Time Dependency of Factors Affecting Renal Allograft Survival
Bibliographic record
Abstract
The function of renal transplants can deteriorate at any time posttransplant, but the risks and mechanisms may differ at different times posttransplant. Survival of 522 consecutive cadaveric renal transplant recipients followed for at least 6 mo were analyzed, with patient death censored. The overall risk factors in univariate analysis were acute rejection requiring antibody therapy (AR), delayed graft function, elevated serum creatinine at 6 mo, high panel-reactive antibodies, and donor age > or =55 yr, with borderline effects of recipient age and female gender. These risks were studied in each of three intervals posttransplantation: < or =6 mo, 6 mo to 5 yr, and >5 yr. Of the 135 graft failures, 53 occurred < or =6 mo, 61 between 6 mo and 5 yr, and 21 beyond 5 yr. By multivariate analysis. the risks for graft failure in interval < or =6 mo were AR (hazard ratio (HR) = 4.86, P < 0.001); delayed graft function (HR = 1.47, P = 0.06): and high panel-reactive antibodies (HR = 2.04, P = 0.0(3). Between 6 mo and 5 yr, the risks for graft loss were AR (HR = 2.87, P < 0.001) and serum creatinine at 6 mo > or =150 micromol/L (HR = 3.69, P < 0.001). Beyond 5 yr the risk factors were donor age > or =55 yr (HR = 5.87, P = 0.002), with a borderline effect of kidneys from female donors (HR = 2.28, P = 0.07). HLA-A, -B, and -DR matching and presensitization had most of their effect through early AR and impaired function. The results indicate that risks for graft loss are time-dependent: early losses correlate with injury and rejection, but late events correlate with donor age and possibly workload.
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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) | 0.001 | 0.001 |
| 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".