Epileptic EEG discharges and short non-convulsive crisis: Influence on cognitive and psychobehavioural functions in youths
Bibliographic record
Abstract
PURPOSE: Learning and behavioural difficulties often occur in benign childhood epilepsy. In recent years, several electroencephalogram (EEG) characteristics have been related to the occurrence of learning and behavioral problems. We determined if the cognitive characteristics of epileptic children depend exclusively on illness factors, or if epileptic electroencephalogram discharges during the crisis contribute to these changes. METHODS: We studied a randomly selected group of 150 youths with short non-convulsive crises, who completed cognitive testing and electroencephalographic studies. The inclusion criteria were: undefined crisis, variations in cognitive function and/or frequent epileptiform discharges on the electroencephalogram. RESULTS: Previous research indicates that the type of epilepsy and the patient's educational level can influence cognitive functioning. The electroencephalographic epileptic discharges during the crisis has been found to influence cognitive transitory functions such as vigilance or swiftness of mental functions. The type of epilepsy is correlated statistically with impairment of learning ability tests: reading (F, 5.487, P = 0.005) and mathematics (F, 3.007, P < or = 0.05). In addition, 40% of the epileptic patients had behavioural disordered versus 16% for the control group (P < 0.02). CONCLUSIONS: Our results show dissociation between the characteristic directly dependent on epilepsy, particularly the type of epilepsy, on stable cognitive functions, such as the progress in school, and the effect of parosystic anomalies or the immediate effect of crisis and EEG dischargeson cognitive processes.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".