New Acute Severity Scale for Neuromyelitis Optica Relapses (P5.249)
Bibliographic record
Abstract
OBJECTIVE: To develop and validate an objective scale that represents degree of neurological dysfunction from an acute relapse of neuromyelitis optica. BACKGROUND: Neuromyelitis optica (NMO) is an autoimmune disease of the central nervous system (CNS) distinct from multiple sclerosis (MS). It is characterized by recurrent episodes of optic neuritis (ON) and longitudinally extensive transverse myelitis (LETM), which commonly lead to incremental event-related disability. Disability generally has been rated using the Expanded Disability Severity Scale (EDSS) developed for MS trials. However, the EDSS is insensitive to changes in visual acuity and limited in patients who cannot walk. DESIGN/METHODS: We designed a 34-point acute relapse severity scale specific to NMO, named the NMO Severity Scale (NMOSS) focusing on areas most significantly affected including 1) Visual Acuity, 2) Visual Fields, 3) Motor, 4) Sensory, 5) Bowel & Bladder, and 6) Brainstem Functions. We asked 17 international experts in NMO to review records from 20 acute NMO admissions to the Johns Hopkins Hospital to evaluate inter-rater reliability and accuracy of the NMOSS. RESULTS: The NMOSS is based on the EDSS but was modified to increase the sensitivity to visual acuity and visual fields. Motor, sensory and bowel/bladder scores were only slightly modified and the brainstem score was changed to focus on NMO-specific attacks of the area postrema and diencephalon. Validation of the NMOSS is ongoing; inter-rater reliability will be calculated using Spearman's rank correlation coefficient and the NMOSS will be analyzed for content and predictive validity. CONCLUSIONS: The NMOSS is a new NMO-specific disability scale for future clinical trials. Study Supported by: The Guthy Jackson Charitable Foundation
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".