OBJECTIVE: To compare the prevalence of metabolic syndrome (MetS) and its components in second-generation antipsychotic (SGA)-treated and SGA-naive children; and to explore the utility of clinical markers, such as waist circumference (WC) and body mass index (BMI), as screening tools for MetS. METHODS: Subjects were prospectively recruited from the Psychiatry Emergency Unit at British Columbia Children's Hospital. As part of a quality-assurance project, a metabolic monitoring protocol was implemented, including collection of anthropomorphic and laboratory data. RESULTS: From January 2008 to February 2010, there were 117 SGA-treated and 217 SGA-naive children recruited. The overall prevalence of MetS was 19.0% (16/84; median treatment duration = 14 months) in SGA-treated and 0.8% (1/127) in SGA-naive children (OR 29.7; 95% CI 3.85 to 228.40, P < 0.001), with an increased prevalence of all components except high-density lipoprotein cholesterol (HDL-C), respectively: elevated WC (40.7% and 10.1%; P < 0.001); hypertriglyceridemia (33.7% and 18.8%; P = 0.01); impaired fasting glucose (12.5% and 0.7%; P = 0.005); and elevated blood pressure (41.2% and 16.5%; P < 0.001). SGA treatment was the strongest predictor of MetS (OR 19.2; 95% CI 2.30 to 160.44, P = 0.006) followed by male sex (OR 5.7; 95% CI 1.08 to 30.62, P = 0.04). Presence of abdominal obesity was more sensitive (92.9%) than BMI (68.8%), while fasting glucose of 5.6 mmol/L or more and HDL-C of 1.03 mmol/L or less were most specific (94.1%) in correctly identifying MetS. CONCLUSIONS: SGA treatment confers a significantly increased risk for MetS over the long term. WC measurement is a simple and sensitive screening tool for determining MetS risk in SGA-treated children. These data highlight the dangers of SGA treatment and the importance of standardized metabolic monitoring using sex- and age-adjusted tables in this population.
OBJECTIVE: To compare the prevalence of metabolic syndrome (MetS) and its components in second-generation antipsychotic (SGA)-treated and SGA-naive children; and to explore the utility of clinical markers, such as waist circumference (WC) and body mass index (BMI), as screening tools for MetS. METHODS: Subjects were prospectively recruited from the Psychiatry Emergency Unit at British Columbia Children's Hospital. As part of a quality-assurance project, a metabolic monitoring protocol was implemented, including collection of anthropomorphic and laboratory data. RESULTS: From January 2008 to February 2010, there were 117 SGA-treated and 217 SGA-naive children recruited. The overall prevalence of MetS was 19.0% (16/84; median treatment duration = 14 months) in SGA-treated and 0.8% (1/127) in SGA-naive children (OR 29.7; 95% CI 3.85 to 228.40, P < 0.001), with an increased prevalence of all components except high-density lipoprotein cholesterol (HDL-C), respectively: elevated WC (40.7% and 10.1%; P < 0.001); hypertriglyceridemia (33.7% and 18.8%; P = 0.01); impaired fasting glucose (12.5% and 0.7%; P = 0.005); and elevated blood pressure (41.2% and 16.5%; P < 0.001). SGA treatment was the strongest predictor of MetS (OR 19.2; 95% CI 2.30 to 160.44, P = 0.006) followed by male sex (OR 5.7; 95% CI 1.08 to 30.62, P = 0.04). Presence of abdominal obesity was more sensitive (92.9%) than BMI (68.8%), while fasting glucose of 5.6 mmol/L or more and HDL-C of 1.03 mmol/L or less were most specific (94.1%) in correctly identifying MetS. CONCLUSIONS: SGA treatment confers a significantly increased risk for MetS over the long term. WC measurement is a simple and sensitive screening tool for determining MetS risk in SGA-treated children. These data highlight the dangers of SGA treatment and the importance of standardized metabolic monitoring using sex- and age-adjusted tables in this population.
Authors: Candice M Klingerman; Michelle E Stipanovic; Mohammad Bader; Christopher J Lynch Journal: Schizophr Bull Date: 2013-01-17 Impact factor: 9.306
Authors: Amanda M Henderson; Nazrul Islam; George G S Sandor; Constadina Panagiotopoulos; Angela M Devlin Journal: Can J Psychiatry Date: 2020-12-02 Impact factor: 4.356