key: cord-0896268-naye8h20 authors: Lee, Jane J.; Montazerin, Sahar M.; Jamil, Adeel; Jamil, Umer; Marszalek, Jolanta; Chuang, Michael L.; Chi, Gerald title: Association between red blood cell distribution width and mortality and severity among patients with COVID‐19: A systematic review and meta‐analysis date: 2021-01-26 journal: J Med Virol DOI: 10.1002/jmv.26797 sha: 9f06614ed0d318c5515a1cc565dcc656f09ef32a doc_id: 896268 cord_uid: naye8h20 Emerging evidence has underscored the potential usefulness of red blood cell distribution width (RDW) measurement in predicting the mortality and disease severity of COVID‐19. This study aimed to assess the association of the plasma RDW levels with adverse prognosis in COVID‐19 patients. A comprehensive literature search from inception to September 2020 was performed to harvest original studies reporting RDW on admission and clinical outcomes among patients hospitalized with COVID‐19. RDW levels were compared between cases (patients who died or developed more severe symptoms) and controls (patients who survived or developed less severe symptoms). A total of 14,866 subjects from 10 studies were included in the meta‐analysis. Higher levels of RDW were associated with adverse outcomes in COVID‐19 patients (mean differences = 0.72; 95% CI = 0.47–0.97; I (2) = 89.51%). Deceased patients had higher levels of RDW compared to patients who survived (mean differences = 0.93; 95% CI = 0.63–1.23; I (2) = 85.58%). Severely ill COVID‐19 patients showed higher levels of RDW, as opposed to patients classified to have milder symptoms (mean differences = 0.61; 95% CI = 0.28–0.94; I (2) = 82.18%). Elevated RDW levels were associated with adverse outcomes in COVID‐19 patients. This finding warrants further research on whether RDW could be utilized as a simple and reliable biomarker for predicting COVID‐19 severity and whether RDW is mechanistically linked with COVID‐19 pathophysiology. dividing the standard deviation (SD) of corpuscular volume by the mean corpuscular volume, is a commonly used measure to quantify the variation of individual RBC volumes as it circulates during the approximate lifespan of 115 days. 4 An increase in RDW can be attributed to several factors. First, increased RDW may reflect an imbalance between hematopoiesis and RBC survival. 5 Specifically, delayed clearance of senescent RBCs from the circulation leading to RBC underproduction, resulting in an increase in the plasma levels of RDW. 5, 6 Second, elevated RDW may suggest an underlying inflammation through multiple mechanisms. For instance, proinflammatory cytokines, such as interferon γ and tumor necrosis factor α, may affect iron metabolism and the capacity of RBC production by the bone marrow, which leads to anemia and increased RDW. 7 Alternatively, RDW may increase due to shortened RBC lifespan and premature release of RBCs from the bone marrow in the presence of increased oxidative stress associated with inflammation. 8 Third, RDW could also increase in other physiologic events, such as aging, pregnancy, or following erythropoietin stimulation and exercise. 1 In practice, elevated RDW levels are utilized as a diagnostic tool for differentiating an early stage of nutritional deficiency or megaloblastic anemias from thalassemia. The potential value of RDW as a rapid and easy prognostic tool among high-risk patients, if effective, will vastly benefit timely intervention because RDW levels are measured as part of routine measures of complete blood count (CBC) by automated instruments in hematology laboratories. In the precoronavirus disease 2019 (COVID-19) era, a large-scale prospective cohort study indicated that RDW was a predictor for all-cause mortality independent of the presence of inflammation. 9 Nevertheless, inflammation may, at least in part, interact with the association of RDW with mortality. In the context of the COVID-19 pandemic, emerging evidence supports the usefulness of biomarkers (e.g., C-reactive protein, troponin, D-dimer) in predicting mortality, disease severity, or thrombotic complications among patients hospitalized for COVID-19. 10, 11 However, the association of RDW with adverse prognosis in COVID-19 has not been well-established. The current meta-analysis aimed to review and synthesize the current evidence on the association of RDW levels with COVID-19 mortality and severity. We hypothesized that among patients with laboratory-confirmed COVID-19 infection, those who died or were severely ill would have higher levels of RDW compared to those who survived or were mildly ill. This study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, and the protocol was registered in PROSPERO (registration number: CRD42020211560). 