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. 2020 Sep 1;3(9):e2022058.
doi: 10.1001/jamanetworkopen.2020.22058.

Association of Red Blood Cell Distribution Width With Mortality Risk in Hospitalized Adults With SARS-CoV-2 Infection

Affiliations

Association of Red Blood Cell Distribution Width With Mortality Risk in Hospitalized Adults With SARS-CoV-2 Infection

Brody H Foy et al. JAMA Netw Open. .

Abstract

Importance: Coronavirus disease 2019 (COVID-19) is an acute respiratory illness with a high rate of hospitalization and mortality. Biomarkers are urgently needed for patient risk stratification. Red blood cell distribution width (RDW), a component of complete blood counts that reflects cellular volume variation, has been shown to be associated with elevated risk for morbidity and mortality in a wide range of diseases.

Objective: To investigate whether an association between mortality risk and elevated RDW at hospital admission and during hospitalization exists in patients with COVID-19.

Design, setting, and participants: This cohort study included adults diagnosed with SARS-CoV-2 infection and admitted to 1 of 4 hospitals in the Boston, Massachusetts area (Massachusetts General Hospital, Brigham and Women's Hospital, North Shore Medical Center, and Newton-Wellesley Hospital) between March 4, 2020, and April 28, 2020.

Main outcomes and measures: The main outcome was patient survival during hospitalization. Measures included RDW at admission and during hospitalization, with an elevated RDW defined as greater than 14.5%. Relative risk (RR) of mortality was estimated by dividing the mortality of those with an elevated RDW by the mortality of those without an elevated RDW. Mortality hazard ratios (HRs) and 95% CIs were estimated using a Cox proportional hazards model.

Results: A total of 1641 patients were included in the study (mean [SD] age, 62[18] years; 886 men [54%]; 740 White individuals [45%] and 497 Hispanic individuals [30%]; 276 nonsurvivors [17%]). Elevated RDW (>14.5%) was associated with an increased mortality risk in patients of all ages. The RR for the entire cohort was 2.73, with a mortality rate of 11% in patients with normal RDW (1173) and 31% in those with an elevated RDW (468). The RR in patients younger than 50 years was 5.25 (normal RDW, 1% [n = 341]; elevated RDW, 8% [n = 65]); 2.90 in the 50- to 59-year age group (normal RDW, 8% [n = 256]; elevated RDW, 24% [n = 63]); 3.96 in the 60- to 69-year age group (normal RDW, 8% [n = 226]; elevated RDW, 30% [104]); 1.45 in the 70- to 79-year age group (normal RDW, 23% [n = 182]; elevated RDW, 33% [n = 113]); and 1.59 in those ≥80 years (normal RDW, 29% [n = 168]; elevated RDW, 46% [n = 123]). RDW was associated with mortality risk in Cox proportional hazards models adjusted for age, D-dimer (dimerized plasmin fragment D) level, absolute lymphocyte count, and common comorbidities such as diabetes and hypertension (hazard ratio of 1.09 per 0.5% RDW increase and 2.01 for an RDW >14.5% vs ≤14.5%; P < .001). Patients whose RDW increased during hospitalization had higher mortality compared with those whose RDW did not change; for those with normal RDW, mortality increased from 6% to 24%, and for those with an elevated RDW at admission, mortality increased from 22% to 40%.

Conclusions and relevance: Elevated RDW at the time of hospital admission and an increase in RDW during hospitalization were associated with increased mortality risk for patients with COVID-19 who received treatment at 4 hospitals in a large academic medical center network.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Westover reported grants from the National Institutes of Health during the conduct of the study. Dr Aguirre reported grants from the CRICO Risk Management Foundation during the conduct of the study. Dr Higgins reported grants from the One Brave Idea Initiative and grants from Fast Grants at the Mercatus Center, George Mason University during the conduct of the study. No other disclosures were reported.

