Impact of Using Alternative Graft Function Endpoints: A Secondary Analysis of a Kidney Transplant Trial
Bibliographic record
Abstract
BACKGROUND: Nephrology trials assessing the impact of interventions on "standard" outcomes, such as doubling of creatinine, end-stage renal disease (ESRD), and/or death, are difficult to conduct given the time required for endpoints to accrue. The objective of this study was to determine if using lesser declines in kidney function would alter the interpretation of a previous randomized controlled trial. METHODS: This study was a secondary analysis of a kidney transplant trial comparing the use of a 40% or greater, 30% or greater, or 20% or greater decline in estimated glomerular filtration rate (eGFR) as a substitute for doubling of serum creatinine. Declines in eGFR were determined relative to baseline. This trial enrolled 212 kidney transplant patients with proteinuria and assessed the clinical impact of ramipril versus placebo on a primary outcome of doubling of serum creatinine, ESRD, or death. In this analysis, the declines in eGFR replaced doubling of creatinine in the composite endpoint. RESULTS: Mean trial follow-up was 41 months. A time-to-event composite of death, ESRD, or a 40% or greater, 30% or greater, or 20% or greater eGFR decline occurred in 45 (26 placebo vs 19 ramipril), 68 (35 vs 33), and 99 (50 vs 49) patients, respectively. Substituting these eGFR declines for doubling of serum creatinine resulted in an increase of 12, 35, and 66 endpoints compared with the original trial. In all 3 eGFR declines, ramipril treatment was not associated with any statistically significant differences despite the increase in events. CONCLUSIONS: Substituting doubling of serum creatinine for lesser eGFR percentage decline thresholds did not alter trial interpretation but did increase the number of events.
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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 | 0.026 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.009 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".