12 A systematic literature search was performed in PubMed, supplemented by a hand search of references from relevant publications, to collect eligible studies from inception to September 2020. The search for identifying qualifying studies was initiated by constructing sets of relevant keywords (i.e., and their synonyms. These search terms were expanded and organized in thematic building blocks, as provided in Table S1 . To be included in the meta-analysis, published studies needed to be (1) conducted in human subjects, (2) original research articles (including letters and abstracts), (3) reported RDW levels in COVID-19 patients, where there were two or more groups of patients with mortality status (i.e., deceased or survived) or severity (e.g., mild, moderate, or severe cases of COVID- 19) , and (4) published in English. Nonoriginal publications (e.g., narrative review, systematic review, meta-analysis, editorial) and studies that did not report RDW or adverse outcomes in COVID-19 patients were excluded. Reference lists of relevant studies and review articles were screened for potentially eligible studies. Additional searches were performed in medRxiv to identify preprints (i.e., preliminary reports of work that have not been certified by peer review) that were qualified for the analysis. 13 Duplicated publications were removed after confirming identical publication information. Marszalek) assessed the quality of the included studies in accordance with the Newcastle-Ottawa Scale. Disagreement in the quality assessment was resolved by discussion and consensus. The quality assessment criteria and scores are provided in Tables S2 and S3. The study endpoint was adverse clinical outcomes, defined as the composite of mortality or severe COVID-19. If a study classified patients into three groups (i.e., mild, moderate, and severe) based on the clinical severity of COVID-19, the group with the most severe symptoms was compared with the group with the mildest symptoms. The coefficient of variation of RDW, expressed as percentages were assessed upon hospital admission as part of the standard complete blood test from each study for assessment of association with adverse clinical outcomes. The statistical analysis for this meta-analysis included primary and subgroup analyses. The primary analysis was performed to compare the mean levels of RDW between cases (patients with adverse outcomes, defined as those who died or developed more severe symptoms) and controls (patients without adverse outcomes, defined as those who survived or developed less severe symptoms). In the subgroup analyses, the difference in RDW levels was calculated by comparison between (1) RDW levels were uniformly expressed in percentage for all included studies. For analysis purposes, RDW levels reported in median and 25th and 75th percentiles were converted to mean and SD. 14 For each study, the mean level of RDW was used as an effect size statistic, and the inverse variance of the mean RDW levels was used as study weight. Confidence intervals (CIs) of RDW levels were calculated by normal approximation. The summary effect size was then computed by fitting a random-effects model using the DerSimonian and Laird method. 15 Heterogeneity across the studies was assessed using the Cochran's Q test (with the threshold of p < .10, indicating the presence of heterogeneity) and I 2 statistic (I 2 > 50%: significant heterogeneity; I 2 ≤ 50%: insignificant heterogeneity). Funnel plots were used for visual inspection of publication bias, and the Egger test was used for detecting small-study effect for endpoints with a study number of 10 or more. 16 All the analysis was performed using the metan and metaninf packages in the STATA software of version 16.1 (Stata Corporation). A total of 14,866 subjects from 10 studies were included in the metaanalysis. Summary of study characteristics and patient characteristics were provided in Tables 1 and 2 . [17] [18] [19] [20] [21] [22] [23] [24] [25] The mean age ranged from 38 to 77 years. The proportion of males ranged from 42.4% to 69.2%. The status of CAD, hypertension, and diabetes ranged from 0% to 28%, 2.9%-68.8%, and 5.7%-70.6%, respectively. The majority of the included studies were retrospective and observational. The quality of the studies was generally high, with scores ranging from 6 to 9, as evaluated with the Newcastle-Ottawa Scale (Tables S2 and S3 ). Higher levels of RDW were significantly associated with severely ill COVID-19 patients (pooled mean differences: 0.72; 95% CI, 0.47 to 0.97; Figure 2 ). The I 2 value of 89.51% suggested the existence of heterogeneity. No sign of publication bias was detected based on visual inspection of the funnel plot, which was symmetrically shaped ( Figure 3 ). No small-study effect was observed, as determined by Figure S1 ). Results of the subgroup analysis on the associations with two subsets of the study participants (mortality and COVID-19 severity) are shown in Figure 4 . which are required for effective hematopoiesis. 