Epidemiology, immunopathogenesis and management of pediatric central nervous system inflammatory demyelinating conditions
Bibliographic record
Abstract
PURPOSE OF REVIEW: Pediatric inflammatory demyelinating central nervous system diseases comprise monofocal and potentially monophasic disorders like optic neuritis and transverse myelitis, the multifocal, self-limiting disorder of acute disseminated encephalomyelitis, and multifocal chronic diseases like relapsing neuromyelitis optica and multiple sclerosis. This review discusses characteristics of these disorders with focus on epidemiology and treatment of acute disseminated encephalomyelitis, neuromyelitis optica and multiple sclerosis. RECENT FINDINGS: An international consensus group very recently defined diagnostic criteria for pediatric multiple sclerosis and acute disseminated encephalomyelitis. Immunological studies on pediatric inflammatory demyelinating disorders revealed possible disease-related humoral and T-cellular pathomechanisms. The recently identified biomarker for neuromyelitis optica, aquaporin-4-autoantibody, was detected in children with relapsing neuromyelitis optica with a similar frequency as in adult neuromyelitis optica patients. Clinically relevant, there is growing evidence that disease-modifying treatments are well tolerated and effective in the pediatric age group also. SUMMARY: Recent studies on pediatric inflammatory demyelinating central nervous system diseases have contributed to current awareness that these disorders are not restricted to the adult age group, and that some of them carry an unfavorable long-term prognosis. Growing knowledge will hopefully enable more timely diagnoses and more specifically tailored therapies in the near future, with the goal of improving outcomes in this young patient group.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".