International Pediatric Multiple Sclerosis Study Group criteria for pediatric multiple sclerosis and immune-mediated central nervous system demyelinating disorders: revisions to the 2007 definitions
Bibliographic record
Abstract
BACKGROUND: There has been tremendous growth in research in pediatric multiple sclerosis (MS) and immune mediated central nervous system demyelinating disorders since operational definitions for these conditions were first proposed in 2007. Further, the International Pediatric Multiple Sclerosis Study Group (IPMSSG), which proposed the criteria, has expanded substantially in membership and in its international scope. OBJECTIVE: The purpose of this review is to revise the 2007 definitions in order to incorporate advances in delineating the clinical and neuroradiologic features of these disorders. METHODS: Through a consensus process, in which input was sought from the 150 members of the Study Group, criteria were drafted, revised and finalized. Final approval was sought through a web survey. RESULTS: Revised criteria are proposed for pediatric acute disseminated encephalomyelitis, pediatric clinically isolated syndrome, pediatric neuromyelitis optica and pediatric MS. These criteria were approved by 93% or more of the 56 Study Group members who responded to the final survey. CONCLUSIONS: These definitions are proposed for clinical and research purposes. Their utility will depend on the outcomes of their application in prospective research.
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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 | 0.024 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".