Comparative Analysis of Manual and Automated Reticulocyte Count in Patients Referred for Haemoglobin Studies in A Tertiary Care Setting: A Cross-Sectional Study - Yousof, Saad; Bozdar, Manzar; Shamoon, Mohib; Mahmood, Rafia; Khurshid, Ayesha; Khan, Aysha; Korejo, Saqib Hussain; Shafaat, Syeda Samia (Pakistan Armed Forces Medical Journal, 2026)
Objective: To compare the effectiveness and accuracy between manual and automated reticulocyte counting methods, and to assess the agreement between these methods. Study Design: Analytical ross-sectional study. Place and Duration of Study: Department of Hematology, Armed Forces Institute of Pathology (AFIP), Rawalpindi, from Jul 2024 to Feb 2025. Methodology: Reticulocyte counts were simultaneously determined by manual microscopic counting and automated counting using the Sysmex XN-3000 hematology analyzer. Comparability, intra-batch precision, correlation, and cost-effectiveness of both methods were evaluated. Data analysis included descriptive statistics, Spearman’s correlation, and Bland-Altman agreement analysis was performed using Statistical Package for the Social Sciences (SPSS) version 23.0. Results: A total of 189 patient samples were analyzed, comprising 108(57.1%) males and 81(42.9%) females, with a median age of 20.0 years. Manual reticulocyte counts had a median of 1.80% (Range: 0.2–10.5%), whereas automated counts showed a median of 2.20% (Range: 0.3–12.6%). Spearman’s rank correlation demonstrated a strong positive correlation between the two methods (ρ=0.960, p<0.001). Bland-Altman analysis revealed a mean bias of 0.44% (95% Confidence Interval: 0.357–0.531%), indicating slight systematic overestimation by the automated method. Using manual criteria, 102(54.0%) samples were classified as normal (1.0–2.5%), whereas the automated method similarly classified 90(47.6%) samples. The automated method categorized more samples as high (>2.5%) compared to manual counting (40.2% vs. 28.0%). Conclusion: Microscopic manual reticulocyte counting is a reliable method for evaluating reticulocyte counts in resource-constrained areas as it possesses the ability to effectively distinguish between high and low reticulocytes levels crucial for clinical decision-making.