19 Lastly, bone marrow suppression or destruction has also been attributed to immunologic dysregulation following COVID-19 infection. In this scenario, patients typically present with anemia due to decreased production of RBC and develop a compensatory response characterized by the release of immature erythroid progenitor cells into the bloodstream that contributes to an increase in RDW levels. 24 On the contrary, RDW may serve as a nonspecific aggregate biomarker of general illness that is not mechanistically associated with the disease progression of COVID-19. bias could occur when more intense surveillance or laboratory tests are arranged for critically ill patients than mildly ill patients. However, the risk of ascertainment bias may be low in the present analysis, as RDW is usually included as a part of the routine CBC test. The meta-analysis demonstrated that elevated RDW levels were associated with adverse outcomes in COVID-19 patients. This finding warrants further research on whether RDW could be utilized as a reliable prognostic tool for predicting COVID-19 severity. As RDW is widely available and included as a routine parameter of CBC, this simple laboratory test can be particularly useful in the context of the COVID-19 pandemic, where identifying high-risk patients and facilitating timely intervention with limited resources are critical. Future research should also examine whether RDW is mechanistically linked to the pathophysiology of COVID-19. The DATA AVAILABILITY STATEMENT Red blood cell distribution width: a simple parameter with multiple clinical applications Prognostic value of red cell distribution width in acute coronary syndrome Shape and biomechanical characteristics of human red blood cells in health and disease Red cell life span heterogeneity in hematologically normal people is sufficient to alter HbA1c Physiological and pathological population dynamics of circulating human red blood cells Red cell life span heterogeneity in hematologically normal people is sufficient to alter HbA1c Relation between red blood cell distribution width and inflammatory biomarkers in a large cohort of unselected outpatients Oxidative stress in the regulation of normal and neoplastic hematopoiesis Red blood cell distribution width and mortality risk in a community-based prospective cohort Hematologic, biochemical and immune biomarker abnormalities associated with severe illness and mortality in coronavirus disease 2019 (COVID-19): a meta-analysis Venous thromboembolism among hospitalized patients with COVID-19 undergoing thromboprophylaxis: a systematic review and meta-analysis Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement The preprint server for health sciences Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range Meta-analysis in clinical trials revisited Meta-analysis: Beyond the grand mean? Association of red blood cell distribution width with mortality risk in hospitalized adults with SARS-CoV-2 infection A Tool for Early Prediction of Severe Coronavirus Disease 2019 (COVID-19): a Multicenter Study Using the Risk Nomogram in Wuhan and Guangdong, China Red blood cell distribution width (RDW) predicts COVID-19 severity: a prospective, observational study from the Cincinnati SARS-CoV-2 Emergency Department Cohort Predicting severe COVID-19 at Presentation, Introducing the COVID Severity Score Estimating survival of hospitalized COVID-19 patients from admission information Characterizing COVID-19 clinical phenotypes and associated comorbidities and complication profiles. medRxiv Estimating risk of mechanical ventilation and mortality among adult COVID-19 patients admitted to Mass General Brigham: the VICE and DICE Scores. medRxiv Preliminary study to identify severe from moderate cases of COVID-19 using combined hematology parameters Clinical characteristics and immune injury mechanisms in 71 patients with COVID-19. mSphere Classification of COVID-19 in intensive care patients An increase in red blood cell distribution width from baseline predicts mortality in patients with severe sepsis or septic shock Red cell distribution width (RDW): a prognostic indicator of severe COVID-19 Anisocytosis is associated with short-term mortality in COVID-19 and may reflect proinflammatory signature in uninfected ambulatory adults Association between red blood cell distribution width and mortality and severity among patients with COVID-19: A systematic review and meta-analysis The data that support the findings of this study are available from the corresponding author upon reasonable request.ORCID Jane J. Lee https://orcid.org/0000-0002-6276-7667