Authors
Kaitlyn Baldwin, William G Honer, Reza Shahbazi, Diane Fredrikson, Randall F White, Fidel Villa-Rodriguez, Reza Rafizadeh
Published in
Schizophrenia bulletin. Volume 52. Issue 6. Oct 27, 2026.
Abstract
Clozapine-resistant schizophrenia (CRS) remains a major clinical challenge, with persistent symptoms and functional impairment despite adequate clozapine treatment. Real-world evidence is limited, and guidelines recommend a narrow set of augmentation strategies-aripiprazole (D2/3R partial agonist), amisulpride (D2/3R selective antagonist), and electroconvulsive therapy (ECT)-without clear guidance on selection or sequencing. This study examined augmentation choice and its association with length of stay (LOS) and symptomatic outcomes.
We conducted a retrospective cohort study using BC Psychosis Program electronic records (2012-2025). Symptom severity and functioning scores (PANSS, CGI-S, GAPS, SOFAS) were extracted at admission and discharge. Multivariable Cox models assessed LOS for index and discharge augmentation strategies. ANCOVA compared symptom change across discharge strategies. A machine-learning model examined predictors of ECT versus pharmacological augmentation at discharge.
Eighty-eight admissions were included. In adjusted index models, D2/3R selective antagonism was associated with shorter LOS than ECT (HR 2.50, 95% CI 1.35-4.62); partial agonism was not (HR 1.41, 95% CI 0.75-2.63). Partial agonist augmentation had the highest inefficacy-related switching. By discharge strategy, ECT was associated with greater reduction in positive symptoms than selective antagonism (MD -3.20, 95% CI -5.65 to -0.75) and partial agonism (MD -3.87, 95% CI -6.57 to -1.16). Greater impairment in psychosis and functioning on admission predicted ECT at discharge (AUC 0.74; balanced accuracy 0.72).
D2/3R selective antagonism was the most resource-efficient strategy, while ECT produced greater improvement in positive symptoms. Incorporating baseline psychosis severity and functioning into measurement-based care may support more informed augmentation selection.
PMID:
42951688
Bibliographic data and abstract were imported from PubMed on 29 Oct 2026.
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