Diagnosis and treatment of pediatric acquired aplastic anemia (AAA): An initial survey of the North American Pediatric Aplastic Anemia Consortium (NAPAAC)
Bibliographic record
Abstract
BACKGROUND: Randomized clinical trials in pediatric aplastic anemia (AA) are rare and data to guide standards of care are scarce. PROCEDURE: Eighteen pediatric institutions formed the North American Pediatric Aplastic Anemia Consortium to foster collaborative studies in AA. The initial goal of NAPAAC was to survey the diagnostic studies and therapies utilized in AA. RESULTS: Our survey indicates considerable variability among institutions in the diagnosis and treatment of AA. There were areas of general consensus, including the need for a bone marrow evaluation, cytogenetic and specific fluorescent in situ hybridization assays to establish diagnosis and exclude genetic etiologies with many institutions requiring results prior to initiation of immunosuppressive therapy (IST); uniform referral for hematopoietic stem cell transplantation as first line therapy if an HLA-identical sibling is identified; the use of first-line IST containing horse anti-thymocyte globulin and cyclosporine A (CSA) if an HLA-identical sibling donor is not identified; supportive care measures; and slow taper of CSA after response. Areas of controversy included the need for telomere length results prior to IST, the time after IST initiation defining a treatment failure; use of hematopoietic growth factors; the preferred rescue therapy after failure of IST; the use of specific hemoglobin and platelet levels as triggers for transfusion support; the use of prophylactic antibiotics; and follow-up monitoring after completion of treatment. CONCLUSIONS: These initial survey results reflect heterogeneity in diagnosis and care amongst pediatric centers and emphasize the need to develop evidence-based diagnosis and treatment approaches in this rare disease.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".