Dynamic Changes in Parameters of Complete Blood Count Predict Disease Severity and Prognosis in Patients with COVID-19; A Prospective Study
Novelty in Biomedicine,
Vol. 13 No. 1 (2025),
20 Bahman 2025
,
Page 10-16
https://doi.org/10.22037/nbm.v13i1.45941
Abstract
Background: The pandemic of the coronavirus disease 2019 (COVID-19) is a major cause of death worldwide; thus, disease prediction is important. This study aimed to evaluate dynamic changes of complete blood count parameters in adult patients to predict disease severity.
Materials and Methods: Data from 980 consecutive hospitalized patients diagnosed with COVID-19 were analyzed prospectively. Patients were categorized into moderate disease-cured (n = 682), severe disease-cured (n = 136), and deceased (n = 162) groups. Clinical conditions at the admission and blood samples every other day were collected for each patient from hospital admission to discharge or death. Mean values of serum parameters were compared among the three groups; the Hazard ratio of different indices for death was calculated, and repeated measured ANOVA was employed to assess the prognostic importance of dynamic changes in blood parameters during the disease.
Results: Univariable and multivariable regression analysis showed that the only important clinical risk factor associated with death was needing invasive ventilation at admission (HR of 18.97 and 23.82 in univariable and multivariable regression analysis, respectively). Considering dynamic changes in blood elements, repeated measured ANOVA showed patients who survived had a decrease in WBC and Neutrophil count as well as Neutrophil to lymphocyte ratio (NLR) compared to expired patients; in contrast, platelet and lymphocyte count increased in survivors while dropped in deceased ones.
Conclusion: Dynamic changes in blood indices are prognostic indicators of an unfavorable prognosis for COVID-19 infection.
- COVID-19
- Severity
- Blood cell count
- Mortality
- Intensive care units
How to Cite
References
Singhal TJA. A review of coronavirus disease-2019 (COVID-19) The indian journal of pediatrics. 2020; 87 (4): 281–286.
Qiu P, Zhou Y, Wang F, et al. Clinical characteristics, laboratory outcome characteristics, comorbidities, and complications of related COVID-19 deceased: a systematic review and meta-analysis. 2020;32(9):1869-1878.
Hu Y, Sun J, Dai Z, et al. Prevalence and severity of corona virus disease 2019 (COVID-19): A systematic review and meta-analysis. 2020;127:104371.
Hellewell J, Abbott S, Gimma A, et al. Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts. 2020;8(4):488-96.
World Health O. Coronavirus disease 2019 (COVID-19): situation report, 70. Geneva: World Health Organization; 2020-03-30 2020.
Lauer SA, Grantz KH, Bi Q, et al. The incubation period of coronavirus disease 2019 (COVID-19) from publicly reported confirmed cases: estimation and application. 2020;172(9):577-82.
Nishiura H, Kobayashi T, Miyama T, et al. Estimation of the asymptomatic ratio of novel coronavirus infections (COVID-19). 2020;94:154-5.
Zu ZY, Di Jiang M, Xu PP, et al. Coronavirus disease 2019 (COVID-19): a perspective from China. 2020.
Li Y, Xia LJAAJR. Coronavirus disease 2019 (COVID-19): role of chest CT in diagnosis and management. 2020;214(6):1280-1286.
Ai T, Yang Z, Hou H, et al. Correlation of chest CT and RT-PCR testing in coronavirus disease 2019 (COVID-19) in China: a report of 1014 cases. 2020.
Ma C, Gu J, Hou P, et al. Incidence, clinical characteristics and prognostic factor of patients with COVID-19: a systematic review and meta-analysis. 2020:2020.2003.2017.20037572.
Guan W-j, Liang W-h, Zhao Y, et al. Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis. 2020;55(5):2000547.
Terpos E, Ntanasis‐Stathopoulos I, Elalamy I, et al. Hematological findings and complications of COVID‐19. 2020;95(7):834-47.
Henry BM, De Oliveira MHS, Benoit S, Plebani M, Lippi GJCC, Medicine L. Hematologic, biochemical and immune biomarker abnormalities associated with severe illness and mortality in coronavirus disease 2019 (COVID-19): a meta-analysis. 2020;58(7):1021-8.
