Diagnosis and Management of Opsoclonus-Myoclonus-Ataxia Syndrome in Children
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Opsoclonus-myoclonus-ataxia syndrome (OMAS) is a rare disorder of the nervous system that classically presents with a combination of characteristic eye movement disorder and myoclonus, in addition to ataxia, irritability, and sleep disturbance. There is good evidence that OMAS is an immune-mediated condition that may be paraneoplastic in the context of neuroblastoma. This syndrome may be associated with long-term cognitive impairment, yet it remains unclear how this is influenced by disease course and treatment. Treatment is largely predicated on immune suppression, but there is limited evidence to indicate an optimal regimen. METHODS: Following an international multiprofessional workshop in 2004, a body of clinicians and scientists comprising the International OMS Study group continued to meet biennially in a joint professionals and family workshop focusing on pediatric OMAS. Seventeen years after publication of the first report, a writing group was convened to provide a clinical update on the definitions and clinical presentation of OMAS, biomarkers and the role of investigations in a child presenting with OMAS, treatment and management strategies including identification and support of long-term sequelae. RESULTS: The clinical criteria for diagnosis were reviewed, with a proposed approach to laboratory and radiologic investigation of a child presenting with possible OMAS. The evidence for an upfront vs escalating treatment regimen was reviewed, and a treatment algorithm proposed to recognize both these approaches. Importantly, recommendations on monitoring of immunotherapy response and longer-term follow-up based on an expert consensus are provided. DISCUSSION: OMAS is a rare neurologic condition that can be associated with poor cognitive outcomes. This report proposes an approach to investigation and treatment of children presenting with OMAS, based on expert international opinion recognizing the limited data available.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".