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Review paper

Red blood cell distribution width as a predictor of outcome in Intensive Care Unit: a retrospective cohort study

By
Asmira Ljuca Orcid logo ,
Asmira Ljuca
Contact Asmira Ljuca

Department of Anaesthesiology, Resuscitation and Intensive Care Unit

Nermina Rizvanović ,
Nermina Rizvanović

Department of Anaesthesiology, Resuscitation and Intensive Care Unit

Senad Ljuca ,
Senad Ljuca

Department of Surgery, Cantonal Hospital Zenica , Zenica , Bosnia and Herzegovina

Alma Jahić
Alma Jahić

Department of Anaesthesiology, Resuscitation and Intensive Care Unit

Abstract

Aim
To evaluate the predictive significance of the red blood cell distribution width (RDW) >14.5 at admission to the Intensive
Care Unit (ICU) on outcome parameters: length of hospital stay (LOHS), incidence of hospital mortality, 30-day mortality and 30-day survival after hospital discharge in unselected (surgical and non-surgical) critically ill patients.
Methods
A total of 325 surgical and non-surgical critically ill patients were divided based on the RDW value at admission to the
ICU into two groups: Group 1 (RDW >14.5) and Group 2 (RDW≤14.5). Demographic and clinical parameters, laboratory findings, treatment and outcome parameters were compared between the groups. The predictive significance of RDW>14.5 on outcome parameters was analysed using linear regression analysis and univariate and multivariate logistic regression analysis, as appropriate.
Results
In Group 1, LOHS was higher (19.77±15.15; p<0.000) as was the prevalence of hospital mortality (46.6%; p<0.0523),
while 30-day survival after hospital discharge was lower (52.9%; p>0.026) compared to Group 2. RDW >14.5 was positively linearly related (r=0.64; r2=0.40; p=0.000) with LOHS. RDW >14.5 predicted the prevalence of in-hospital mortality with a 73.7% positive predictive value (AUC 0.62; sensitivity 70.1%; specificity 59.5%; p<0.05) and 30-day survival after hospital discharge with a 34.5% negative predictive value (AUC 0.45; sensitivity 58.3%;
specificity 68.7%; p<0.05).
Conclusions
RDW value >14.5 at admission to the ICU can predict prolonged hospital stay, higher mortality and lower survival
rate. RDW >14.5 may be an inexpensive and widely available early warning to redirect diagnostic and therapeutic decisions and improve outcomes.