Goel H, Gupta I, Mourya M, et al. A systematic review of clinical and laboratory parameters of 3,000 COVID-19 cases. Obstet Gynecol Sci. 2021;64(2):174-89.
Asghar M, Hussain N, Shoaib H, Kim M, Lynch TJ. Hematological characteristics of patients in coronavirus 19 infection: a systematic review and meta-analysis. J Community Hosp Intern Med Perspect. 2020;10(6):508-13.
Ahern DJ, Ai Z, Ainsworth M, et al. A blood atlas of COVID-19 defines hallmarks of disease severity and specificity. Cell. 2022/03/03/ 2022;185(5):916-938.e958.
Ghahramani S, Tabrizi R, Lankarani KB, et al. Laboratory features of severe vs. non-severe COVID-19 patients in Asian populations: a systematic review and meta-analysis. European Journal of Medical Research. 2020/08/03 2020;25(1):30.
Liu K, Fang Y-Y, Deng Y, et al. Clinical characteristics of novel coronavirus cases in tertiary hospitals in Hubei Province. 2020;133(09):1025-31.
Solomon T, Lewthwaite P, Perera D, Cardosa MJ, McMinn P, Ooi MHJTLid. Virology, epidemiology, pathogenesis, and control of enterovirus 71. 2010;10(11):778-90.
Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. 2020;395(10223):497-506.
Qin C, Ziwei MPLZM, Tao SYMY, Ke PCXMP, Shang MMPKJCID. Dysregulation of immune response in patients with COVID-19 in Wuhan, China; Clinical Infectious Diseases; Oxford Academic. 2020.
Wang D, Hu B, Hu C, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus–infected pneumonia in Wuhan, China. 2020;323(11):1061-9.
Thachil J. What do monitoring platelet counts in COVID-19 teach us? J Thromb Haemost. 2020;18(8):2071-2.
Giannis D, Ziogas IA, Gianni PJJoCV. Coagulation disorders in coronavirus infected patients: COVID-19, SARS-CoV-1, MERS-CoV and lessons from the past. 2020;127:104362.
Simmons J, Pittet J-FJCoia. The coagulopathy of acute sepsis. 2015;28(2):227.
Makatsariya AD, Grigoreva K, Mingalimov MA, et al. Coronavirus disease (COVID-19) and disseminated intravascular coagulation syndrome. 2020;14(2):123-131.
Tang N, Li D, Wang X, Sun ZJJot, haemostasis. Abnormal coagulation parameters are associated with poor prognosis in patients with novel coronavirus pneumonia. 2020;18(4):844-847.
Lippi G, Plebani M, Henry BMJCca. Thrombocytopenia is associated with severe coronavirus disease 2019 (COVID-19) infections: a meta-analysis. 2020;506:145-8.
Li Q, Ding X, Xia G, et al. A simple laboratory parameter facilitates early identification of COVID-19 patients. 2020.
Taneri PE, Alejandro Gómez-Ochoa S, Llanaj E, et al. Anemia and iron metabolism in COVID-19: A systematic review and meta-analysis. 2020:2020.2006.2004.20122267.
Wu C, Chen X, Cai Y, et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. 2020;180(7):934-43.
Liu Y, Du X, Chen J, et al. Neutrophil-to-lymphocyte ratio as an independent risk factor for mortality in hospitalized patients with COVID-19. 2020;81(1):e6-e12.
Zhang B, Zhou X, Zhu C, et al. Immune phenotyping based on the neutrophil-to-lymphocyte ratio and IgG level predicts disease severity and outcome for patients with COVID-19. 2020;7:157.
Słomka A, Kowalewski M, Żekanowska EJP. Coronavirus disease 2019 (COVID–19): A short review on hematological manifestations. 2020;9(6):493.
Yang A-P, Liu J-p, Tao W-q, Li H-mJIi. The diagnostic and predictive role of NLR, d-NLR and PLR in COVID-19 patients. 2020;84:106504.
Qu R, Ling Y, Zhang Yhz, et al. Platelet‐to‐lymphocyte ratio is associated with prognosis in patients with coronavirus disease‐19. 2020;92(9):1533-1541.
Eslamijouybari M, Heydari K, Maleki I, et al. Neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios in COVID-19 patients and control group and relationship with disease prognosis. 2020;11(Suppl 1):531.
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