Why Do Preemptive Kidney Transplant Recipients Have an Allograft Survival Advantage?
Bibliographic record
Abstract
BACKGROUND: Preemptive kidney transplantation is associated with an allograft survival advantage and is promoted in part because of this association. The basis for the allograft survival advantage in preemptive recipients is unclear. Possibilities include a lead time bias due to the earlier transplantation of patients with preserved native kidney function, less rapid loss of kidney function after transplantation, or the longer patient survival of preemptive recipients. METHODS: We compared the glomerular filtration rate (GFR) six months after transplantation and the subsequent rate of loss of kidney function as defined by the annualized change in GFR (mL/min/1.73 m2/year) in 5,966 preemptive and 34,997 non-preemptive recipients. Linear regression methods were applied to serial GFR estimates after transplantation to determine the annualized change in GFR. Multiple regression was used to determine the independent effect of preemptive transplantation upon the annualized change in GFR. RESULTS: The mean GFR six months after transplantation was similar among preemptive (49.5+/-15.7 mL/min/1.73 m2) and non-preemptive (49.2+/-14.7 mL/min/1.73 m2) recipients (P=0.37). In multivariate analysis, preemptive recipients had a slower decline in GFR (0.28 mL/min/year/1.73 m2; 95% confidence interval 0.11, 0.46; P=0.002). However, this difference was of modest clinical significance and would not explain the allograft survival advantage of preemptive transplantation. CONCLUSIONS: Neither the preservation of native kidney function nor differences in the rate of loss of kidney function explain the superior allograft survival of preemptive recipients. By exclusion, the allograft survival advantage associated with preemptive transplantation may be due to the longer survival of preemptive recipients.
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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) | 0.000 | 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".