Incidence of Drug‐Induced Aggravation in Benign Epilepsy with Centrotemporal Spikes
Bibliographic record
Abstract
PURPOSE: Benign epilepsy with centrotemporal spikes (BECTS) is characterized by an excellent prognosis. Drug therapy is necessary in only a minority of patients. Carbamazepine (CBZ) and phenobarbital (PB) have been reported to cause electroclinical aggravation in some cases. The incidence of drug-induced aggravation in BECTS has never been established. METHODS: We retrospectively studied 98 consecutive cases of BECTS, examined at the Centre Saint Paul between 1984 and 1999; 82 patients had received one or more treatments, often successively and in association. RESULTS: We found only one case of electroclinical aggravation with CBZ among 40 patients exposed to CBZ (35 in monotherapy, five in polytherapy). An additional case showed a marked EEG aggravation on CBZ + PB among 14 patients taking PB (nine with monotherapy and five with polytherapy), and PB was apparently responsible. No patient treated with valproate or benzodiazepines showed aggravation. CONCLUSIONS: Aggravation of BECTS caused by antiepileptic drugs happens only rarely. There is a minor risk of aggravation with CBZ and also probably with PB. Drug-induced aggravation may occur only during certain periods coinciding with spontaneous worsening of BECTS.
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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 | 0.000 | 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) | 0.002 | 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".