RDW shows prognostic potential in hospitalized patients with COVID‐19
2022; Wiley; Volume: 94; Issue: 8 Linguagem: Inglês
10.1002/jmv.27764
ISSN1096-9071
Autores Tópico(s)Dermatological and COVID-19 studies
ResumoJournal of Medical VirologyEarly View LETTER TO THE EDITORFree Access RDW shows prognostic potential in hospitalized patients with COVID-19 Sergio Gama, Corresponding Author Sergio Gama s.gama@health.gov.je Department of Blood Sciences, Jersey General Hospital, Saint Helier, UK Correspondence Sergio Gama, Department of Blood Sciences, Jersey General Hospital, Gloucester Street, St. Helier, Jersey, JE1 3QS, UK. Email: s.gama@health.gov.jeSearch for more papers by this author Sergio Gama, Corresponding Author Sergio Gama s.gama@health.gov.je Department of Blood Sciences, Jersey General Hospital, Saint Helier, UK Correspondence Sergio Gama, Department of Blood Sciences, Jersey General Hospital, Gloucester Street, St. Helier, Jersey, JE1 3QS, UK. Email: s.gama@health.gov.jeSearch for more papers by this author First published: 06 April 2022 https://doi.org/10.1002/jmv.27764AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat To the Editor, A recent meta-analysis published in the Journal of Medical Virology identified a potential association between red cell distribution width (RDW) and mortality risk in patients with coronavirus disease 2019 (COVID-19).1 This follows similar reports elsewhere.2, 3 COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2),4 which has been associated with over 5 million deaths worldwide since December 2019.5 RDW is a routine full blood count (FBC) parameter that reflects the level of change in size between red cells (anisocytosis)6 and has been widely researched as an independent predictor of mortality in different hospital settings, including critically ill patients with sepsis.7 Identifying patients with a higher risk of in-hospital mortality may enable prioritization of resources and targeted treatments directed at those at increased risk of death which could ultimately improve outcomes. This retrospective study included all laboratory-confirmed cases of SARS-CoV-2 infection in patients presenting at the General Hospital in Jersey (Channel Islands, UK) between March and December 2020. Laboratory confirmation for SARS-CoV-2 was defined as a positive result of real-time reverse transcriptase-polymerase chain reaction (RT-PCR) assay using a nasopharyngeal/oropharyngeal swab as per World Health Organization guidance.8 Specimens were initially tested at Public Health England, Porton Down (UK), and in-house testing commenced in April 2020, using qualitative Gene Xpert SARS-CoV-2 RT-PCR test kits (Cepheid). FBC tests were locally performed on venous blood samples collected into a 4-ml anticoagulated BD Vacutainer tube containing K2 ethylenediaminetetraacetic acid (0.184 mol/L; BD), and analysis performed in Sysmex XN-2000 analyzers (Sysmex corporation). Biochemistry tests were performed on a venous blood sample collected into a 3.5-ml BD Vacutainer SST II gel tube (BD), centrifuged at 3500 rpm for 10 min before analysis, and then analyzed using Ortho Vitros 5600 analyzers (Ortho-Clinical Diagnostics) by MicroSlide technology. Statistical analysis was performed in the IBM SPSS software (version 26). Differences between groups were calculated using the t test if data were normally distributed; otherwise, the Mann–Whitney test was used. Categorical variables were compared using the χ2 or Fisher exact test, as appropriate. Probability (p) <0.05 was considered significant for all tests. Receiver operating characteristic (ROC) curves were calculated for continuous variables showing statistically significant differences between the survivors and non-survivors. The area under the curve (AUC) and the 95% confidence interval (CI) were determined to establish the optimal cut-off point that maximized sensitivity and specificity to predict death by the Youden's index. These cut-offs were used to transform the continuous variables into binary variables, and univariate and multivariate logistic regression models were applied to calculate the estimated odds ratio and the 95% CI. A total of 139 patients were identified as having had a positive SARS-CoV-2 RT-PCR test on admission or during hospitalization: 27 patients presented with minor symptoms and only required a short hospitalization (<2 days), and 29 were hospital-acquired cases. 77 patients (55.4%) were male, and 62 were female (44.6%). Nonsurvivors were found to be significantly older (median age: 82 vs. 69 years; p = 0.001) and presented with higher RDW results when compared with survivors (14.1 vs. 13.2 in survivors; p = 0.004) (Table 1). Men accounted for most deaths in this cohort (males: 18 deaths, 58.1% vs. females: 13 deaths, 41.9%). Like other studies, no statistically significant difference was found in gender distribution between survivors and nonsurvivors (p = 0.735).2, 9 Table 1. Demographics and laboratory features in COVID-19 patients Survivors (n = 108) Non-Survivors (n = 31) Parameter Median (IQR) or mean ± SD Median (IQR) or mean ± SD p value Age (years) 69 (53–80) 82 (75–87) 0.001a,b, a,ba Mann-Whitney U test.b Statistically significant (p < 0.05). Hemoglobin (g/dl) 13.09 ± 1.91 12.54 ± 2.40 