Early experience with two‐dose daclizumab in the prevention of acute rejection in cardiac transplantation
Bibliographic record
Abstract
BACKGROUND: Daclizumab is a human monoclonal antibody that binds to the interleukin-2 receptor. It has been used as induction therapy in heart transplantation with repeated administrations over several weeks. At our institution, we use a two-dose regimen of daclizumab based on its extended half-life. We sought to determine the incidence of acute rejection with 2-dose daclizumab in cardiac transplantation. METHODS: Eighteen consecutive heart transplants performed at a single center were analyzed retrospectively. Patients received daclizumab (2 mg/kg) within 8 h of cardiac transplantation and a second dose (1 mg/kg) 2 wk thereafter. Maintenance immunosupression included mycophenolate mofetil, prednisone and either cyclosporine or tacrolimus, based on side-effect profile. The endpoint was the incidence of acute rejection as defined by a histologic grade >2 according to the classification of the International Society of Heart and Lung Transplantation. RESULTS: Four patients had acute rejections (all were 3A) during the first 3 months post-transplantation. All four patients had rejection at the first biopsy and only two had rejection thereafter. None of the rejections were hemodynamically significant and no patients were hospitalized. All except one rejection was seen in the context of low 2-h cyclosporine levels. The two-dose regimen was easier to administer on an outpatient basis and resulted in lower cost. CONCLUSIONS: This preliminary report suggests that induction therapy with a two-dose regimen of daclizumab appears to be safe and well tolerated in patients undergoing cardiac transplantation.
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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 | 0.003 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".