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Enregistrement W4407387193 · doi:10.1093/ijnp/pyae059.296

IS THERE AN OPTIMAL ELECTRODE PLACEMENT FOR PATIENTS WITH SCHIZOPHRENIA UNDERGOING ELECTROCONVULSIVE THERAPY?

2025· article· en· W4407387193 sur OpenAlexaboutno aff
Weng Jun Tan, Jenies Hui Xin Foo, Kimberly Wan Xin Choo

Notice bibliographique

RevueThe International Journal of Neuropsychopharmacology · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueElectroconvulsive Therapy Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésElectroconvulsive therapySchizophrenia (object-oriented programming)MedicinePsychiatryPsychology

Résumé

récupéré en direct d'OpenAlex

Abstract Background Electroconvulsive therapy (ECT) using the 3 common electrode placements, namely bitemporal, bifrontal and right unilateral (RUL) modalities, has been shown to be efficacious in symptom-reduction in patients with schizophrenia (Ali et al., 2019). However, the most efficacious modality for the treatment of schizophrenia has not been ascertained. Furthermore, the benefit of switching ECT modalities after poor response to the initial electrode placement has not been well-studied. Aims And Objectives We hypothesise that different patients with schizophrenia respond well to a particular ECT modality but not to another. These patients would benefit from switching ECT modalities once a lack of response to the initial modality is identified. Hence, we aim to illustrate the twin issues of the optimal ECT modality and the effect of switching ECT modalities after initial non-response in patients with schizophrenia. Method We report a case series of two distinct patients with schizophrenia who underwent multiple courses of both bifrontal and RUL ECT. Their response to ECT was objectively assessed by comparing their scores on the Brief Psychiatric Rating Scale (BPRS) and the Global Assessment of Functioning (GAF) scale prior to the commencement of ECT with their scores after the 6th and 12th sessions of ECT. The Montreal Cognitive Assessment (MoCA) was used to assess for cognitive side effects of ECT. Results Both patients showed good response to at least one previous course of bifrontal ECT. Subsequently, they were given 6 sessions of RUL ECT with the aim to minimise cognitive side effects, but their response to RUL ECT was poor. However, after they were switched back to bifrontal ECT, they showed marked improvement in their BPRS and GAF scores. Furthermore, one of the patients had a better MoCA score after he was switched back to bifrontal ECT than when he had received RUL ECT. Discussion And Conclusion As both patients had lacked response to RUL ECT but consistently responded well to bifrontal ECT, we believe that different patients with schizophrenia only respond well to a certain type of ECT modality. This is possibly because the pattern and degree of brain stimulation can be affected by the type of electrode placement which influences the strength and distribution of the electric field generated by the ECT stimulus (Bai et al., 2017; Bai et al., 2019; Lee et al., 2010), as well as anatomical differences such as head-size and skull-thickness (Bai et al., 2019; Fridgeirsson et al., 2021). In conclusion, there is no optimal ECT modality for the treatment of schizophrenia currently. Patients present with a variety of demographics, anatomy and severity of symptoms, and hence we believe that the prescription of ECT should be individualised, rather than employ a “one size fits all” approach. If response to a particular type of ECT modality is insufficient after 6 sessions, a switch to a different modality should be strongly considered as adequate response may only be achieved using a different ECT modality that is unique to the individual patient. References [1]Ali, SA. et al. (2019) ‘Electroconvulsive therapy and schizophrenia: a systematic review’, Mol Neuropsychiatry. 5(2), pp. 75-83. doi:10.1159/000497376. [2]Bai, S. et al. (2017) ‘Computational models of bitemporal, bifrontal and right unilateral ECT predict differential stimulation of brain regions associated with efficacy and cognitive side effects’, Eur Psychiatry. 41, pp. 21-29. doi:10.1016/j.eurpsy.2016.09.005. [3]Bai, S. et al. (2019) ‘Computational comparison of conventional and novel electroconvulsive therapy electrode placements for the treatment of depression’, Eur Psychiatry. 60, pp. 71-78. doi:10.1016/j.eurpsy.2019.05.006. [4]Lee, WH. et al. (2010) ‘Regional electric field induced by electroconvulsive therapy: a finite element simulation study’, Annu Int Conf IEEE Eng Med Biol Soc. 2010, pp. 2045-2048. doi:10.1109/IEMBS.2010.5626553. [5]Fridgeirsson, EA. et al. (2021) ‘Electric field strength induced by electroconvulsive therapy is associated with clinical outcome’, Neuroimage Clin. 30, pp. 102581. doi:10.1016/j.nicl.2021.102581.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,188
Score d'incertitude au seuil0,568

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,013
Tête enseignante GPT0,337
Écart entre enseignants0,324 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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