A254 IGA-MEDIATED WARM AUTOIMMUNE HEMOLYTIC ANEMIA IN A PATIENT WITH CROHN’S DISEASE ON VEDOLIZUMAB
Bibliographic record
Abstract
Abstract Background Iron deficiency anemia and anemia of chronic disease are relatively common manifestations of Crohn’s disease. Autoimmune hemolytic anemia, however, is quite rare with few reported cases. Aims To present a rare case of IgA-mediated warm autoimmune hemolytic anemia in Crohn’s Disease. Methods A chart review and literature search were performed in preparation of this case report. Results A 21-year-old male with a recent diagnosis of Crohn’s disease on Vedolizumab presents to infusion clinic with generalized weakness, coke-colored urine and weight loss. Physical examination was remarkable for tachycardia and jaundice. Laboratory investigations revealed profound anemia with IgA-mediated DAT positivity. The patient remained admitted in hospital for a prolonged period. Bone marrow biopsy, CT imaging and infectious workup were negative. Vedolizumab was held and treatment with both high-dose corticosteroids and rituximab was required. Eventually, the anemia would stabilize and Vedolizumab was safely resumed as an outpatient. Conclusions Here we report a both rare and challenging case of IgA-mediated DAT positive autoimmune hemolytic anemia in a patient with Crohn’s disease who was successfully treated with corticosteroids and rituxumab. Funding Agencies None
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".