Management of epilepsy with eyelid myoclonia: Results of an international expert consensus panel
Bibliographic record
Abstract
OBJECTIVE: There are limited data about the treatment and management of epilepsy with eyelid myoclonia (EEM). The objective of this study was to determine areas of consensus among an international panel of experts for the management of EEM (formerly known as Jeavons syndrome). METHODS: An international steering committee was convened of physicians and patients/caregivers with expertise in EEM. This committee summarized the current literature and identified an international panel of experts (comprising 25 physicians and five patients/caregivers). This panel participated in a modified Delphi process, including three rounds of surveys to determine areas of consensus for the treatment, other areas of management, and prognosis for EEM. RESULTS: There was a strong consensus for valproic acid as the first-line treatment, with levetiracetam or lamotrigine as preferable alternatives for women of childbearing age. There was a moderate consensus that ethosuximide and clobazam are also efficacious. There was a strong consensus to avoid sodium channel-blocking medications, except for lamotrigine, as they may worsen seizure control. There was consensus that seizures typically persist into adulthood, with remission occurring in <50% of patients. There was less agreement about other areas of management, including dietary therapy, lens therapy, candidacy for driving, and outcome. SIGNIFICANCE: This international expert panel identified multiple areas of consensus regarding the optimal management of EEM. These areas of consensus may inform clinical practice to improve the management of EEM. In addition, multiple areas with less agreement were identified, which highlight topics for further research.
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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 | 0.194 | 0.202 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".