Testing for Antibodies Against Aquaporin-4 and Myelin Oligodendrocyte Glycoprotein in the Diagnosis of Patients With Suspected Autoimmune Myelopathy
Bibliographic record
Abstract
Autoimmune myelopathies are immune-mediated disorders of the spinal cord that can cause significant neurologic disability. Discoveries of antibodies targeting aquaporin-4 (AQP4-IgG) and myelin oligodendrocyte glycoprotein (MOG-IgG) have facilitated the diagnosis of autoimmune myelopathies that were previously considered to be atypical presentations of multiple sclerosis (MS) or idiopathic, and represent major advancements in the field of autoimmune neurology. The detection of these antibodies can substantially impact patient diagnosis and management, and increasing awareness of this has led to a dramatic increase in testing for these antibodies among patients with suspected autoimmune myelopathy. In this review we discuss test methodologies used to detect these antibodies, the role of serum vs. cerebrospinal fluid testing, and the value of antibody titers when interpreting results, with the aim of helping laboratorians and clinicians navigate this testing when ordered as part of the diagnostic evaluation for suspected autoimmune myelopathy.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".