References

1.
Salvagno GL, Sanchis-Gomar F, Picanza A, Lippi G. Red blood cell distribution width: A simple parametar with multiple clinical applications. Crit Rev Clin Lab Sci. 2015;52:86–105.
2.
McPherson R, Pincus M. Henry’s Clinical Diagnosis and Management by Laboratory Methods. 2021.
3.
Montagnana M, Cervellin G, Meschi T, Lippi G. The role of red blood cell distribution width in cardiovascular and thrombotic disorders. Clin Chem Lab Med. 2011;50:635–41.
4.
Pan J, Borné Y, Engström G. The relationship between red cell distribution width and all-cause and cause-specific mortality in a general population. Sci Rep. 2019;9(16208).
5.
Wang F, Pan W, Pan S, Ge J, Wang S, Chen M. Red cell distribution width as a novel predictor of mortality in ICU patients. Ann Med. 2010;43:40–6.
6.
Bazick HS, Chang D, Muhadavappa K, Gibbons FK, Christopher KB. Red cell distribution width and allcauses mortality in critically ill patients. Critical Care Med. 2011;39:1913–21.
7.
Zhang FX, Li ZL, Zhang ZD, Ma XC. Prognostic value of red blood cell distribution width for severe acute pancreatitis. World J Gastroenterol. 2019;25:4739–48.
8.
Jia L, Cui S, Yang J, Jia Q, Hao L, Jia R, et al. Red blood cell distribution width predicts long-term mortality in critically ill patients with acute kidney injury: a retrospective database study. Sci Rep. 2020;10:4563–73.
9.
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 Res Int. 2019;1942078.
10.
Hoffmann JJ, Nabbe KC, Broek NM. Effect of age and gender on reference intervals of red blood cell distribution width (RDW. 53(2015):19.
11.
Kim KM, Lui LY, Browner WS, Cauley JA, Ensrud KE, Kado DM, et al. Association between variation in red cell size and multiple aging-related outcomes. J Gerontol A Biol Sci Med Sci. 2021;76:1288–94.
12.
Pilling LC, Atkins JL, Duff MO, Beaumont RN, Jones SE, Tyrrell J, et al. Red blood cell distribution width: genetic evidence for aging pathways in 116,666 volunteers. PLoS One. 2018;12:e0185083.
13.
Yan Z, Fan Y, Meng Z, Huang C, Liu M, Zhang Q, et al. The relationship between red blood cell distribution width and metabolic syndrome in elderly Chinese: a cross-sectional study. Lipids Health Dis. 2019;18(34).
14.
Li Q, Chen X, Han B. Red blood cell distribution width is associated with frailty in older inpatients in China: Sex differences in a cross-sectional study. Exp Gerontol. 2021;150(111392).
15.
Paulson RF, Shi L, Wu DC. Stress erythropoiesis: new signals and new stress progenitor cells. Curr Opin Hematol. 2011;18:139–45.
16.
Marzetti E, Picca A, Marini F, Biancolillo A, CoelhoJunior HJ, Gervasoni J, et al. Inflammatory signatures in older persons with physical frailty and sarcopenia: the frailty “cytokinome” at its core. Exp Gerontol. 2019;122:129–38.
17.
Lippi G, Turcato G, Cervellin G, Sanchis-Gomar F. Red blood cell distribution width in heart failure: a narrative review. World J Cardiol. 2018;10:6–14.
18.
Subramani K, Raju SP, Chu X, Warren M, Pandya CD, Hoda N, et al. Effect of plasma-derived extracellular vesicles on erythrocyte deformability in polymicrobial sepsis. Int Immunopharmacol. 2018;65:244–7.
19.
Kato H, Ishida J, Imagawa S. Enhanced erythropoiesis mediated by activation of the reninangiotensin system via angiotensin II type 1a receptor. FASEB J. 2005;19:2023–5.
20.
Hu Y, Liu H, Fu S, Wan J, Li X. Red Blood cell distribution width is an independent predictor of AKI and mortality in patients in the coronary care unit. Vol. 42. 2017.
21.
Freeman AM, Rai M, Morando DW. Anemia Screening. 2023;
22.
Forhecz Z, Gombos T, Borgulya G, Pozsonyi Z, Prohaszka Z, Janoskuti L. Red cell distribution width in heart failure: prediction of clinical events and relationship with markers of ineffective erythropoiesis, inflammation, renal function, and nutritional state. Am Heart J. 2009;158:659–66.
23.
Kellum JA, N L, KDIGO AKI Guideline Work Group. Diagnosis, evaluation, and management of acute kidney injury: a KDIGO summary (Part 1. Crit Care. 2013;17(204).
24.
Fuller BM, Dellinger RP. Lactate as a hemodynamic marker in the critically ill. Curr Opin Crit Care. 2012;18:267–72.
25.
Otero TMN, Yeh DD, Bajwa EK, Azocar RJ, Tsai AL, Belcher DM, et al. Elevated red cell distribution width is associated with decreased ventilator-free days in critically ill patients. J Intensive Care Med. 2018;33:241–7.
26.
Zhang L, Yu C, Guo K, Huang C, Mo L. Prognostic role of red blood cell distribution width in patients with sepsis: a systematic review and meta-analysis. BMC Immunol. 2020;21(40).
27.
Wagner DP, Draper EA. Acute physiology and chronic health evaluation (APACHE II) and Medicare reimbursement. Health Care Financ Rev. 1984;Suppl(Suppl):91-105.
28.
Vincent JL, Moreno R, Takala J, Willatts S, Mendonça A, Bruining H, et al. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. In: On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine Intensive Care Med. 1996. p. 707–10.

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