Notice bibliographique
Résumé
Dear Editor: We read with much interest the letter by Dr Bayerlein and others (1) describing a patient who developed an acute psychotic episode during treatment with levetiracetam (LEV). In their report, the authors quoted one of our works on psychiatric adverse events (PAEs) related to LEV (2), stating that lamotrigine (LTG) cotherapy was a risk factor for the occurrence of PAEs. We wish to point out that, in our paper, we showed that this combination was a favourable one and that patients taking LTG were less likely to develop PAEs (OR 0.40; 95%CI, 0.17 to 0.92)-probably because of its antidepressant properties. A previous study showed the same findings with other antiepileptic drugs (AEDs) such as topiramate (3). Regarding the case presented by the authors, we regret to note that forced normalization (FN) was not taken into account among the possible hypotheses. Although this is a well-described phenomenon (4) with an increasing literature investigating its biological basis (5), some psychiatrists do not consider its occurrence in patients with epilepsy. This particular case is typical of one where FN may play a role. The phenomenon has been described with several AEDs, suggesting that it is more likely to be related to the clinical phenotype of the patient than to be a characteristic of the drug. In his original report, Landolt suggested that a subgroup of subjects with idiopathic generalized epilepsy could be at risk (4), and Tellenbach described alternative psychosis in patients with myoclonic epilepsy (6) like the case presented by Dr Bayerlein. Interestingly, we noted the same association in a previous study investigating the role of FN in topiramate-associated psychopathology (7). Moreover, in the presented case, seizures improved remarkably, although they were not completely suppressed. This is enough to consider that the hypothesis is plausible, according to recently suggested guidelines (8). Alternative psychoses are characterized by rapid onset and highly flourished symptoms with a short duration (usually, 1 week) followed by an almost complete remission after seizure reoccurrence or AED dosage reduction. There is no relation to the duration of AED therapy; it is seen mainly with an increase in dosage or a change in the AED regime. Thus patients who have been taking the drug for a long time may develop FN with the same drug, owing to such changes. In conclusion, the patient described by Dr Beyerlein and colleagues has several features that may make FN a reasonable hypothesis. We hope that clinicians will be more interested in this phenomenon to lead to a correct diagnosis, prognosis, and therapy of psychosis in epilepsy and to identify patients who may be studied in further research into the pathophysiology of psychosis in general and the psychosis of epilepsy in particular. References 1. Bayerlein K, Frieling H, Beyer B, Kornhuber J, Bleich S. Drug-induced psychosis after long-term treatment with levetiracetam. Can J Psychiatry 2004;49:868. 2. MuIa M, Trimble MR, Yuen A, Liu RS, Sander JW. Psychiatric adverse events during levetiracetam therapy. Neurology 2003;61:704-6. 3. MuIa M, Trimble MR, Lhatoo SD, Sander JW. …
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,013 | 0,013 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».