Benefit of Neoral C2 Monitoring in De Novo Cardiac Transplant Recipients Receiving Basiliximab Induction
Bibliographic record
Abstract
BACKGROUND: For cyclosporine (CsA), 2-hr postdose level (C2) is the best single time point predictor of the area under the curve and a critical measure for effective dosing. The therapeutic CsA microemulsion (Neoral) C2 range in de novo heart transplant patients remains to be determined. PURPOSE: The purpose of this study was to determine the efficacy of CsA C2 monitoring in de novo heart transplant patients receiving basiliximab induction. METHODS: This prospective, multicenter, randomized study enrolled 87 adult heart transplant recipients stratified according to 4 to 6 hrs posttransplant serum creatinine less than or equal to 170 micromol/L (cohort A) or more than 170 micromol/L (cohort B). Patients in cohort A were randomized into three C2 ranges (A1: "high" n=25, 1600-1800 ng/mL; A2: "intermediate" n=27, 1400-1600 ng/mL; and A3: "low" n=24, 1200-1400 ng/mL). Patients in cohort B were randomized into intermediate (n=5) and low C2 (n=6). Target ranges were progressively lowered after 1 month. Immunosuppression included basiliximab, Neoral, mycophenolate mofetil, and corticosteroids. Endpoints were acute rejection and renal function. RESULTS: The incidence of acute rejection at 12 months was 44% in group A1, 41% in group A2, 33% in group A3, and 27% in cohort B. Pretransplant and 12-month creatinine clearance (mL/min) were group A1, 72+/-25 and 64+/-24; group A2, 81+/-32 and 68+/-25; group A3, 91+/-28 and 86+/-26; and cohort B, 62+/-28 and 79+/-37. CONCLUSION: These results suggest that C2 monitoring is safe in de novo heart transplant patients. A low Neoral C2 range in combination with basiliximab induction resulted in preserved renal function without increased risk of acute rejection.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".