Epileptiform Asymetries and Treatment Response in Juvenile Myoclonic Epilepsy
Bibliographic record
Abstract
BACKGROUND: Epileptiform electroencephalogram (EEG) asymmetries are not uncommon in juvenile myoclonic epilepsy (JME) and can contribute to the misdiagnosis of this syndrome. The objective of this study is to further characterize patients with focal or asymmetric epileptiform electroencephalographic abnormalities and more specifically in terms of response to treatment. Controversial data exists in the literature concerning this issue. METHODS: We retrospectively reviewed clinical and EEG data of a group of consecutive JME patients followed at our Epilepsy Service. The first EEG available for each patient was reviewed blindly by two independent electroencephalographers. RESULTS: Twenty-eight patients with JME were identified: 11 (39.3%) were resistant to at least one appropriate anti-epileptic drug (AED), including valproate, lamotrigine, topiramate or levetiracetam. All patients except two had generalized epileptiform abnormalities. Overall, EEG asymmetries were detected in 57.1% of the cases. The proportion of EEG asymmetries between AED-sensitive group (52.9%) and AED-resistant group (63.5%) did not reach statistical significance. Concordance between examiners for identification of EEG asymmetries was good. Analysis of patients with and without asymmetries showed no statistically significant differences in comparisons of age, family history of seizure, presence of polyspike and slow wave, photosensitivity and timing of EEG related to the onset of treatment. CONCLUSION: Asymmetric electroencephalographic abnormalities are frequent in patients with JME. These features should not be misinterpreted as being indicative of partial epilepsy. In our group, asymmetries were not associated with resistance to treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads 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".