Daratumumab in Heart Transplantation: A Pilot Study in a Pediatric and Young Adult Series
Bibliographic record
Abstract
BACKGROUND: Anti-HLA sensitization is associated with antibody-mediated rejection and represents a major challenge to successful heart transplantation. Daratumumab, an IgGκ monoclonal antibody targeting the CD38 receptor on plasma cells, was initially developed for the treatment of multiple myeloma. In transplantation, it may help reduce antibody production by inducing plasma cell apoptosis. Its use in heart transplantation has been limited, particularly in pediatric patients, with only two cases reported in the literature. METHODS: Since 2020, four heart transplant recipients at CHU Sainte-Justine developed donor-specific antibodies (DSAs) and were treated with daratumumab intravenously (16 mg/kg once a week for a minimum of 6 weeks) for desensitization prior to heart transplantation or for the treatment of antibody-mediated rejection. Their medical records were thoroughly analyzed (e.g., DSA levels, biopsy results) to assess the efficacy and safety of daratumumab treatment in four individual case studies. RESULTS: Three patients received daratumumab for antibody-mediated rejection, and one received it as part of a desensitization protocol prior to heart transplantation. DSAs became undetectable in three of the patients. Despite this clearance, one died 18 months after treatment from coronary artery disease while awaiting a second transplant. In the fourth patient, a young adult with both cellular and antibody-mediated rejection, treatment was ineffective despite two cycles. No major side effects were reported during or after daratumumab treatment. CONCLUSION: In all treated patients, Daratumumab was well tolerated, with no major adverse effects except for secondary hypogammaglobulinemia. It may play a key role in managing acute antibody-mediated rejection and desensitizing highly sensitized pediatric transplant recipients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 teacher head, 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".