Osés Recalde, MaddiCadenas-Sánchez, CristinaMedrano Echeverría, MaríaGalbete Jiménez, ArkaitzMiranda Ferrúa, EmilianoRuiz, Jonatan R.Sánchez-Valverde, FelixOrtega, Francisco B.Cabeza Laguna, RafaelVillanueva Larre, ArantxaIdoate, FernandoLabayen Goñi, Idoia2022-08-192022-08-192022Oses, M.; Cadenas-Sanchez, C.; Medrano, M.; Galbete, A.; Miranda-Ferrua, E.; Ruiz, J. R.; Sánchez-Valverde, F.; Ortega, F. B.; Cabeza, R.; Villanueva, A.; Idoate, F.; Labayen, I.. (2022). Development of a prediction protocol for the screening of metabolic associated fatty liver disease in children with overweight or obesity. Pediatric Obesity. 17.2047-630210.1111/ijpo.12917https://academica-e.unavarra.es/handle/2454/43819Background: the early detection and management of children with metabolic associ-ated fatty liver disease (MAFLD) is challenging. Objective: to develop a non-invasive and accurate prediction protocol for the identi-fication of MAFLD among children with overweight/obesity candidates to confirma-tory diagnosis. Methods: a total of 115 children aged 8–12 years with overweight/obesity, rec-ruited at a primary care, were enrolled in this cross-sectional study. The external vali-dation was performed using a cohort of children with overweight/obesity (N=46)aged 8.5–14.0 years. MAFLD (≥5.5% hepatic fat) was diagnosed by magnetic reso-nance imaging (MRI). Fasting blood biochemical parameters were measured, and25 candidates’ single nucleotide polymorphisms (SNPs) were determined. Variablespotentially associated with the presence of MAFLD were included in a multivariatelogistic regression. Results: children with MAFLD (36%) showed higher plasma triglycerides (TG),insulin, homeostasis model assessment ofinsulin resistance (HOMA-IR), alanineaminotransferase (ALT), aspartate transaminase (AST), glutamyl-transferase (GGT)and ferritin (p< 0.05). The distribution of the risk-alleles of PPARGrs13081389, PPARGrs1801282, HFErs1800562 and PNLPLA3rs4823173 was significantly different between children with and without MAFLD (p<0.05). Threebiochemical- and/or SNPs-based predictive models were developed, showingstrong discriminatory capacity (AUC-ROC: 0.708–0.888) but limited diagnosticperformance (sensitivity 67%–82% and specificity 63%–69%). A prediction proto-col with elevated sensitivity (72%) and specificity (84%) based on two consecutive steps was developed. The external validation showed similar results: sensitivity of 70% and specificity of 85%. Conclusions: the HEPAKID prediction protocol is an accurate, easy to implant, minimally invasive and low economic cost tool useful for the early identification and management of paediatric MAFLD in primary care.application/pdfengThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial LicenseFatty liverMetabolic diseasesPaediatric obesityPrimary health careArtículo / Artikulua2022-08-19Acceso abierto / Sarbide irekiainfo:eu-repo/semantics/openAccess