Long-Term Deterioration of Kidney Allograft Function
Bibliographic record
Abstract
Although long-term survival after kidney transplantation is critically dependent on maintaining stable allograft function, few studies have examined renal allograft function over time. Using pooled data from 10 278 consecutive transplants at five centers, we calculated slopes of estimated glomerular filtration rates (eGFR) measured after 1, 6 and 12 months in 9515, 8861 and 7359 patients surviving > or =1, > or =6 and > or =12 months, respectively. Slopes of eGFR progressively diminished for patients transplanted during 1984-1989, 1990-1993, 1994-1998 and 1999-2002 (analysis of variance p < 0.0001 and p = 0.1245 for slopes measured after 1 and 6 months, respectively). Slopes measured after 12 months were less in the most recent era: -2.2 +/- 7.2 mL/min/1.73 m(2)/year, -2.3 +/- 6.6 mL/min/1.73 m(2)/year, -2.4 +/- 7.4 mL/min/1.73 m(2)/year and -1.4 +/- 10.9 mL/min/1.73 m(2)/year, respectively, p = 0.0058. Slopes measured after 1, 6 and 12 months each were less for transplantations during 1999-2002, after adjusting for multiple transplantation characteristics (p < 0.0001). Similarly, in Cox proportional hazards analysis, the risk (95% CI) for a 25% reduction in eGFR was 0.92 (0.85-1.01), p = 0.0736 during 1990-1994; 0.94 (0.82-1.08), p = 0.4111 during 1995-1998 and 0.78 (0.64-0.95), p = 0.0110 during 1999-2002 (compared to 1984-1989). We conclude that the rate of decline in allograft function after kidney transplantation has improved, suggesting that stable, long-term function may be achievable.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".