2010 McDonald criteria for diagnosing pediatric multiple sclerosis
Bibliographic record
Abstract
OBJECTIVE: The diagnosis of multiple sclerosis (MS) rests on confirmation of central nervous system inflammatory disease that is disseminated in space and time, as evidenced clinically or by magnetic resonance imaging (MRI). The 2010 McDonald criteria simplified MRI requirements, and newly proposed that the criteria are also suitable for the diagnosis of pediatric MS. METHODS: In a national prospective incident cohort study of children with acute demyelination observed for a minimum of 24 months, baseline and serial clinical and MRI examinations were used to retrospectively evaluate the 2010 and 2005 McDonald criteria using clinically relapsing disease as the gold standard. RESULTS: Of 212 eligible participants, 34 experienced 2 or more clinical attacks, 58 met the 2010 criteria, and 42 met 2005 McDonald criteria. The 2010 criteria demonstrated high sensitivity (100%), specificity (86%), positive predictive value (76%), and negative predictive value (100%) for children older than 11 years with non-acute disseminated encephalomyelitis (ADEM) presentations, as did the 2005 McDonald criteria. In younger children with a non-ADEM presentation, PPV of the 2010 criteria was only 55%. None of the 50 children with ADEM met clinical criteria for MS, but 10 met 2010 and 4 met 2005 criteria. INTERPRETATION: Both 2005 and 2010 McDonald criteria identify children with relapsing-remitting MS, although caution is suggested when applying these criteria in younger children. The 2010 McDonald criteria are simple and enable an early diagnosis of MS, but are not suited for application in the context of ADEM-like presentations.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".