Refractory Primary Central Nervous System Vasculitis of Childhood: Successful Treatment with Infliximab
Bibliographic record
Abstract
To the Editor: Childhood primary angiitis of the central nervous system (cPACNS) is an increasingly recognized inflammatory brain disease causing devastating brain injury in previously healthy children1. Early recognition and initiation of treatment may reverse the severe deficits caused by inflammation and lead to complete neurological recovery. cPACNS has a broad clinical spectrum including acute ischemic stroke, intractable seizures, and severe cognitive decline2. cPACNS is classified into angiography-positive vasculitis and angiography-negative small-vessel vasculitis (SV-cPACNS)2. We reported the efficacy and safety of a treatment protocol for SV-cPACNS3. This immunosuppressive regimen led to complete neurological recovery in the majority of children3. There is limited knowledge of the approach to children who fail standard therapy. Tumor necrosis factor (TNF) inhibition has been considered in the treatment of refractory systemic vasculitis4. In addition, histological studies of SV-cPACNS brain biopsies demonstrated primary lymphocytic vessel wall infiltrates5. We describe 2 children with refractory SV-cPACNS who failed standard treatment with cyclophosphamide and high-dose corticosteroids. Treatment with anti-TNF therapy with infliximab (IFX) controlled disease activity and resolved neurologic symptoms. In Case 1, a 7-year-old previously healthy girl presented with fever and headaches. She was admitted to hospital and developed a generalized tonic-clonic seizure. … Address correspondence to Dr. S. Benseler, Division of Rheumatology, Department of Pediatrics, The Hospital for Sick Children, 555 University Ave., Toronto, Ontario M5G 1X8, Canada. E-mail: susanne.benseler{at}sickkids.ca
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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".