The clinical features, MRI findings, and outcome of optic neuritis in children
Bibliographic record
Abstract
BACKGROUND: Optic neuritis (ON) in childhood is thought to be more likely bilateral and less likely to lead to multiple sclerosis (MS) vs ON in adults. METHODS: The authors evaluated clinical features, maximal visual deficit and recovery, visual evoked potentials (VEPs), neuroimaging, and outcome in a cohort of children with ON. RESULTS: Records of 36 children (female/male ratio 1.6), ages 2.2 to 17.8 (mean 12.2) years, were reviewed. ON was unilateral in 58% and bilateral in 42%. Maximal visual deficit was severe in 69%, but full recovery occurred in 39 of 47 affected eyes (83%). VEPs were abnormal in 88%. Neurologic abnormalities in addition to those associated with ON were documented in 13 children. Neuroimaging studies of the optic nerve were abnormal in 55%. Brain MRI in 35 children demonstrated white matter lesions separate from the optic nerves in 54%. Follow-up is 2.4 years (0.3 to 8.3 years). To date, 13 children (36%) have been diagnosed with MS and 1 has Devic disease. Bilateral ON was more likely to be associated with MS outcome (p = 0.03). All 13 children with MS had white matter lesions on brain MRI. None of the children with a normal brain MRI have developed MS to date. CONCLUSIONS: Contrary to expectations, optic neuritis (ON) in childhood was more likely to be unilateral, multiple sclerosis (MS) risk was high (36% at 2 years), and bilateral rather than unilateral ON was associated with a greater likelihood of MS. Clinical findings extrinsic to the visual system on baseline examination (p < 0.0001) and MRI evidence of white matter lesions outside the optic nerves (p < 0.0001) were strongly correlated with MS outcome.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".