RESUMEN
OBJECTIVE: To assess the diagnostic accuracy of existing clinical criteria and to develop prediction tools for iron deficiency in 2-year-old children. STUDY DESIGN: In a national cross-sectional study conducted in primary care pediatricians' practices throughout France, 2-year-old children were consecutively included (2016-2017). Multivariable logistic regression modeling and bootstrapping were used to develop several clinical models to predict iron deficiency (serum ferritin <12 µg/L). These models used the best criteria and combinations among the American Academy of Pediatrics' (AAP) criteria adapted to the European context (n = 10), then all potential predictors (n = 19). One model was then simplified into a simple prediction tool. RESULTS: Among 568 included infants, 38 had iron deficiency (6.7%). In univariable analyses, no significant association with iron deficiency was observed for 8 of the 10 adapted AAP criteria. Three criteria (both parents born outside the European Union, low weight at 1 year old, and weaning to cow's milk without supplemental iron) were retained in the AAP model, which area under the receiver operating characteristic curve, sensitivity, and specificity were 0.62 (95% CI, 0.58-0.67), 30% (95% CI, 22%-39%), and 95% (95% CI, 92%-97%), respectively. Four criteria were retained in a newly derived simple prediction tool (≥1 criterion among the 3 previous plus duration of iron-rich formula consumption <12 months), which area under the receiver operating characteristic curve, sensitivity, and specificity were 0.72 (95% CI, 0.65-0.79), 63% (95% CI, 47%-80%), and 81% (95% CI, 70%-91%), respectively. CONCLUSIONS: All prediction tools achieved acceptable diagnostic accuracy. The newly derived simple prediction tool offered potential ease of use. TRIAL REGISTRATION: ClinicalTrials.gov NCT02484274.