Case Report of an ABO-Matched Post-Hematopoietic Stem Cell Transplant-Associated Autoimmune Hemolytic Anemia: A Diagnostic and Therapeutic Challenge
Bibliographic record
Abstract
• Autoimmune hemolytic anemia (AIHA) is a rare complication of ABO-matched hematopoietic stem cell transplantation (HSCT). • Chronic graft versus host disease, unrelated and mismatched donors, and lymphocyte depletion in the peri-HSCT period are risk factors for post-HSCT AIHA. • Post-HSCT AIHA is diagnosed by a positive hemolysis laboratory work-up and positive direct antiglobulin testing with usually a pan-reactive antibody in indirect antiglobulin testing. • Post-HSCT AIHA is generally refractory to treatment but combination therapies with steroids, rituximab, intravenous immunoglobulins, and other immunomodulators represent a promising avenue to maximize the likelihood of transfusion independence. Autoimmune hemolytic anemia (AIHA) is a rare complication of ABO-matched hematopoietic stem cell transplantation (HSCT). Post-HSCT AIHA is diagnosed by a positive hemolysis laboratory work-up and positive direct antiglobulin testing with usually a pan-reactive antibody in indirect antiglobulin testing. In this case report, we describe the diagnosis of post-HSCT AIHA in a 62-year-old male patient and its management with combined immunosuppressive therapy with steroids, rituximab, and intravenous immunoglobulin to achieve transfusion independence and disease remission. Post-HSCT AIHA is generally refractory to treatment but this case highlights the role of combination immunosuppressive therapies to maximize the likelihood of transfusion independence.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".