Comparison of Manual Versus Automated Complete Blood Count Parameters in Patients Attending Plateau Specialist Hospital, Jos, Nigeria

Abstract

Background: The complete blood count (CBC) is a fundamental laboratory investigation used in the diagnosis and monitoring of a wide range of clinical conditions. While automated hematology analyzers are increasingly adopted due to their speed and precision, manual methods remain widely used in resource-limited settings. Comparative evaluation of these methods is essential to ensure analytical reliability and clinical relevance. Objective: To compare complete blood count parameters obtained using manual hematological techniques with those generated by an automated hematology analyzer (ADVIA 120i) among patients attending Plateau Specialist Hospital, Jos, Nigeria. Methods: This cross-sectional, laboratory-based method-comparison study involved 50 adult patients requiring CBC testing. Venous blood samples were analyzed using both manual methods and an automated hematology analyzer. Parameters compared included RBC count, WBC count, hemoglobin concentration, hematocrit, platelet count, and red cell indices. Statistical analysis was performed using paired t-tests, Pearson correlation coefficients, and Bland–Altman agreement analysis, with significance set at p < 0.05. Results: There was no statistically significant difference between manual and automated methods for RBC count, hemoglobin concentration, hematocrit, and platelet count (p > 0.05). However, significant differences were observed for WBC count (p = 0.018) and mean corpuscular volume (p = 0.005). Strong positive correlations were demonstrated for all parameters (r = 0.91–0.99; p < 0.001). Bland–Altman analysis revealed minimal mean bias for most parameters, though wider limits of agreement were noted for platelet counts. Time-based analysis showed progressive instability of CBC parameters with delayed testing, more pronounced in manual methods. Conclusion: Manual and automated CBC methods show strong correlation and acceptable agreement for most hematological parameters. Automated analysis offers superior precision and consistency, while manual methods remain essential for quality control and morphological assessment. A combined approach is recommended to optimize diagnostic accuracy, particularly in resource-limited healthcare settings.