Relationship between Mixed Donor–Recipient Chimerism and Disease Recurrence after Hematopoietic Cell Transplantation for Sickle Cell Disease
Bibliographic record
Abstract
Mixed donor chimerism after hematopoietic cell transplantation for sickle cell disease (SCD) can result in resolution of disease symptoms, but symptoms recur when donor chimerism is critically low. The relationship between chimerism, hemoglobin S (HbS) level, and symptomatic disease was correlated retrospectively in 95 patients who had chimerism reports available at day 100 and at 1 and 2 years after transplantation. Recurrent disease was defined as recurrence of vaso-occlusive crises, acute chest syndrome, stroke, and/or HbS levels > 50%. Thirty-five patients maintained full donor chimerism (myeloid or whole blood) through 2 years. Donor chimerism was less than 10% (defined as graft failure) in 13 patients during this period. Mixed chimerism was reported in the remaining 47 patients (range, 10% to 94%). The lowest documented donor chimerism without symptomatic disease was 26%. Of 12 surviving patients with recurrent disease, 2 had recurrence of symptoms before documented graft failure (donor chimerism of 11% and 17%, respectively). Three patients underwent second transplantation for graft failure. None received donor leukocyte infusion to maintain mixed chimerism or prevent graft failure. We conclude stable donor chimerism greater than 25% is associated with resolution of SCD-related symptoms, and HbS levels in transplant recipients should be interpreted in context of the sickle trait status of the donors.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".