The Association of Red Blood Cell Distribution Width with Secondary Infection and Prognosis in hospitalized patients with COVID -19 pneumonia

Document Type : Original Article


1 Internal Medicine, Department of Internal Medicine, Faculty of Medicine, Mashhad University of Medical Science, Mashhad, Iran.

2 Department of Hematology Oncology, Mashhad University of Medical Science, Mashhad, Iran

3 Internist, Department of Internal Medicine, Mashhad University of Medical Science, Mashhad, Iran

4 Pulmonologist, Lung Diseases Research, Mashhad University of medical science, Mashhad, Iran

5 Department of Internal Medicine, Mashhad University of Medical Science, Mashhad, Iran

6 Clinical Research Unit, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran

7 Pulmonologist, Lung Diseases Research Center, Mashhad University of Medical Science, Mashhad, Iran


Introduction: Novel Coronavirus outbreak has posed a global threat. While the infection appears to be mild in most patients, considering its high rate of transmission, a large number of people are at risk of developing severe to critical illness in total which makes prognosis studies a priority.The aim of the present study was to evaluate red blood cell distribution width (RDW) as a predictive factor for diagnosing severe cases of coronavirus disease 2019 (COVID-19).
Materials and Methods: A total number of 204 inpatients diagnosed with COVID-19 including 122 men and 82 women (Mean age: 58.83±15.93 years old) treated at Imam Reza Hospital, Mashhad, Iran were included in the study. Patients were divided into severe and moderate groups according to their clinical signs and examinations and pulmonary imaging features. Demographic Data, laboratory test results, treatments, patients’ complications and outcome were recorded. Mann-Whitney U test and spearman correlation coefficient (r) were performed to assess RDW correlation with severity and serious complications in patients including intensive care unit (ICU) admission, shock, secondary infections, intubation, length of hospitalization and death. Receiver operating characteristics (ROC) curves analysis was carried out to define the reliability of RDW as a predictive indicator in severe COVID-19.
Results: The results showed statistical significant correlations between high levels of RDW and developing secondary infections and longer hospitalization (P values ≤0.001). The optimal cutoff for RDW to predict the length of hospitalization (≤ 7 days or more than 7 days) was estimated to be 14.65% with 94% sensitivity and 71.3% specificity. The area under curve was calculated to be 0.895 through Roc curve analysis.
Conclusion: High predictive value of RDW, a routine blood test parameter, could be used in diagnosing COVID-19 patients at higher risk for developing secondary infections and longer hospital stay which in turn helps with better management of the disease.


