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In search of measures to improve the detection of increased cardiometabolic risk in children using second-generation antipsychotic medications

Abstract Purpose Second-generation antipsychotic medications (SGAs) are widely used in child psychiatry. SGA-induced metabolic disturbances are common in children, but monitoring practices need systematisation. The study’s aims were to test an SGA-monitoring protocol, examine the distributions of metabolic measurements compared to reference values in child psychiatry patients, and determine whether using a homeostasis model for the assessment of insulin resistance (HOMA-IR) and triglyceride/high-density lipoprotein (TG/HDL) ratio could improve the detection of increased cardiometabolic risk. Materials and methods A systematic monitoring protocol was implemented. Weight and height, blood pressure, fasting glucose, insulin, HDL, and TG were measured at baseline and four times during follow-up. HOMA-IR, TG/HDL ratio and zBMI were calculated. Age-, gender- and BMI-specific percentile curves for HOMA-IR were used to define elevated cardiometabolic risk. Results The study patients (n = 55, mean age 9.9 years) were followed for a median of 9 months. A disadvantageous, statistically significant shift, often appearing within the reference range, was seen in zBMI, TG, HDL, glucose, insulin, HOMA-IR, and TG/HDL ratio. The increase in HOMA-IR appeared earlier than individual laboratory values and was more evident than the TG/HDL ratio increase. An HOMA-IR cut point of 1.98 resulted in a sensitivity and specificity of 83%. Compared to a previous study performed in the same location, the monitoring rates of metabolic parameters improved. Conclusion The monitoring protocol implementation improved the monitoring of metabolic parameters in child psychiatric patients using SGAs. Using HOMA-IR as part of systematic SGA monitoring could help detect metabolic adverse effects.