Antibodies to MOG and AQP4 in children with neuromyelitis optica and limited forms of the disease
Bibliographic record
Abstract
OBJECTIVE: To determine the frequency and clinical-radiological associations of antibodies to myelin oligodendrocyte glycoprotein (MOG) and aquaporin-4 (AQP4) in children presenting with neuromyelitis optica (NMO) and limited forms. METHODS: Children with a first event of NMO, recurrent (RON), bilateral ON (BON), longitudinally extensive transverse myelitis (LETM) or brainstem syndrome (BS) with a clinical follow-up of more than 12 months were enrolled. Serum samples were tested for MOG- and AQP4-antibodies using live cell-based assays. RESULTS: 45 children with NMO (n=12), LETM (n=14), BON (n=6), RON (n=12) and BS (n=1) were included. 25/45 (56%) children had MOG-antibodies at initial presentation (7 NMO, 4 BON, 8 ON, 6 LETM). 5/45 (11%) children showed AQP4-antibodies (3 NMO, 1 LETM, 1 BS) and 15/45 (33%) were seronegative for both antibodies (2 NMO, 2 BON, 4 RON, 7 LETM). No differences were found in the age at presentation, sex ratio, frequency of oligoclonal bands or median EDSS at last follow-up between the three groups. Children with MOG-antibodies more frequently (1) had a monophasic course (p=0.018) after one year, (2) presented with simultaneous ON and LETM (p=0.004) and (3) were less likely to receive immunosuppressive therapies (p=0.0002). MRI in MOG-antibody positive patients (4) less frequently demonstrated periependymal lesions (p=0.001), (5) more often were unspecific (p=0.004) and (6) resolved more frequently (p=0.016). CONCLUSIONS: 67% of all children presenting with NMO or limited forms tested positive for MOG- or AQP4-antibodies. MOG-antibody positivity was associated with distinct features. We therefore recommend to measure both antibodies in children with demyelinating syndromes.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 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".