Effect of Cyclosporin Weaning on Glomerular Filtration Rate in Renal Transplantation
Bibliographic record
Abstract
The objective of this study was to determine the effect of weaning cyclosporin on glomerular filtration rate in 55 renal transplant patients from the Renal Transplant Unit at the Royal Victoria Hospital. Men or women, older than 20 years of age, who received cadaveric or living-related renal transplant and who were treated with the complete cyclosporin protocol, were included. Weaning of cyclosporin was started 15 days after the prednisone dose was reduced to 15 mg/day and this weaning process was completed at day 105 posttransplant. The daily cyclosporin dose was decreased by 25 mg once every 2 weeks, and completely withdrawn after treatment when 50 mg/day was tolerated for 2 weeks. The duration of the weaning process varied because of fixed dose reduction. Renal graft function was assessed by plasma creatinine concentrations. We used the time point of cyclosporin discontinuation as time zero. Serum creatinine decreased over the time from 150 +/- 61 mmol/l at time zero to 100 +/- 18 mmol/l in the last determination, while GFR had a significant increment from 66 +/- 18 to 77 +/- 20. A total of 4 rejection episodes were observed 6 months after cyclosporin discontinuation. There were no graft failures and deaths. To determine predictors of improvement, we carried out multiple regression analysis and we found that prophylactic antilymphocyte globulin and the onset of graft function after transplantation were predictors.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".