Case Report on the Rare Diagnosis of Schnitzler’s Syndrome
Bibliographic record
Abstract
A 66-year-old male presented to internal medicine clinic with a 2-year history of an urticarial-like rash with fatigue, decreased appetite, chills, and 45 pounds of weight loss. He had a history of ulcerative colitis diagnosed in 1972, but has not required medication to control his disease for many years. His clinical exam revealed an erythematous blanchable urticarial rash on his trunk and extremities, but was otherwise unremarkable. Investigations revealed leukocytosis of 21.7 × 10 e9/L with neutrophilia 19.4 × 10 e9/L. Microcytic anemia was present with a hemoglobin of 119 g/L, MCV 75.1 fL, TSAT 6%, iron 2.6 umol/L, TIBC 44.9 umol/L, and ferritin 1082 ug/L. Thrombocytosis was present with platelets 523 × 10 e9/L. Serum protein electrophoresis revealed an M-spike of 4.5 g/L in the gamma globulin region, with immunofixation revealing it to be a mono- clonal IgM-type kappa. Given the history of ulcerative colitis and microcytic anemia, the patient underwent a colonoscopy and EGD which were both normal. Skin biopsy performed by dermatology demonstrated urticarial neutrophilic dermatosis. Given the constellation of findings, in consultation with rheumatology and dermatology, the diagnosis of Schnitzler’s syndrome was made as per the Strasbourg criteria. The patient has had improvement of his clinical symptoms on colchicine and is pending provincial approval for use of the IL-1 receptor antagonist Anakinra. Due to the association of the syndrome with lymphoproliferative disorders, the patient underwent a bone marrow biopsy and lymph node biopsy, which demonstrated possible low- grade lymphoma, and the patient is actively followed by hematology for the same.
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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) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".