Progression of Kidney Disease in Kidney Transplant Recipients With a Failing Graft: A Matched Cohort Study
Bibliographic record
Abstract
Background:Few studies have assessed outcomes in transplant recipients with failing grafts as most studies have focused on outcomes after graft loss.Objective:To determine whether renal function declines faster in kidney transplant recipients with a failing graft than in people with chronic kidney disease of their native kidneys.Design:Retrospective cohort study.Setting:Alberta, Canada (2002-2019).Patients:We identified kidney transplant recipients with a failing graft (2 estimated glomerular filtration rate [eGFR] measurements 15-30 mL/min/1.73 m<sup>2</sup> ≥90 days apart).Measurements:We compared the change in eGFR over time (eGFR with 95% confidence limits, <sub>LCL</sub>eGFR<sub>UCL</sub>) and the competing risks of kidney failure and death (cause-specific hazard ratios [HRs], <sub>LCL</sub>HR<sub>UCL</sub>).Methods:Recipients (n = 575) were compared with propensity-score-matched, nontransplant controls (n = 575) with a similar degree of kidney dysfunction.Results:The median potential follow-up time was 7.8 years (interquartile range, 3.6-12.1). The hazards for kidney failure (HR<sub>1.10</sub>1.33<sub>1.60</sub>) and death (HR<sub>1.21</sub>1.59<sub>2.07</sub>) were significantly higher for recipients, while the eGFR decline over time was similar (recipients vs controls: <sub>–2.60</sub>–2.27<sub>–1.94</sub> vs <sub>–2.52</sub>–2.21<sub>–1.90</sub> mL/min/1.73 m<sup>2</sup> per year). The rate of eGFR decline was associated with kidney failure but not death.Limitations:This was a retrospective, observational study, and there is a risk of bias due to residual confounding.Conclusions:Although eGFR declines at a similar rate in transplant recipients as in nontransplant controls, recipients have a higher risk of kidney failure and death. Studies are needed to identify preventive measures to improve outcomes in transplant recipients with a failing graft.
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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) | 0.000 | 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".