0.190cc t Test. WBC (109/L) 6.9 (5.5–9.4) 9.5 (6.1–13.6) 0.012a,ba Mann-Whitney U test. Platelets (109/L) 228.5 (183.0–292.0) 255.0 (173.2–337.5) 0.556aa Mann-Whitney U test. RDW (%) 13.2 (12.3–14.3) 14.1 (13.0–15.0) 0.004a,ba Mann-Whitney U test. Neutrophils (109/L) 4.8 (3.5–6.9) 7.3 (4.2–12.2) 0.008a,ba Mann-Whitney U test. Lymphocytes (109/L) 1.1 (0.7–1.7) 0.7 (0.5–0.9) <0.001a,ba Mann-Whitney U test. Monocytes (109/L) 0.6 (0.4–0.8) 0.6 (0.4–1.0) 0.680aa Mann-Whitney U test. Eosinophils (109/L) 0.04 (0.01–0.12) 0.03 (0.01–0.08) 0.422aa Mann-Whitney U test. Basophils (109/L) 0.02 (0.01–0.04) 0.02 (0.01–0.06) 0.478aa Mann-Whitney U test. Creatinine (µmol/L) 72.0 (55.0–90.0) 102 (63.0–123.0) 0.004a,ba Mann-Whitney U test. CRP (mg/L) 34.0 (11.0–69.0) 62.0 (33.0–174.0) 0.003a,ba Mann-Whitney U test. Note: ♂ male; ♀ female. Abbreviations: IQR: Interquartile range (Q1, Q3); SD, standard deviation. a Mann-Whitney U test. b Statistically significant (p < 0.05). c t Test. ROC curve analysis determined RDW >14% as the optimal cut-off point for logistic regression analysis (AUC = 0.668 [95% CI: 0.572–0.764]; p = 0.004), and univariate analysis confirmed this cut-off was significantly associated with death (p = 0.008). Cut-offs determined for the other parameters showing statistically significant differences between survivors and nonsurvivors are shown in Table 2. The multivariate logistic analysis demonstrated that RDW > 14% on admission was associated with a 3.7-fold increased mortality risk in hospitalized patients with COVID-19 (p = 0.015), and this association was independent of the effects of age, WBC, neutrophils, lymphocytes, creatinine, or CRP. Age >70 years, neutrophils ≥10.2 × 109/L, and lymphocytes 70 years 10.431 2.991–36.378 8.3 × 109/L 3.636 1.574–8.402 0.003 RDW >14% 3.048 1.335–6.958 0.008 3.744 1.292–10.852 0.015 Neutrophils ≥10.2 × 109/L 7.078 2.695–18.588 <0.001 10.187 2.761–37.582 <0.001 Lymphocytes <0.88 × 109/L 7.151 2.812–18.186 <0.001 5.592 1.848–16.916 0.002 Creatinine ≥100 µmol/L 5.624 2.371–13.341 44 mg/L 3.500 1.472–8.320 0.005 Abbreviations: CI, confidence interval; OR, odds ratio. This study showed nonsurvivors presented with higher RDW (p = 0.004), which is comparable with other studies,2, 3 although the author reports more modest differences between sub-groups. Regression analysis identified a significantly higher mortality risk in hospitalized patients with COVID-19 presenting with RDW greater than 14% on admission, confirming its prognostic potential. RDW has been widely researched as an independent predictor of mortality in other settings,7 suggesting RDW may act as a generic predictor of mortality, not directly linked to specific pathological changes arising from SARS-CoV-2 infection. Despite this, RDW may play a role in the risk-stratification of hospitalized patients with COVID-19. CONFLICT OF INTEREST The author declares no conflict of interest. DATA AVAILABILITY STATEMENT The data that support the findings of this study are available from the corresponding author upon reasonable request. PEER REVIEW The peer review history for this article is available at https://publons.com/publon/10.1002/jmv.27764 Open Research PEER REVIEW The peer review history for this article is available at https://publons.com/publon/10.1002/jmv.27764 DATA AVAILABILITY STATEMENT The data that support the findings of this study are available from the corresponding author upon reasonable request. REFERENCES 1Lee JJ, Jamil U, Chi G, Chuang ML. Association between red blood cell distribution width and mortality and severity among patients with COVID-19: a systematic review and meta-analysis. J Med Virol. 2021; 93: 2513- 2522. Wiley Online LibraryCASPubMedWeb of Science®Google Scholar 2Foy BH, Carlson JCT, Reinertsen E, et al. Association of red blood cell distribution width with mortality risk in hospitalized adults with SARS-CoV-2 infection. JAMA Netw open. 2020; 3(9):e2022058. CrossrefPubMedWeb of Science®Google Scholar 3Henry BM, Benoit JL, Benoit S, et al. Red blood cell distribution width (RDW) predicts COVID-19 severity: a prospective, observational study from the cincinnati SARS-CoV-2 emergency department cohort. Diagnostics. 2020; 10(9): 1- 9. CrossrefGoogle Scholar 4Zhu N, Zhang D, Wang W, et al. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med. 2020; 382(8): 727- 733. CrossrefCASPubMedWeb of Science®Google Scholar 5 WHO. COVID-19 Weekly Epidemiological Update. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports/. Accessed November 22 2021. Google Scholar 6Lippi G, Mattiuzzi C, Cervellin G. Learning more and spending less with neglected laboratory parameters: the paradigmatic case of red blood cell distribution width. Acta Biomed. 2016; 87(3): 323- 328. CASPubMedGoogle Scholar 7Zhang 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(1): 1- 8. CrossrefPubMedGoogle Scholar 8 WHO. Laboratory testing for coronavirus disease 2019 (COVID-19) in suspected human cases, Accessed November 22 2021. https://www.who.int/publications/i/item/10665-331501Google Scholar 9Wang 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. CrossrefCASPubMedWeb of Science®Google Scholar Early ViewOnline Version of Record before inclusion in an issue ReferencesRelatedInformation
Referência(s)