Abstract Background Red Cell Distribution Width (RDW) is a routinely available parameter on automated haematology analysers. This parameter is often used to help in the diagnosis of iron deficiency anaemia. RDW quantitatively measures the degree of anisocytosis of the red blood cells. The more common way of reporting RDW is RDW-CV, which is based on the coefficient of variation of the red blood cell distribution volume and is calculated using mean red cell volume. RDW can also be presented as RDW-SD, which is a direct measurement of the width of the red blood cell distribution curve and is not influenced by mean red cell volume. Conventionally, laboratories report RDW-CV as part of the red blood cell indices in full blood count (FBC) reports. However, it has been proposed that RDW-SD is a better indicator of iron deficiency anaemia compared to RDW-CV. The authors seek to review and assess the clinical utility of both RDW measurements in patients with iron deficiency anaemia in an acute care hospital in Singapore. Methods RDW data of samples from 271 unique individuals from Sysmex XN-9000 (Sysmex, Japan) automated haematology analysers over a period of two months were reviewed. These individuals were selected as they had plasma iron measured in the same blood collection. The individuals were sorted into two groups based on the plasma iron measurement: with iron deficiency (80%) and without iron deficiency (20%). The correlation of RDW-CV and RDW-SD with the plasma iron concentration of the individuals was studied. The RDW-CV reference range used were established for the local population by an in-house reference range validation study while that of the RDW-SD is from a recent Participant Summary Report for a College of American Pathologists (CAP) Hematology Automated Differential survey (FH9-B 2022). The sensitivity, specificity, predictive values, and overall efficiency of RDW-CV and RDW-SD were calculated and compared using the data collected. Results The sensitivity and specificity of RDW-CV in detecting iron deficiency anaemia are 45.2% and 68.5%. The positive and negative predictive values for RDW-CV are 85.2% and 23.7% respectively. The sensitivity and specificity of RDW-SD in detecting iron deficiency are 33.2% and 64.8%. The positive and negative predictive value of RDW-SD are 79.1% and 19.4% respectively. The overall efficiency of RDW-CV is 49.8%, significantly higher than 39.4% of RDW-SD. Conclusion This retrospective study suggested that RDW-CV is still a better blood cell index than RDW-SD in the differential diagnosis of iron deficiency anaemia in a predominantly Asian population. However, the use of RDW-SD reference range that is appropriate for the local population may improve the clinical utility of the RDW-SD.
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