Consensus definitions proposed for pediatric multiple sclerosis and related disorders
Bibliographic record
Abstract
BACKGROUND: The CNS inflammatory demyelinating disorders of childhood include both self-limited and lifelong conditions, which can be indistinguishable at the time of initial presentation. Clinical, biologic, and radiographic delineation of the various monophasic and chronic childhood demyelinating disorders requires an operational classification system to facilitate prospective research studies. METHODS: The National Multiple Sclerosis Society (NMSS) organized an International Pediatric MS Study Group (Study Group) composed of adult and pediatric neurologists and experts in genetics, epidemiology, neuropsychology, nursing, and immunology. The group met several times to develop consensus definitions regarding the major CNS inflammatory demyelinating disorders of children and adolescents. RESULTS: Clinical definitions are proposed for pediatric multiple sclerosis (MS), acute disseminated encephalomyelitis (ADEM), recurrent ADEM, multiphasic ADEM, neuromyelitis optica, and clinically isolated syndrome. These definitions are considered operational and need to be tested in future research and modified accordingly. CONCLUSION: CNS inflammatory demyelinating disorders presenting in children and adolescents can be defined and distinguished. However, prospective research is necessary to determine the validity and utility of the proposed diagnostic categories.
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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 | 0.022 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".