Red cell distribution width as a predictor for the severity of coronavirus disease 2019 infection in hospitalized patients: a retrospective study

Abstract

Background
Red cell distribution width (RDW) has recently gained attention as a potential predictor of coronavirus disease 2019 (COVID-19) severity. RDW, routinely reported in complete blood counts, reflects the degree of anisocytosis, indicating variability in red blood cell size.


Aim
To investigate the association between RDW and other hematological indices and the severity of COVID-19 infection among hospitalized patients.


Patients and methods
This study analyzes clinical data from 261 patients diagnosed with COVID-19 between June 2020 and December 2022 at COVID-19 isolation facilities in Sohag Governorate, Egypt, excluding patients with pre-existing hematological disorders. Comprehensive data collection included demographic information, symptomatology, and laboratory results, with a focus on complete blood count parameters, serum biochemistry, and coagulation markers. The study classified COVID-19 severity based on respiratory rate, oxygen saturation, and the partial pressure of oxygen to the fractional concentration of inspired oxygen ratio, aiming to correlate these with hematological markers.


Results

RDW exhibits a moderate positive correlation with C-reactive protein (
r
=0.331,
P
<0.001) and erythrocyte sedimentation rate (
r
=0.243,
P
<0.001). Univariate logistic regression: RDW significantly associated with severe COVID-19 [
P
<0.001, odds ratio (OR)= 5.356, 95% confidence interval (CI)=2.457–11.675). Multivariate logistic regression: RDW is an independent predictor of severity, with elevated RDW patients nearly nine times more likely to develop severe disease (
P
<0.001, OR=8.998, 95% CI=3.620–22.365). Diagnostic validity (receiver operating characteristic analysis): using a cutoff of 13.9, RDW has an area under the curve=0.651, sensitivity 62.5%, specificity 64.8%, positive predictive value 65.9%, and negative predictive value 61.4% (
P
<0.001).



Conclusion
By focusing on RDW, an inexpensive and routinely measured parameter, this study provides a practical tool for early risk stratification, potentially guiding timely interventions and improving patient management. Integrating RDW with clinical observations and other hematological markers may enhance the prediction of severe COVID-19, ultimately contributing to a reduction in morbidity and mortality.