Nomenclature of Genetically Determined Myoclonus Syndromes: Recommendations of the International Parkinson and Movement Disorder Society Task Force
Bibliographic record
Abstract
Genetically determined myoclonus disorders are a result of a large number of genes. They have wide clinical variation and no systematic nomenclature. With next-generation sequencing, genetic diagnostics require stringent criteria to associate genes and phenotype. To improve (future) classification and recognition of genetically determined movement disorders, the Movement Disorder Society Task Force for Nomenclature of Genetic Movement Disorders (2012) advocates and renews the naming system of locus symbols. Here, we propose a nomenclature for myoclonus syndromes and related disorders with myoclonic jerks (hyperekplexia and myoclonic epileptic encephalopathies) to guide clinicians in their diagnostic approach to patients with these disorders. Sixty-seven genes were included in the nomenclature. They were divided into 3 subgroups: prominent myoclonus syndromes, 35 genes; prominent myoclonus syndromes combined with another prominent movement disorder, 9 genes; disorders that present usually with other phenotypes but can manifest as a prominent myoclonus syndrome, 23 genes. An additional movement disorder is seen in nearly all myoclonus syndromes: ataxia (n = 41), ataxia and dystonia (n = 6), and dystonia (n = 5). However, no additional movement disorders were seen in related disorders. Cognitive decline and epilepsy are present in the vast majority. The anatomical origin of myoclonus is known in 64% of genetic disorders: cortical (n = 34), noncortical areas (n = 8), and both (n = 1). Cortical myoclonus is commonly seen in association with ataxia, and noncortical myoclonus is often seen with myoclonus-dystonia. This new nomenclature of myoclonus will guide diagnostic testing and phenotype classification. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
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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 | 0.035 | 0.041 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.015 | 0.008 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.009 | 0.004 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".