Figures

Figure 1.
Figure 1.. Elevated Red Blood Cell Distribution Width (RDW) at Hospital Admission and Mortality Among Patients With Coronavirus Disease 2019
Across all age groups, an RDW greater than 14.5% measured at the time of admission was associated with a 31% mortality compared with an 11% mortality for patients whose RDW at admission was ≤14.5%. All increases in mortality are statistically significant except in the 70- to 80-year age group. Table 2 details age-stratified and RDW-stratified mortality rates.
Figure 2.
Figure 2.. Cox Proportional Hazards Modeling of Mortality Risk
Models of mortality adjusted for age, race, ethnicity, red blood cell distribution width (RDW), absolute lymphocyte count, and D-dimer (dimerized plasmin fragment D) level are given for the multivariate (A) and univariate (B) analyses. Variables were coded as either continuous (A and B) or discrete (C and D) using the following thresholds: age older than 70 years, RDW >14.5%, lymphocyte count <0.8 × 109/L, and D-dimer level greater than 1500 ng/L, which provided similar proportions of abnormality in the cohort (33%, 29%, 27%, and 28%, respectively, for age, RDW, lymphocyte count, and D-dimer level). Race was coded as 1 for Black/African American, and 0 for all other groups. Ethnicity was coded as 1 for Hispanic, and 0 for non-Hispanic/unknown. For continuous models, changes in variables were normalized as follows: age increase of 10 years, RDW increase of 0.5%, D-dimer level increase of 100 ng/L, and a lymphocyte count decrease of 0.1 103 ×109/L.
Figure 3.
Figure 3.. Red Blood Cell Distribution Width (RDW) Increase After Admission and Mortality Risk Among Patients With Coronavirus Disease 2019
A, Stratifying patients based on admission RDW and mortality reveals that, among patients with an RDW of 14.5% or less at admission, those who do not survive have an average RDW increase of 1.5% during their first week of hospitalization, a significantly larger RDW increase than in all other groups. Shading represents the 95% CI. B, Among patients with an RDW of 14.5% or less at admission, those with an increase of more than 0.5% in RDW between admission and discharge had a 24% (95% CI, 18%-30%) mortality rate compared to 6% (95% CI, 4%-8%) for those with stable RDW (≥−0.5% and ≤0.5%). Among patients with elevated RDW at admission, a further increase in RDW during admission was associated with a mortality rate of 40% (95% CI, 33%-47%), and a stable elevated RDW was associated with a mortality rate of 22% (95% CI, 18%-26%). C, A histogram of RDW change in survivors and nonsurvivors of coronavirus disease 2019 shows that nonsurvivors were more likely than survivors to experience an RDW increase during hospitalization. Change in RDW is reported in percentage points. For instance, a change in RDW from 14.0% to 15.0% is reported as 1.0%.

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References

    1. Wang D, Hu B, Hu C, et al. . Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA. 2020;323(11):1061-1069. doi:10.1001/jama.2020.1585 - DOI - PMC - PubMed
    1. Grasselli G, Zangrillo A, Zanella A, et al. ; COVID-19 Lombardy ICU Network . Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy region, Italy. JAMA. 2020;323(16):1574-1581. doi:10.1001/jama.2020.5394 - DOI - PMC - PubMed
    1. Guan WJ, Ni ZY, Hu Y, et al. ; China Medical Treatment Expert Group for Covid-19 . Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020;382(18):1708-1720. doi:10.1056/NEJMoa2002032 - DOI - PMC - PubMed
    1. Zhou F, Yu T, Du R, et al. . Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395(10229):1054-1062. doi:10.1016/S0140-6736(20)30566-3 - DOI - PMC - PubMed
    1. Malka R, Delgado FF, Manalis SR, Higgins JM. In vivo volume and hemoglobin dynamics of human red blood cells. PLoS Comput Biol. 2014;10(10):e1003839. doi:10.1371/journal.pcbi.1003839 - DOI - PMC - PubMed

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