Resumo

FAASEN, N; NIEHAUS, D J H; KOEN, L  e  JORDAAN, E. Undiagnosed metabolic syndrome and other adverse effects among clozapine users of Xhosa descent. S. Afr. j. psyc. [online]. 2014, vol.20, n.2, pp.54-57. ISSN 2078-6786.  http://dx.doi.org/10.7196/SAJP.528.

BACKGROUND: Clozapine use is known to be associated with significant side-effects, including prolongation of the QT-interval, agranu-locytosis and metabolic syndrome. However, few data exist on the prevalence of clozapine side-effects in patients of Xhosa descent. OBJECTIVE: To gather data from Xhosa patients with schizophrenia to establish the prevalence of clozapine side-effects in this population. METHODS: Twenty-nine Xhosa patients with schizophrenia (as per the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR)) who had been receiving clozapine treatment for >1 year on an outpatient basis were selected for inclusion. All patients were participating in a genetics study in the Cape Metropolitan area. The participants were evaluated for the presence of side-effects (tests including an electrocardiogram, white blood cell count (WCC) and fasting blood glucose. RESULTS: The prevalence of metabolic syndrome was 44.8% (95% confidence interval (CI) 26.7 - 62.9) and of undiagnosed diabetes mellitus 13.8% (95% CI 1.24 - 26.34). There was a significant association between metabolic syndrome and body mass index (BMI) (p<0.01). The mean (SD) WCC was 7.8 x 10⁹/L (2.8), with 3.4% of the subjects having a WCC <3.5 x 10⁹/L. Sedation (82.8%; 95% CI 69.0 - 96.5), hypersalivation (79.3%; 95% CI 64.6 - 94.1) and constipation (44.8%; 95% CI 26.7 - 62.9) were common. The mean QT-interval was 373.8 (35.9) ms and 10% had a corrected QT-interval >440 ms. There was an association between the duration of clozapine treatment and QT-interval (with Bazett's correction. CONCLUSION: The high prevalence of metabolic syndrome and undiagnosed diabetes mellitus in this sample points to a need to monitor glucose levels and BMI on a regular basis. A larger study should be done to accurately quantify the differences in prevalence of side-effects between population groups.

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