Abstract
BACKGROUND: The Single-Point Insulin Sensitivity Estimator (SPISE) is a biomarker of insulin sensitivity estimated using BMI and triglycerides and high-density lipoprotein cholesterol. We assessed the accuracy of SPISE to screen obesity-related cardiometabolic risk in children and adolescents. METHOD: Cross-sectional validation study for a screening test in a sample of n=725 children and adolescents from an obesity clinic. Weight, height, waist circumference, blood arterial pressure, lipid profile, glucose, insulin and Tanner stage were measured. BMI, BMI for-age-and sex (BAZ), and HOMA-IR were estimated. HOMA-IR values ≥2.1 and ≥3.3 were considered IR in Tanner I-II, ≥3.3 for Tanner III-IV and ≥2.6 for Tanner V, respectively. Metabolic Syndrome (MetS) was diagnosed with the Cook phenotype. SPISE was estimated according to the following algorithm: [600* HDL^0.185/(TG^0.2* BMI^1.338)]. The optimal SPISE cut points for IR and MetS prediction were determined by ROC curve analysis. RESULTS: In prepubertal obese patients (9.2 ± 2.1y; 18.4% males), the prevalence of IR and MetS was 28.2% y 46.9%, respectively; 58% had severe obesity (BAZ ≥4 SD). In pubertal obese patients (12.6 ± 1.8y; 57% males), the prevalence of IR and MetS was 34.1% and 55.3%, respectively; 34% had severe obesity. In prepubertal children, a SPISE of 6.3 showed the highest sensitivity (73.2%) and specificity (80%) to screen individuals with IR (AUC: 0.80; LR +: 3.3). Likewise, a SPISE of 5.7 got the highest sensitivity (82.6%) and specificity (86.1%) to screen patients with MetS (AUC: 0.87; LR +: 5.4). In pubertal patients, a SPISE of 5.4 showed the highest sensitivity and specificity to screen children and adolescents with both IR (Sn: 76.1%; Sp: 77.5%; AUC: 0.8; LR +: 3.1) and MetS (Sn: 90.4%; Sp: 76.1%; AUC: 0.90; LR +: 3.5). CONCLUSION: In children and adolescents with obesity, SPISE has good or very good performance in predicting IR and MetS. SPISE may be considered a relatively simple and low-cost diagnosis tool that can be helpful to identify patients with greater biological risk. In adolescents with obesity, the same cut point allows identification of those at higher risk of both IR and MetS.