Pattern-Based Interpretation of Complete Blood Count: A Case Series and Diagnostic Framework for Common Hematologic Presentations

Objective : This study examines the diagnostic relevance of Complete Blood Count (CBC) parameters across 21 anonymized patient cases. Methods : A retrospective, qualitative case series analysis was conducted using clinical CBC profiles alongside supporting biochemical tests. Each case was assessed for hematological abnormalities and correlated with clinical history and laboratory findings. Results : An interpretive diagnostic algorithm was developed based on pattern recognition across red cell indices, WBC profiles, platelet trends, and biochemical markers. Distinct patterns of anemia (microcytic, macrocytic, normocytic), leukemoid reactions, and pancytopenia were identified. Key findings include underrecognized megaloblastic anemia in vegetarians, leukemic profiles in elderly patients, and rare reticulocyte response deviations. Discussion : Pattern recognition in CBC interpretation enables early identification of critical conditions such as leukemia, marrow suppression, and nutritional deficiencies. A structured, algorithmic approach improves diagnostic accuracy, particularly when supported by reticulocyte indices, LDH, CRP, and vitamin status. Conclusion : CBC remains a cornerstone of diagnostic workups. Integrating red cell indices, platelet counts, and WBC differentials with clinical context improves diagnostic accuracy and guides timely intervention.