A Case of Autoimmune Neutropenia That Responded to Rituximab
Bibliographic record
Abstract
Autoimmune neutropenia (AIN) refers to the immune-mediated destruction of neutrophils. It is a rare condition with an estimated prevalence of less than 1 case per 100,000 per year. Typical treatment involves supportive care with granulocyte colony-stimulating factor (G-CSF) and management of secondary infections with antibiotics. Other therapies targeted at the immune system such as steroids, intravenous immunoglobulin (IVIG), and rituximab have not been thoroughly evaluated, but recently rituximab has shown promising results in one case series. We present a 76-year-old man with the diagnosis of antineutrophil antibody-negative AIN and concurrent immune thrombocytopenic purpura (ITP), whose AIN was treated initially with G-CSF which had a short-lived effect, then treated with rituximab which induced a lasting remission. We then review this case in context of other cases described in the literature, given the paucity of available publications.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.003 |
| 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".