Myelitis features and outcomes in CNS demyelinating disorders: Comparison between multiple sclerosis, MOGAD, and AQP4-IgG-positive NMOSD
Bibliographic record
Abstract
Inflammatory myelopathies can manifest with a combination of motor, sensory and autonomic dysfunction of variable severity. Depending on the underlying etiology, the episodes of myelitis can recur, often leading to irreversible spinal cord damage and major long-term disability. Three main demyelinating disorders of the central nervous system, namely multiple sclerosis (MS), aquaporin-4-IgG-positive neuromyelitis optica spectrum disorders (AQP4+NMOSD) and myelin oligodendrocyte glycoprotein-IgG associated disease (MOGAD), can induce spinal cord inflammation through different pathogenic mechanisms, resulting in a more or less profound disruption of spinal cord integrity. This ultimately translates into distinctive clinical-MRI features, as well as distinct patterns of disability accrual, with a step-wise worsening of neurological function in MOGAD and AQP4+NMOSD, and progressive disability accrual in MS. Early recognition of the specific etiologies of demyelinating myelitis and initiation of the appropriate treatment is crucial to improve outcome. In this review article we summarize and compare the clinical and imaging features of spinal cord involvement in these three demyelinating disorders, both during the acute phase and over time, and outline the current knowledge on the expected patterns of disability accrual and outcomes. We also discuss the potential implications of these observations for patient management and counseling.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".