The Younis Integrated Anemia Differentiation Index (YIADI): A CBC-Based Model for Physiologic Classification of Anemia

Abstract

Background: Distinguishing anemia etiologies remains diagnostically challenging. While serum ferritin, vitamin B12, and folate represent established standards, inflammatory conditions, limited accessibility, and delayed testing constrain their utility. A CBC-based screening tool could enhance preliminary classification and guide targeted biochemical investigation. Objective: To develop and validate the Younis Integrated Anemia Differentiation Index (YIADI), a novel composite metric derived exclusively from routine CBC parameters for initial anemia classification. Methods: This cross-sectional study evaluated 140 adult anemic patients. YIADI was calculated as (RDW × Platelets) / (Hemoglobin × MCV × RBC). Anemia subtypes were classified biochemically: iron deficiency (ferritin <30 ng/mL, n=55), chronic disease (ferritin ≥50 ng/mL, n=35), mixed anemia (concurrent abnormalities, n=30), and thalassemia trait (normal ferritin with microcytosis and elevated RBC, n=20). Predefined thresholds: >2.0 (iron deficiency), 0.8–2.0 (mixed), 0.3–0.8 (chronic disease), <0.3 (thalassemia). Performance was assessed via sensitivity, specificity, and ROC analysis. Results: YIADI demonstrated distinct distributions, iron deficiency (5.6±3.1), mixed anemia (1.4±0.3), chronic disease (0.6±0.1), thalassemia trait (0.24±0.06). Sensitivity ranged 86–95%; specificity 84–92%. Thalassemia trait achieved the highest performance (sensitivity 95%, specificity 92%), followed by iron deficiency (sensitivity 93%, specificity 90%). Overall accuracy (90%) exceeded the Mentzer index (74%), RDW alone (68%), and MCV alone (62%). ROC analysis yielded AUC values: thalassemia 0.96 (95% CI: 0.91–0.99), iron deficiency 0.94 (0.89–0.98), and chronic disease versus iron deficiency 0.92. Conclusion: YIADI is a physiologically grounded, CBC-based tool enabling reliable initial anemia stratification with superior diagnostic accuracy. While not replacing biochemical testing, it optimizes diagnostic pathways, particularly in resource-limited or high-volume settings.