Use of assessment for neuropathic pain in MOGAD
Bibliographic record
Abstract
Myelin oligodendrocyte glycoprotein antibody-associated disorders (MOGAD) is a central inflammatory autoimmune disease primarily characterized by demyelination of the myelin oligodendrocyte glycoprotein and neuronal damage caused by inflammatory cell infiltration. While many studies have reported pain in adult patients with MOGAD, few have reported pain in pediatric patients. An 8-year-old girl developed repeated focal to bilateral tonic-clonic seizures preceded by episodes of falling. Based on the seizures, electroencephalographic and brain MRI findings, and positive anti-MOG antibodies in the blood and cerebrospinal fluid, she was diagnosed with unilateral cortical fluid-attenuated inversion recovery (FLAIR)-hyperintense lesions in anti-MOG-associated encephalitis with seizures (FLAMES). Although the contrast-enhanced spinal MRI showed no abnormalities, she exhibited Lhermitte's sign and neuropathic pain, implying myelitis as a complication. Neuropathic pain was retrospectively assessed using two questionnaires (PainDETECT and Short-Form McGill Pain Questionnaire-2). We report a case of unilateral cortical encephalitis with suspected myelitis on the MOGAD spectrum. For the assessment of neuropathic pain, the modified questionnaires enabled the quantitative and qualitative evaluation of pediatric MOGAD-related pain.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".