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Comparative efficacy of akathisia treatments: A network meta-analysis. | LitMetric

Comparative efficacy of akathisia treatments: A network meta-analysis.

CNS Spectr

SIMED (Società Italiana di Medicina e Divulgazione Scientifica), Parma, Italy.

Published: August 2024

Objective: Akathisia, a common side effect of psychotropic medications, poses a significant challenge in neuropsychiatry, affecting up to 30% of patients on antipsychotics. Despite its prevalence, akathisia remains poorly understood, with difficulties in diagnosis, patient reporting, and treatment efficacy. This research aimed to shed light on effective interventions to improve akathisia management.

Methods: A systematic review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was conducted, encompassing controlled trials in English and Italian languages. Databases, such asPubMed, Scopus, and EMBASE, were searched until July 9, 2023. Treatment effectiveness was assessed using standardized mean differences (SMDs) in post-treatment akathisia scores.

Results: Thirteen studies involving 446 individuals met the inclusion criteria. Benzodiazepines, beta-blockers, and NaSSA demonstrated significant efficacy as compared with placebo. Anticholinergic, anticonvulsant, triptan, and other treatments did not show significant differences. Benzodiazepines ranked highest in -scores (0.8186), followed by beta-blockers and NaSSA.

Conclusions: Effective management of akathisia is crucial, with benzodiazepines, beta-blockers, and NaSSA offering evidence-based options. Treatment rankings provide guidance for clinicians. Future research should prioritize larger, more robust studies to address limitations associated with small sample sizes and publication bias. This research enhances our understanding of interventions for akathisia, offering promising options to improve patient quality of life and prevent complications related to non-adherence and mismanagement.

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Source
http://dx.doi.org/10.1017/S1092852924000233DOI Listing

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