Study rationale, design, and pretransplantation alloantibody status: A first report of Clinical Trials in Organ Transplantation in Children-04 (CTOTC-04) in pediatric heart transplantation
Bibliographic record
Abstract
Anti-HLA donor-specific antibodies are associated with worse outcomes after organ transplantation. Among sensitized pediatric heart candidates, requirement for negative donor-specific cytotoxicity crossmatch increases wait times and mortality. However, transplantation with positive crossmatch may increase posttransplantation morbidity and mortality. We address this clinical challenge in a prospective, multicenter, observational cohort study of children listed for heart transplantation (Clinical Trials in Organ Transplantation in Children-04 [CTOTC-04]). Outcomes were compared among sensitized recipients who underwent transplantation with positive crossmatch, nonsensitized recipients, and sensitized recipients without positive crossmatch. Positive crossmatch recipients received antibody removal and augmented immunosuppression, while other recipients received standard immunosuppression with corticosteroid avoidance. This first CTOTC-04 report summarizes study rationale and design and relates pretransplantation sensitization status using solid-phase technology. Risk factors for sensitization were explored. Of 317 screened patients, 290 were enrolled and 240 underwent transplantation. Core laboratory evaluation demonstrated that more than half of patients were anti-HLA sensitized. Greater than 80% of sensitized patients had class I (with or without class II) HLA antibodies, and one-third of sensitized patients had at least 1 HLA antibody with median fluorescence intensity of ≥8000. Logistic regression models demonstrated male sex, weight, congenital heart disease history, prior allograft, and ventricular assist device are independent risk factors for sensitization.
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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 | 0.059 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".