Abstract
Accurate and timely interpretation of microcytic anemia can be diagnostically challenging in the primary care setting. We sought to develop a novel model for distinguishing iron-deficiency anemia from thalassemia trait in the modern pediatric population. Demographic history and red blood cell indices were retrospectively characterized for 76 children referred to our pediatric hematology clinic for evaluation of microcytic anemia. Statistically significant variables were sequentially added into a logistic regression model to develop the final model. The final discriminating model incorporates red cell distribution width, mean corpuscular hemoglobin concentration, and red blood cell values. Favorable predictive performance is seen in the initial (sensitivity 89.2%, specificity 92.3%) and external validation cohort (sensitivity 84.4%, specificity 88.9%). This novel tool may aid in determining the cause of hypochromic, microcytic anemia in the primary care setting. Finally, the study cohort reflects an underrepresented group in the development of screening tools, and thus offers generalizability.
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