Low Dose Ciclosporin from the Early Postoperative Period Yields Potent Immunosuppression after Renal Transplantation
Bibliographic record
Abstract
This study sought to determine if low doses of ciclosporin (CS) designed to give fasting serum levels of 50-100 ng/ml achieve effective immunosuppression when used from the early postoperative period after renal transplantation. Ninety-four primary renal transplant recipients were studied. Group 1 patients were treated with CS 100 ng/ml and prednisone (0.15 mg/kg/day). Group 2 patients received CS 50 ng/ml, prednisone (0.15 mg/kg/day) and azathioprine (1 mg/kg/day). These patients were compared to a control group of 26 patients (group 3) maintained on only prednisone and azathioprine. CS-treated patients suffered significantly fewer rejection episodes than control subjects (rejection episodes per patient in first year: group 1: 0.3 +/- SD 0.6; group 2: 0.7 +/- SD 0.7; group 3: 1.3 +/- SD 1.1, p less than 0.005). In addition, a greater number of CS-treated patients were completely free of rejection episodes during the first year posttransplant (group 1: 63%; group 2: 64%; group 3: 19%, p less than 0.005). Patient and graft survival were similar in all groups after 1 year (group 1: 92 and 92% respectively; group 2: 95 and 87% respectively; group 3: 96 and 85% respectively). These data suggest that the dose of CS required for effective immunosuppression in vivo is lower than has been previously thought.
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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 | 0.000 | 0.001 |
| 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) | 0.000 | 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 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".