Pediatric Occipital Spikes at a Single Center Over 26 Years and the Significance of Tangential Dipole
Bibliographic record
Abstract
Background: Pediatric occipital epileptiform discharges occur in various clinical settings, including self-limited and treatment-resistant epilepsies. The study objective is to determine electro-clinical predictors for prognosis in children with occipital epileptiform discharges. Methods: 205 patients with occipital epileptiform discharges were classified into seizure groups: self-limited occipital (SLO) (n = 57), including Panayiotopoulos and Gastaut syndrome; non-self-limited occipital (non-SLO) (n = 98), including various seizure etiologies; genetic-generalized (n = 18); febrile (n = 5); and no-seizure (n = 27) groups. Electro-clinical features of the SLO and non-SLO were compared, as this is of most clinical relevance. Results: The median age of seizure onset was 3 years (range: 0-19). Occipital epileptiform discharges with frontal/central positivity were present in both groups, but more common in the SLO than non-SLO groups; 21/57 (36.8%) and 19/98 (19.4%), respectively ( P < .022). However, when occipital epileptiform discharges with tangential dipoles ( P < .048) were accompanied by abnormal ictal eye movements ( P < .037), they were predictive of SLO epilepsy. Conclusions: In our cohort, occipital epileptiform discharges with tangential dipole detected by visual analysis and abnormal ictal eye movements were predictive of SLO epilepsy.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".