Study of peripheral blood smear findings in patients of anemia and to compare it with automated hematology analyzer generated red cell parameters

Abstract

Introduction: Anemia is one of the common medical conditions prevalent in our society. The correct categorization of varying types of anemia is essential for therapeutic purposes. Various laboratory tests are done to find out its underlying cause, but peripheral smear (PS) study of red blood cells (RBCs) morphology is important along with study of red blood cell indices in the classification of anemia.

Objectives: This study was done to evaluate RBC morphology on peripheral smear examination in patients of anemia and to compare these findings with cell counter generated red blood cells indices comprising of Mean corpuscular volume (MCV), Mean corpuscular hemoglobin concentration (MCHC) and Mean corpuscular hemoglobin (MCH)

Methodology: Red blood cell morphology on peripheral blood smear was studied in 350 patients of anemia irrespective of age and gender received under six months duration  from 1st January 2019 to 30 th June 2019 and  findings  were compared with  cell counter generated  red cell parameters generated by automated  hematology analyzer.

Results: Most common anemia seen on smear examination was microcytic hypochromic anemia which accounted for 210 (60%) cases followed by dimorphic anemia in 73 (20.86%) cases. Most of the patients were female, comprising of 227 (64.85%) cases. Highest numbers of patient were in the age group of 21-30 years (20.30%). Sensitivity of MCV was 78%, MCHC was 14% and MCH was 80% in detection of microcytic hypochromic anemia. The sensitivity of MCV and MCH was found to be 100 %  in detection of macrocytic anemia. Sensitivity of MCHC was only 10% for detection of macrocytic anemia. The sensitivity of MCV, MCHC and MCH was 78%, 100% and 67 % respectively in detection of normocytic normochromic anemia. 

Conclusion: The peripheral smear examination should always be interpreted along with the red blood cell indices generated by an automated analyzer in order to classify various types of anemia.