1.             Yin Y, Wunderink RG. MERS, SARS and other coronaviruses as causes of pneumonia. Respirology. 2018;23(2):130-7.
2.             Drosten C, Günther S, Preiser W, Van Der Werf S, Brodt H-R, Becker S, et al. Identification of a novel coronavirus in patients with severe acute respiratory syndrome. New England journal of medicine. 2003;348(20):1967-76.
3.             Zaki AM, Van Boheemen S, Bestebroer TM, Osterhaus AD, Fouchier RA. Isolation of a novel coronavirus from a man with pneumonia in Saudi Arabia. New England Journal of Medicine. 2012;367(19):1814-20.
4.             Attaran, D., Ataei Azimi, S., M.Lari, S., Rokni, H., Taghavi, M., Maraashi, M. The Evaluation of Pulmonary Function Tests in Patients with Polycystic Ovary Syndrome. Journal of Cardio-Thoracic Medicine, 2013; 1(3): 84-88
5.             Kuiken T, Fouchier RA, Schutten M, Rimmelzwaan GF, Van Amerongen G, van Riel D, et al. Newly discovered coronavirus as the primary cause of severe acute respiratory syndrome. The Lancet. 2003;362(9380):263-70.
6.             de Groot RJ, Baker SC, Baric RS, Brown CS, Drosten C, Enjuanes L, et al. Commentary: Middle East respiratory syndrome coronavirus (MERS-CoV): announcement of the Coronavirus Study Group. Journal of virology. 2013;87(14):7790-2.
7.             Qu R, Ling Y, Zhang Yh, Wei Ly, Chen X, Li X, et al. Platelet‐to‐lymphocyte ratio is associated with prognosis in patients with Corona Virus Disease‐19. Journal of Medical Virology. 2020.
8.             Beigoli S, Sharifi Rad A, Askari A, Assaran Darban R, Chamani J. Isothermal titration calorimetry and stopped flow circular dichroism investigations of the interaction between lomefloxacin and human serum albumin in the presence of amino acids. 2019;37(9):2265-2282.
9.             Lu R, Zhao X, Li J, Niu P, Yang B, Wu H, et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. The Lancet. 2020;395(10224):565-74.
10.          Phelan A, Katz R, Gostin L. The novel coronavirus originating in wuhan. China, J Am Med Assoc. 2020.
11.          Gorbalenya A, Baker S, Baric R. Severe acute respiratory syndrome-related coronavirus: the species and its viruses–a statement of the coronavirus study group. bioRxiv preprint first posted online February 11, 2020. 2020: 2020.2002. 2007.937862. doi: 10.1101/2020.02. 07.937862. Accessed February. 2020;12.
12.          Holshue ML, DeBolt C, Lindquist S, Lofy KH, Wiesman J, Bruce H, et al. First case of 2019 novel coronavirus in the United States. New England Journal of Medicine. 2020.
13.          Chamani j. Energetic domains analysis of bovine α-lactalbumin upon interaction with copper and dodecyl trimethylammonium bromide. Journal of Molecular Structure. 2010;979(1-3):227-234.
14.          Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. The Lancet. 2020.
15.          Feng Z, Yu Q, Yao S, Luo L, Duan J, Yan Z, et al. Early Prediction of Disease Progression in 2019 Novel Coronavirus Pneumonia Patients Outside Wuhan with CT and Clinical Characteristics. medRxiv. 2020.
16.          Guan W-j, Chen R-c, Zhong N-s. Strategies for the prevention and management of coronavirus disease 2019. Eur Respiratory Soc; 2020.
17.          Coronavirus disease 2019 (COVID-19) Situation Report – 87 2020 [Available from:
18.          Guan W-j, Ni Z-y, Hu Y, Liang W-h, Ou C-q, He J-x, et al. Clinical characteristics of 2019 novel coronavirus infection in China. MedRxiv. 2020.
19.          Gong J, Ou J, Qiu X, Jie Y, Chen Y, Yuan L, et al. A Tool to Early Predict Severe 2019-Novel Coronavirus Pneumonia (COVID-19): A Multicenter Study using the Risk Nomogram in Wuhan and Guangdong, China. medRxiv. 2020.
20.          Liu J, Liu Y, Xiang P, Pu L, Xiong H, Li C, et al. Neutrophil-to-lymphocyte ratio predicts severe illness patients with 2019 novel coronavirus in the early stage. MedRxiv. 2020.
21.          de Gonzalo-Calvo D, de Luxán-Delgado B, Rodríguez-González S, García-Macia M, Suárez FM, Solano JJ, et al. Interleukin 6, soluble tumor necrosis factor receptor I and red blood cell distribution width as biological markers of functional dependence in an elderly population: a translational approach. Cytokine. 2012;58(2):193-8.
22.          Arbel Y, Weitzman D, Raz R, Steinvil A, Zeltser D, Berliner S, et al. Red blood cell distribution width and the risk of cardiovascular morbidity and all-cause mortality. Thrombosis and haemostasis. 2014;112(02):300-7.
23.          Oh HJ, Park JT, Kim J-K, Yoo DE, Kim SJ, Han SH, et al. Red blood cell distribution width is an independent predictor of mortality in acute kidney injury patients treated with continuous renal replacement therapy. Nephrology Dialysis Transplantation. 2012;27(2):589-94.
24.          Engström G, Smith J, Persson M, Nilsson P, Melander O, Hedblad B. Red cell distribution width, haemoglobin A 1c and incidence of diabetes mellitus. Journal of internal medicine. 2014;276(2):174-83.
25.          Koma Y, Onishi A, Matsuoka H, Oda N, Yokota N, Matsumoto Y, et al. Increased red blood cell distribution width associates with cancer stage and prognosis in patients with lung cancer. PloS one. 2013;8(11).
26.          Ozgul G, Seyhan EC, Ozgul MA, Gunluoglu MZ. Red blood cell distribution width in patients with chronic obstructive pulmonary disease and healthy subjects. Archivos de Bronconeumología (English Edition). 2017;53(3):107-13.
27.          Wang B, Gong Y, Ying B, Cheng B. Relation between red cell distribution width and mortality in critically ill patients with acute respiratory distress syndrome. BioMed research international. 2019;2019.
28.          Nishimoto N. Interleukin‐6 as a therapeutic target in candidate inflammatory diseases. Clinical Pharmacology & Therapeutics. 2010;87(4):483-7.
29.          Mahindra A, Laubach J, Raje N, Munshi N, Richardson PG, Anderson K. Latest advances and current challenges in the treatment of multiple myeloma. Nature reviews Clinical oncology. 2012;9(3):135.
30.          Bazick HS, Chang D, Mahadevappa K, Gibbons FK, Christopher KB. Red cell distribution width and all cause mortality in critically ill patients. Critical care medicine. 2011;39(8):1913.
31.          Zhu M, Han M, Xiao X, Lu S, Guan Z, Song Y, et al. Dynamic Differences Of Red Cell Distribution Width Levels Contribute To The Differential Diagnosis Of Hepatitis B Virus-related Chronic Liver Diseases: A Case-control Study. International Journal of Medical Sciences. 2019;16(5):720.
32. Rezaeetalab, F., Mozdourian, M., Amini, M., Javidarabshahi, Z., Akbari, F. COVID-19: A New Virus as a Potential Rapidly Spreading in the Worldwide. Journal of Cardio-Thoracic Medicine, 2020; 8(1): 563-564