Absence Epilepsy in Childhood: Electroencephalography (EEG) Does Not Predict Outcome
Bibliographic record
Abstract
Absence epilepsy is a form of generalized epilepsy commonly seen in children. The clinician is often presented with a patient whose electroencephalogram does not fit the typical absence pattern. The purpose of this study is to more closely examine both typical and atypical absence variants and their outcome. A retrospective chart review was performed on children diagnosed with absence epilepsy over the past 5 years at the University of Alberta. A total of 119 patients were reviewed. Patients were classified with typical or atypical absence seizures following International League Against Epilepsy criteria and electroencephalography (EEG) characteristics. Clinical seizure characteristics, magnetic resonance imaging (MRI), initial response to treatment, and outcome were examined. Seizure characteristics were similar in both the typical and atypical absence groups. Aura, complex automatisms, changes in tone, and incontinence were seen in both groups, although status epilepticus was found only in the atypical group. Associated comorbid conditions such as attention-deficit hyperactivity disorder (ADHD), learning disorders, and enuresis were found equally in both groups. Developmental delay was found more often in the atypical group. Of the typical group, 83% responded to an initial antiepileptic drug (either valproic acid or ethosuximide), whereas only 51% of the atypical group came under control. Remission at 2 years however, was similar between groups, with 76% of the typical group and 71% of the atypical group completely seizure free. Absence seizures in childhood, both typical and atypical, share similar clinical and electroencephalographic features and appear to be part of a continuum. Associated comorbid features such as ADHD, learning disorders, and developmental delay are also seen in both groups. The outcome for both types is excellent, although the atypical variants may be initially more difficult to control.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".