Incidence, characterization, and impact of newly detected donor-specific anti-HLA antibody in the first year after pediatric heart transplantation: A report from the CTOTC-04 study
Bibliographic record
Abstract
Data on the clinical importance of newly detected donor-specific anti-HLA antibodies (ndDSAs) after pediatric heart transplantation are lacking despite mounting evidence of the detrimental effect of de novo DSAs in solid organ transplantation. We prospectively tested 237 pediatric heart transplant recipients for ndDSAs in the first year posttransplantation to determine their incidence, pattern, and clinical impact. One-third of patients developed ndDSAs; when present, these were mostly detected within the first 6 weeks after transplantation, suggesting that memory responses may predominate over true de novo DSA production in this population. In the absence of preexisting DSAs, patients with ndDSAs had significantly more acute cellular rejection but not antibody-mediated rejection, and there was no impact on graft and patient survival in the first year posttransplantation. Risk factors for ndDSAs included common sensitizing events. Given the early detection of the antibody response, memory responses may be more important in the first year after pediatric heart transplantation and patients with a history of a sensitizing event may be at risk even with a negative pretransplantation antibody screen. The impact on late graft and patient outcomes of first-year ndDSAs is being assessed in an extended cohort of patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".