Pediatric central nervous system inflammatory demyelination: acute disseminated encephalomyelitis, clinically isolated syndromes, neuromyelitis optica, and multiple sclerosis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE OF REVIEW: We review the recent consensus definitions for acute disseminated encephalomyelitis,clinically isolated syndromes, neuromyelitis optica, and multiple sclerosis (MS) in children. We also discuss the importance of clinically defined consistency, the need for biomarker-based patient delineation, the likelihood of subsequent MS diagnosis following acute demyelination, and current therapeutic options. RECENT FINDINGS: Studies of children after a first episode of demyelination have identified disease onset in adolescence, intrathecal oligoclonal bands and optic neuritis as associated with a higher MS risk, whereas prepubertal onset, presence of polyfocal features with encephalopathy, and transverse myelitis have been associated with a lower risk of subsequent MS. The relapsing-remitting form of MS accounts for over 96% of all MS in children. Neuromyelitis optica appears to be a distinct clinical and biological entity for which neuromyelitis optica IgG provides a high degree of specificity. Neuroimaging plays a key role in the diagnosis of acute demyelination, and serial imaging can provide evidence of lesion dissemination in time that can confirm a diagnosis of MS even in the absence of clinical relapse. SUMMARY: Although clinical definitions, increased awareness, and MRI have contributed to the increasing identification of acute demyelination and MS in children, challenges remain in predicting MS risk. Identification of reliable biomarkers or application of more advanced neuroimaging techniques would serve as invaluable tools to distinguish monophasic demyelination from the first attack of MS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it