Assessing Metabolic Syndrome Risk in Children and Adolescents with Prader-Willi Syndrome: A Comparison of Index...

Background: Currently, there is a lack of data regarding the reliability of different anthropometric, instrumental, and biochemical indexes in detecting metabolic syndrome (MetS) in pediatric patients with Prader-Willi syndrome (PWS). Therefore, this study aimed to compare the accuracy of different indices to identify the simplest and most accurate predictor of MetS in this at-risk population. Methods: We conducted a multicenter study involving 124 children and adolescents with PWS (61 males and 63 females), aged 13.6 ± 3.7 years. For each participant, we assessed all components of MetS, defined according to either the Identification and prevention of Dietary- and lifestyle-induced health EFfects In Children and infantS (IDEFICS) study or the International Diabetes Federation (IDF) criteria, based on age. The following indexes were calculated: Body Mass Index (BMI), BMI standard deviation score (BMI-SDS), tri-ponderal mass index, body mass fat index, fat mass index, fat-free mass index, body shape index, visceral adiposity index, waist-to-height ratio, cardiometabolic index, total cholesterol/high-density lipoprotein cholesterol (HDL-C) ratio, and triglycerides/HDL-C (TG/HDL-C) ratio. Results: MetS was identified in 24 subjects (9 females and 15 males), representing 19.4% of the sample. When comparing the receiver operating characteristic (ROC) curves, the TG/HDL-C ratio and cardiometabolic index demonstrated significantly better performance than the other indices in detecting MetS, with no difference between the two. As a result, we focused on the TG/HDL-C ratio since it is the simplest measure, requiring no additional anthropometric data compared to the cardiometabolic index. Additionally, applying age- and gender-specific thresholds can further improve its accuracy. Conclusions: The TG/HDL-C ratio, which requires only two standard biochemical markers, provides the same accuracy as more complex indexes in detecting MetS in children and adolescents with PWS, making it the optimal predictor for MetS in this population.