Devic's Neuromyelitis Optica Treated with Intravenous Gamma Globulin (IVIG)
Bibliographic record
Abstract
BACKGROUND: Devic's syndrome is a demyelinating disease of the spinal cord and optic nerves. It tends to have a poor prognosis, probably due to the occurrence of necrosis within lesions. There is no proven effective treatment although relapses are commonly treated with corticosteroids and people with recurrent attacks may be managed with chronic immune suppressing treatments. Intravenous gamma globulin (IVIG) and plasma exchange are reasonable treatment options because Devic's syndrome is believed to be antibody mediated. We report two patients of Devic's syndrome that stabilized following initiation of monthly IVIG. PATIENT 1: A 42-year-old woman with a 23 year history of Devic's syndrome continued to have frequent attacks of optic neuritis unresponsive to daily corticosteroids and azathioprine. Since initiation of monthly IVIG 5 1/2 years ago she has had no further definite attacks. She has also noted minimal improvement in color perception. PATIENT 2: A 58-year-old woman with a three year history of Devic's syndrome experienced five attacks during the first 16 months of disease. Monthly IVIG was associated with complete cessation of relapses and significantly improved neurological status over one year of treatment. CONCLUSIONS: Because active Devic's disease often results in severe, permanent neurological impairment, preventive intervention should be considered. These cases suggest that IVIG may be effective in preventing attacks and possibly in enhancing neurological recovery. Randomized controlled trials will be needed to confirm this and to determine optimal dosing and treatment duration.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".