Factors Associated with Improvement in Deceased Donor Renal Allograft Function in the 1990s
Bibliographic record
Abstract
The decade of the 1990s saw an improvement in cadaveric renal graft function and dramatic reduction in the acute rejection (AR) rate. The purpose of this study was to determine whether the reduction in rejection rate was the primary cause of the improvement in graft function seen and whether this improved long-term graft survival. All adult patients who received a cadaver renal transplant between 1991 and 2000 and had graft survival of at least 6 mo and complete data for creatinine at 6 mo, HLA mismatch, delayed graft function, and acute rejection (AR) were identified in the United Network for Organ Sharing database. A total of 40,164 cases that met the inclusion criteria were identified. The mean Modification of Diet in Renal Disease GFR at 6 mo improved from 49.94 ml/min per 1.73 m2 in 1991 to 54.59 ml/min per 1.73 m2 in 2000 (P < 0.001). The improvement in GFR was not gradual but occurred over a 4-yr period between 1994 and 1997, coinciding with the introduction of new immunosuppressive agents mycophenolate mofetil and tacrolimus into maintenance immunosuppression regimens. The improvement was seen in all subgroups of patients, even patients without clinical AR or delayed graft function. The magnitude of improvement in patients without clinical AR was similar to that seen in patients with AR. The drop in clinical AR rate accounted for a minority of the improvement in graft function in the 1990s. Other factors, such as reduced drug toxicity and improved control of subclinical rejection, seem to account for the majority of the improvement. This improvement in graft function at 6 mo did not translate into improved long-term graft survival, however.
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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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".