Prevalence and predictors of treatment-resistant schizophrenia in a tertiary hospital in Northeast Brazil

• Autor(a) principal: Soares,Douglas de Sousa
• Data de Publicação: 2021
• Outros Autores: Carvalho,Danyelle Rolim, Ribeiro,Mellanie Dellylah Trinta, Diniz,Elton Jorge Bessa, Rêgo Neto,Alcides Ferreira
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Trends in Psychiatry and Psychotherapy
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2237-60892021000400270
• topic: Treatment-resistant schizophrenia; clozapine; schizophrenia; psychosis; epidemiology

Abstract Objective To investigate epidemiological factors related to treatment-resistant schizophrenia (TRS) in Northeast Brazil, a region where data about mental health are still scarce. Methods This retrospective cross-sectional study included all patients with schizophrenia currently receiving treatment at the outpatient psychiatric clinic of a tertiary hospital in Northeast Brazil. They were divided into TRS and treatment-responsive groups, and epidemiological characteristics of both groups were compared. A logistic regression model investigated factors related to treatment resistance. Results Two hundred and five patients were included, 155 treatment-resistant and 50 treatment-responsive. The TRS group had higher use of benzodiazepines (36.1 vs. 18%, p = 0.017) and antiepileptics (36.8 vs. 8.0%, p < 0.001), antipsychotic polypharmacy (28.6 vs. 8%, p = 0.003) and suicide attempts (35.6 vs. 20%, p = 0.04). Age at onset was younger (19.7±7.3 vs. 24.6±8.6 years, p = 0.001) and CGI was higher in TRS (3.72±1.00 vs. 3.16±1.00, p = 0.001). In logistic regression, being married was a protector (odds ratio [OR] = 0.248, 95% confidence interval [95%CI] 0.091-0.679, p = 0.007) and younger age at onset was a predictor (OR = 1.076, 95%CI 1.034-1.120, p < 0.001) of treatment resistance. Conclusion Early onset of disease was associated with more treatment resistance, while being married with less resistance. Clinicians should identify early predictors of resistance in order to reduce unfavorable outcomes.