Serum MOG-IgG in children meeting multiple sclerosis diagnostic criteria
Bibliographic record
Abstract
BACKGROUND: Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is now recognized as distinct from multiple sclerosis (MS). OBJECTIVE: To evaluate the importance of considering myelin oligodendrocyte glycoprotein (MOG)-immunoglobulin-G (IgG) serology when applying MS diagnostic criteria in children. METHODS: Within a prospective cohort of children meeting MS criteria (median follow-up = 6 years, interquartile range (IQR) = 4-9), we measured MOG-IgG in serial archived serum obtained from presentation, and compared imaging and clinical features between seropositive and seronegative participants. RESULTS: Of 65 children meeting MS criteria (median age = 14.0 years, IQR = 10.9-15.1), 12 (18%) had MOG-IgG at disease onset. Seropositive participants were younger, had brain magnetic resonance imaging (MRI) features atypical for MS, rarely had cerebrospinal fluid (CSF) oligoclonal bands (2/8, 25%), and accumulated fewer T2 lesions over time. On serial samples, 5/12 (42%) were persistently seropositive, 5/12 (42%) became seronegative, and 2/12 (17%) had fluctuating results. All 12 children experienced a disease course different from typical MS. CONCLUSION: While children with MOG-IgG can have clinical, CSF, and MRI features conforming to MS criteria, the presence of MOG-IgG is associated with atypical features and predicts a non-MS disease course. Given MOG-IgG seropositivity can wane over time, testing at first attack is of considerable importance for the diagnosis of MOGAD.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".