Variation in Kidney Transplant Referral, Living Donor Contacts, Waitlisting, and Kidney Transplant Across Regional Renal Programs in Ontario, Canada: A Population-Based Cohort Study
Bibliographic record
Abstract
Background: Previous studies conducted in publicly and privately funded health care systems suggest that access to kidney transplants may vary depending on where a patient receives their kidney care. It is poorly understood whether variability exists across the key steps required to receive a kidney transplant in a publicly funded health care system. Objective: To determine whether there is variation across Ontario's regional renal programs (RRPs) in key steps completed toward receiving a kidney transplant. Design: Population-based cohort study from November 1, 2017, to December 31, 2021, using linked administrative health care databases with a maximum follow-up of March 31, 2023. Setting: This study includes 27 RRPs and independent health facilities in Ontario, Canada. Patients: Patients approaching the need for dialysis and patients receiving maintenance dialysis with no recorded contraindication to kidney transplant. Measurements: Key steps toward receiving a kidney transplant, including (1) referred to a transplant center for an evaluation; (2) had a potential living donor contact a transplant center to be evaluated; (3) deceased donor waitlist activation; and (4) received a transplant from a living or deceased donor. Methods: For each step toward receiving a kidney transplant, we reported a unique incidence rate per 100 person-years with a 95% confidence interval (95% CI), presented by Ontario's RRPs, including the 27 RRPs and independent health facilities. We also presented results by 5 Ontario geographic regions. In an additional analysis, we examined the time to complete specific transplant steps. Results: We included 8319 individuals approaching the need for dialysis and 4869 individuals receiving maintenance dialysis. During follow-up, 2870 (34.5%) individuals approaching the need for dialysis initiated maintenance dialysis. In individuals approaching the need for dialysis, we found the rate of a potential living kidney donor contacting a transplant center to be evaluated varied more than 17-fold across RRPs from 0.67 (95% CI = 0.1, 4.8) to 11.7 (95% CI = 9.2, 14.9). In the dialysis cohort, the average number of steps completed toward receiving a kidney transplant varied almost 4-fold across RRPs from 11.7 (95% CI = 9.3, 14.8) to 44.0 (95% CI = 38.6, 50.1) steps per 100 person-years. The average rate of each step measured separately also varied widely, with the rate of referral to a transplant center for an evaluation (per 100 person-years) varying across RRPs from 6.0 (95% CI = 4.2, 8.5) to 47.9 (95% CI = 42.6, 53.8), the rate of a potential living kidney donor contacting a transplant center to be evaluated from 1.5 (95% CI = 0.78, 2.9) to 10.7 (95% CI = 7.9, 14.5), the rate of deceased donor waitlisting from 2.9 (95% CI = 1.9, 4.4) to 13.2 (95% CI = 11.0, 15.8), and the rate of kidney transplant from 2.0 (95% CI = 1.1, 3.4) to 12.6 (95% CI = 10.8, 14.8). When examining the results by 5 Ontario geographic regions, we found patients receiving maintenance dialysis in Northern Ontario had substantially lower rates of completing key steps toward receiving a kidney transplant. For example, the rate of transplant referral (per 100 person-years) was almost 3-fold lower in Northern Ontario (10.0, 95% CI = 8.3, 12.0) compared to Toronto (28.7, 95% CI = 25.7, 32.1). Limitations: We did not examine the reason for differences in access to kidney transplant across RRPs (eg, differences in physician practices and staff-to-patient ratio). Conclusions: Despite operating in a publicly funded health care system, there is substantial variability across the 4 key steps required to receive a kidney transplant. Trial registration: Not registered.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 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".