Deoxygenation-free digital holographic microscopy discriminates sickle-cell disease in a piloted Colombian cohort via phase and shape metrics.

Rapid, reagent-free screening tools for sickle-cell disease (SCD) are urgently needed in low-resource regions where carrier frequency is high and laboratory infrastructure is scarce. We demonstrate digital holographic microscopy (DHM) as a label-free SCD tool in Colombia, imaging 885 individual erythrocytes (443 cells from venous blood of six SCD patients and 442 cells from 5 healthy donors). Two direct optical observables were extracted: phase difference (Δφ) relative to the surrounding medium and projected circularity index (CI), defined as the aspect ratio between the erythrocyte's minor and major axes. Healthy cells are characterized by Δφ = 1.72 ± 0.30 (mean ± std) rad and CI = 0.94 ± 0.04, whereas SCD cells are distributed around Δφ = 3.00 ± 0.96 rad and CI = 0.70 ± 0.19. Despite some minimal overlap between both distributions, SCD cells are statistically distinguishable from healthy ones based on both Δφ and CI (p < 0.001). A simple rule (Δφ > 2.2 radians ∧ CI < 0.85) classified individual cells with 97.40% accuracy, 94.81% sensitivity, and 100% specificity. While sophisticated classifiers can further optimize boundaries and enable anemia sub-typing, the distinctive contribution of this work is its deliberately minimalist rule - requiring no model training or engineered features - offering immediate and interpretable triage well-suited for low-resource workflows.