Bibliographic record
Abstract
The myoclonic epilepsies are a group of syndromes in which myoclonic seizures are a prominent symptom. However, they persistently present a challenge during neurological training and are often difficult to comprehend. The molecular advances in our understanding of the progressive myoclonus epilepsies, the recognition of the patterns of idiopathic generalized epilepsy in adults, and the identification of myoclonic epilepsy syndromes in children have clarified considerably the dimensions of the problem. However, there are currently many questions about both malignant and benign myoclonic epilepsies that need resolution. Particularly striking is the tremendous range in the etiology of myoclonic disorders from the most malignant, as in the progressive myoclonus epilepsies, to the most benign and most easily treated, as in the idiopathic generalized epilepsies. In addition, it has recently become clear that some drugs are effective antimyoclonic agents, whereas others are promyoclonic and may contribute to the emergence or aggravation of myoclonus. The principles of treatment of myoclonus are not necessarily the same as those for the treatment of the epilepsies in general. Clearly, the myoclonic epilepsies are an intriguing group of disorders that will benefit from this instructive and highly relevant discussion. The following articles are compiled from the proceedings of a satellite symposium sponsored by the American Epilepsy Society, held in December 2001, and seek to present a thorough examination of myoclonic epilepsies, resulting in improved understanding, diagnosis, and more effective treatment. It is necessary to classify a patient's syndrome correctly since treatment, prognosis, and further research depend on accurate categorization. Dr. Ilo Leppik's article provides a detailed discussion of the various classifications of the myoclonic epilepsies and the importance of accurate classification. Likewise, it is also essential to examine the clinical description of myoclonic disorders. Dr. Edward Faught reviews the phenomenology of myoclonic seizures and the classification of myoclonus based on correlations with EEG and EMG. Molecular genetic research in myoclonus further assists in providing a more accurate syndrome classification and ultimately is expected to provide rational treatment through gene therapy. Dr. Antonio Delgado-Escueta provides an overview of the new advances in molecular genetics of benign or idiopathic and progressive myoclonus epilepsies in infants, children, adolescents, and adults. Finally, we must consider the treatment strategies for myoclonic epilepsy. More treatment options are available today and the clinician faces the challenge of determining the most appropriate approach. Dr. James Wheless discusses treatment options based on determining etiology and rational classification of the epilepsy syndrome. Despite the challenges involved in treatment, significant advances in both our understanding of the underlying etiology, classification, genetics, and treatment options for myoclonic epilepsies have recently surfaced, and current research continues to progress.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.495 | 0.362 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".