Guideline concordant screening and monitoring of extrapyramidal symptoms in patients prescribed antipsychotic medication: a systematic review and narrative synthesis
Notice bibliographique
Résumé
Introduction Given the increasing rates of antipsychotic use in multiple psychiatric conditions, greater attention to the assessment, monitoring and documentation of their side effects is warranted. While significant attention has been provided to metabolic side effect monitoring, comparatively little is known about how clinicians screen for, document and monitor their motor side effects (i.e. parkinsonism, akathisia, dystonia and tardive dyskinesia (TD), collectively “extrapyramidal symptoms” or EPS). Objectives This review aims to systematically assess the literature for insights into current trends in EPS monitoring practices within various mental health settings globally. Methods In line with our preregistered protocol (PROSPERO: CRD42023482372), we systematically searched the OVID Medline, PubMed, Embase, CINAHL and PsycINFO databases for studies published from 1998 to present day. Figure 1 shows a detailed flowchart of the selection process. Included studies were assessed for quality using a modified version of the Quality Improvement Minimum Criteria Set (QI-MQCS) and findings summarized using narrative synthesis. All stages of the review process are reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Results A total of 22 studies met our inclusion criteria. Studies occurred in varied settings and employed a range of study designs. The APA and NICE guidelines were most commonly used to guide practice. Baseline monitoring rates in adult settings ranged from 0 to 54%, and 3.7 to 100% in child & adolescent settings. In studies reassessing EPS monitoring rates following practice improvement initiatives, virtually all demonstrated benefits. Screening processes and instruments varied, ranging from standardized rating scales (such as the AIMS for TD screening) to locally developed tools. In some studies, no structured tool was identified. Monitoring rates were higher when structured processes and tools were used. Image 1: Conclusions This review demonstrates significant heterogeneity in clinical practice for the screening, documentation, and monitoring of EPS in patients prescribed antipsychotic medication in mental health settings globally. Adherence to existing guidelines was found to be poor in most settings, with practice improvements observed in virtually all settings where quality improvement initiatives were implemented. The best improvements were seen to occur after services introduced structured EPS screening tools with regular education on their use. Disclosure of Interest R. Aubry: None Declared, T. Hastings: None Declared, M. Morgan: None Declared, J. Hastings: None Declared, M. Bolton: None Declared, M. Grummell: None Declared, R. Shorr: None Declared, S. Killeen: None Declared, C. Coyne: None Declared, M. Solmi Consultant of: MS has received honoraria/has been a consultant for AbbVie, Angelini, Lundbeck, Otsuka.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
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 tête enseignante, 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 ».