Organic Catatonia Secondary to Central Nervous Infection : An Evidence Based Case Report - Wiranata, Kristian; Puspowardojo, Irena Aryani; Fitrikasari, Alifiati; Suryawati, Herlina; Sofro, Muchlis Achsan Udji; MR, Witrie Sutaty (RSUP Dr. Kariadi, 2026)
Background: Organic catatonia has been associated with various infectious etiologies, particularly central nervous system infections. While benzodiazepines and electroconvulsive therapy (ECT) are the most extensively studied treatments, accurate identification and targeted management of the underlying cause remain essential for effective treatment Aims : evaluating evidence-based therapeutic strategies for the management of organic catatonia in patients with infections. Method : Electronic Data Based was conducted using PubMed, ScienceDirect, Google Scholar, Cochrane, and Proquest. Eligible studies published between 2015 and 2025 included randomized controlled trials, systematic reviews, and case reports or case series focusing on the treatment of organic catatonia associated with central nervous system infections. Literature reviews, abstracts, non-English publications, and studies not aligned with the predefined PICO were excluded. Selected articles were critically appraised using the Joanna Briggs Institute (JBI) Critical Appraisal tools. Results : 458 articles was identified, two studies (case series and case report) met the inclusion criteria. Abhijita et al. emphasized evidence-based management of organic catatonia secondary to meningitis (treated with ceftriaxone, doxycycline, lorazepam, and olanzapine, in addition to electroconvulsive therapy), while Doval et al. highlighted key diagnostic and therapeutic considerations in organic catatonia following encephalitis (treated with haloperidol, promethazine, lorazepam, amantadine, and escitalopram). Overall, these case reports offer valuable clinical insights. Conclusion : Alongside infection-directed therapy, early recognition and timely pharmacological management of organic catatonia are essential for achieving optimal clinical outcomes.