ECTRIMS 2024 Lecture: Unraveling the spectrum of the antibody-mediated demyelinating diseases: Emerging insights
Bibliographic record
Abstract
Neuromyelitis optica spectrum disorder (NMOSD) and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) are antibody-mediated inflammatory disorders that target extracellular proteins of the central nervous system (CNS). Over the past decades, significant advances in their understanding, diagnosis, and treatment have redefined their clinical and pathological paradigms. The discovery of aquaporin-4 (AQP4) antibodies revolutionized the understanding of NMOSD, recognizing astrocytopathy as the primary pathogenic process. The diagnostic criteria have evolved to incorporate AQP4 antibody testing and expanded the spectrum of disease phenotypes. The improved understanding of disease pathophysiology has facilitated the development of highly effective therapies. The identification of antibodies to myelin oligodendrocyte glycoprotein (MOG) has also been the cornerstone for establishing MOGAD as a distinct clinical entity, subsequently leading to clarification of the spectrum of associated phenotypes, the publication of consensus diagnostic criteria, and the launch of randomized controlled trials. This article reviews key insights gained into these conditions, tracing the timelines that have shaped our knowledge. It outlines the evolution of antibody assay techniques, examines their epidemiology and phenotypic presentations, and describes the predictive factors for clinical outcome. By highlighting some remarkable treatment advances, it demonstrates the rapid and impactful progresses made in this field.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.017 |
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".