Pediatric anti-myelin oligodendrocyte glycoprotein syndrome: case series of a newly recognized central nervous system inflammatory disease
Bibliographic record
Abstract
Pediatric acquired demyelinating syndromes have overlapping clinical and imaging features, but management and prognosis vary. We describe four children between the ages of 3 and 10 presenting with inflammatory brain disease - one with polyfocal neurological symptoms, one with severe bilateral optic neuritis and two with transverse myelitis, all without encephalopathy. All brain MRIs had extensive involvement of both deep grey and subcortical white matter. Three patients had longitudinally extensive spinal cord lesions. Clinical and radiological findings did not meet criteria for multiple sclerosis, acute disseminated encephalomyelitis, or neuromyelitis optica (NMO). NMO IgG testing was negative. All patients had resolution of clinical and imaging findings after treatment with steroids and IVIg. We found, elevated levels of anti-myelin oligodendrocyte glycoprotein antibodies in all four patients. Three of the children receive monthly IVIg infusions. Two of the patients relapsed once within 18 months of their initial attack and have since remained relapse free for 32 months and 43 months, respectively. The third patient (transverse myelitis) has not had any relapses since her initial attack 15 months ago. It appears that children with this syndrome may have more favourable outcomes when compared to other CNS relapsing inflammatory conditions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".