality Risk for Dialysis Patients and Cadaveric First Renal Transplant Recipients in Ontario, Canada
Bibliographic record
Abstract
In population-based studies, renal transplantation has been shown to improve survival compared to dialysis patients awaiting transplantation in the United States. However, dialysis mortality in the United States is higher than in Canada. Whether transplantation offers a survival advantage in regions where dialysis survival is superior to that in the United States is uncertain. This study examines a cohort of 1156 patients who started end-stage renal disease (ESRD) therapy and were wait-listed for cadaveric renal transplantation in the province of Ontario, Canada between January 1, 1990 and December 31, 1994. Patients were followed from wait-listing for renal transplant (n = 1156), to cadaveric first renal transplant (n = 722), to death, or to study end (December 31, 1995). The annual crude mortality rates for wait-listed dialysis patients and transplanted patients were 5.0 and 3.4%, respectively. In Cox proportional hazards models, mortality in wait-listed patients was associated with increased age and diabetes, but not time from onset of ESRD to wait-listing. Factors associated with death following transplantation include older age, diabetes, and longer time spent on the waiting list before transplantation. In a time-dependent Cox regression model, the relative risk of death after transplantation compared to dialysis varied in a time-dependent manner. Covariates associated with increased risk included older age, diabetes, and time from onset of ESRD to wait-listing. The average relative risk (RR) of dying was 2.91 (95% confidence interval [CI], 1.34 to 6.32) in the first 30 d after transplantation, but was significantly lower 1 yr after transplantation (RR 0.25; 95% CI, 0.14 to 0.42), indicating a beneficial long-term effect when compared to wait-listed dialysis patients. This long-term benefit was most evident in subgroups of patients with diabetes (RR 0.38; 95% CI, 0.17 to 0.87) and glomerulonephritis (RR 0.13; 95% CI, 0.04 to 0.39) as the cause of ESRD. The survival advantage associated with renal transplantation is evident in this cohort of patients with a lower wait-listed dialysis mortality than that reported previously in the United States. The magnitude of the treatment effect is consistent across studies.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| 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".