Impact of iron overload on poor graft function after allo-HSCT in a patient with transfusion-dependent low-risk MDS: A case report and literature review
Bibliographic record
Abstract
RATIONALE: Poor graft function (PGF) occurs in 5% to 27% of allogeneic hematopoietic stem cell transplantation (allo-HSCT) and is associated with high life-threatening complications. The etiology of PGF is complex and multifactorial, and iron overload (IOL) is considered as a predictive factor. PATIENT CONCERN: A 45-years-old woman who was diagnosed as low-risk myelodysplastic syndrome in 2012 has been transfusion dependent and developed severe IOL. DIAGNOSES: Due to transfusion dependency and also ineffective erythropoiesis, this patient was diagnosed as IOL and developed PGF after allo-HSCT. INTERVENTIONS: Deferasirox (20mg/kg/d) was administered regularly after allo-HSCT for 2 years. OUTCOMES: Hematopoiesis was gradually recovered during iron chelation therapy treatment after allo-HSCT and PGF was reverted. LESSONS: IOL, as a prognostic factor for PGF, is a common problem in Transfusion dependent myelodysplastic syndrome patients undergoing HSCT. IOL issues should be considered at the time of diagnosis and throughout the treatment course for patients who are potential candidates for HSCT.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| 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) | 0.002 | 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".