The Stability of the Glomerular Filtration Rate after Renal Transplantation Is Improving
Bibliographic record
Abstract
The 6-mo function and the stability of function posttransplantation in 429 cadaver renal transplants was investigated from 1990 to 2000. The 6-mo creatinine clearance (CrCl) and the rate of change of CrCl beyond 6 mo posttransplantation were calculated. The mean 6-mo CrCl was 64.6 +/- 1.1 ml/min and was stable between 1990 and 2000. The net slope of CrCl was -1.4 +/- 0.5 ml/min per yr. The slope has improved in recent years, such that the mean slopes in the period after 1997 are actually positive (+3.5 ml/min per yr). The slope of CrCl beyond 6 mo was not related to the actual value of the 6 mo CrCl, i.e., there was no accelerated loss of function at low CrCl levels. The 6-mo CrCl was independently determined by donor factors (age, gender), recipient factors (age, gender), and immune factors (rejection episodes, regraft status). The slope of the CrCl correlated independently with the transplant year, recipient gender, rejection episodes, diastolic BP, and the choice of immunosuppressive drugs. Cytomegalovirus infection and mismatch status and lipid levels and treatment were not independently associated with slope or 6-mo CrCl. Thus, the most striking change in the course of renal transplants over the past decade is the new stability of function, correlating with reduced rejection and probably due at least in part to the new immunosuppressive agents. Despite continued calcineurin inhibitor use, late improvement in function now occurs in many cadaver kidney transplants, suggesting a previously unappreciated capacity for functional adaptation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".