Clinical presentation and evaluation of epilepsy with eyelid myoclonia: Results of an international expert consensus panel
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to determine areas of consensus among an international panel of experts for the clinical presentation and diagnosis of epilepsy with eyelid myoclonia (EEM; formerly known as Jeavons syndrome) to improve a timely diagnosis. 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 international expert panel participated in a modified Delphi process, including three rounds of surveys to determine areas of consensus for the diagnosis of EEM. RESULTS: There was a strong consensus that EEM is a female predominant generalized epilepsy syndrome with onset between 3 and 12 years of age and that eyelid myoclonia must be present to make the diagnosis. There was a strong consensus that eyelid myoclonia may go unrecognized for years prior to an epilepsy diagnosis. There was consensus that generalized tonic-clonic and absence seizures are typically or occasionally seen in patients. There was a consensus that atonic or focal seizures should lead to the consideration of reclassification or alternate diagnoses. There was a strong consensus that electroencephalography is required, whereas magnetic resonance imaging is not required for diagnosis. There was a strong consensus to perform genetic testing (either epilepsy gene panel or whole exome sequencing) when one or a combination of factors was present: family history of epilepsy, intellectual disability, or drug-resistant epilepsy. SIGNIFICANCE: This international expert panel identified multiple areas of consensus regarding the presentation and evaluation of EEM. These areas of consensus may be used to inform clinical practice to shorten the time to the appropriate diagnosis.
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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 | 0.125 | 0.138 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".