The early detection of anaemia and aetiology prediction through the modelling of red cell distribution width (RDW) in cross-sectional community patient data

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Abstract

Background: Red cell distribution width (RDW) is a marker of iron-deficient anaemia that can also assist differentiation of other anaemias. RDW also has been suggested as an effective marker for earlier anaemia detection. The RDWanaemia relationship was investigated in cross-sectional community patient data, and the capacity of RDW to predict the diagnostic value of second tier anaemia markers assessed. Methods: Routine and second tier assay data were provided by the laboratory Sullivan Nicolaides Pathology. The cohort was divided into male and female groups stratified by age, and correlation analyses assessed associations of RDW to haemoglobin and ferritin. Analysis of covariance (ANCOVA) was performed for both routine and second tier markers to investigate their significance for RDW prediction. Results: RDW had statistically significant negative correlation with haemoglobin for both sexes and age ranges (p<0.01). The RDW relationship with serum ferritin was non-linear, representing two populations. ANCOVA showed categorical ferritin as a significant RDW predictor for younger females, with vitamin B12 a significant RDW predictor for older men. Haemoglobin, mean corpuscular haemoglobin (MCH) and second tier iron markers (e.g., transferrin) were significant RDW predictors for both sexes and ages investigated. An individual longitudinal female case study showed RDW as very sensitive to haemoglobin decrease, with ferritin not as responsive. Conclusions: RDW had a significant negative association with haemoglobin in cross-sectional community patient data. ANCOVA showed ferritin as a significant RDW predictor for younger females only. This study confirms the utility of RDW as a marker for early anaemia detection, and useful to accelerated diagnoses of anaemia aetiology.

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Badrick, T., Richardson, A. M., Arnott, A., & Lidbury, B. A. (2015). The early detection of anaemia and aetiology prediction through the modelling of red cell distribution width (RDW) in cross-sectional community patient data. Diagnosis, 2(3), 171–179. https://doi.org/10.1515/dx-2015-0010

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