Clinical laboratory evaluation of COVID-19

Chen, Zhufeng; Xu, Wenzhe; Ma, Wanbiao; Shi, Xia; Li, Shuomin; Hao, Min; Fang, Yuanxun; Zhang, Li

doi:10.1016/j.cca.2021.04.022

Cited by 38 publications

(35 citation statements)

References 112 publications

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“…Other inflammatory parameters, including WBC, PCT, ESR, and SAA, were also proposed as the predictors of fatality. Our synthesis agrees with the findings of previous studies [179][180][181][182][183]. All patients with COVID-19, regardless of the severity, should be screened for hyperinflammation as precaution for potential ARDS once increases in these indicators are detected.…”

Section: Discussionsupporting

confidence: 90%

Identification of Parameters Representative of Immune Dysfunction in Patients with Severe and Fatal COVID-19 Infection: a Systematic Review and Meta-analysis

Qin

Yang

et al. 2022

Clinic Rev Allerg Immunol

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Abnormal immunological indicators associated with disease severity and mortality in patients with COVID-19 have been reported in several observational studies. However, there are marked heterogeneities in patient characteristics and research methodologies in these studies. We aimed to provide an updated synthesis of the association between immune-related indicators and COVID-19 prognosis. We conducted an electronic search of PubMed, Scopus, Ovid, Willey, Web of Science, Cochrane library, and CNKI for studies reporting immunological and/or immune-related parameters, including hematological, inflammatory, coagulation, and biochemical variables, tested on hospital admission of COVID-19 patients with different severities and outcomes. A total of 145 studies were included in the current meta-analysis, with 26 immunological, 11 hematological, 5 inflammatory, 4 coagulation, and 10 biochemical variables reported. Of them, levels of cytokines, including IL-1β, IL-1Ra, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, TNF-α, IFN-γ, IgA, IgG, and CD4 + T/CD8 + T cell ratio, WBC, neutrophil, platelet, ESR, CRP, ferritin, SAA, D-dimer, FIB, and LDH were significantly increased in severely ill patients or non-survivors. Moreover, non-severely ill patients or survivors presented significantly higher counts of lymphocytes, monocytes, lymphocyte/monocyte ratio, eosinophils, CD3 + T,CD4 + T and CD8 + T cells, B cells, and NK cells. The currently updated meta-analysis primarily identified a hypercytokinemia profile with the severity and mortality of COVID-19 containing IL-1β, IL-1Ra, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, TNF-α, and IFN-γ. Impaired innate and adaptive immune responses, reflected by decreased eosinophils, lymphocytes, monocytes, B cells, NK cells, T cells, and their subtype CD4 + and CD8 + T cells, and augmented inflammation, coagulation dysfunction, and nonpulmonary organ injury, were marked features of patients with poor prognosis. Therefore, parameters of immune response dysfunction combined with inflammatory, coagulated, or nonpulmonary organ injury indicators may be more sensitive to predict severe patients and those non-survivors. Supplementary Information The online version contains supplementary material available at 10.1007/s12016-021-08908-8.

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Section: Discussionsupporting

confidence: 90%

Identification of Parameters Representative of Immune Dysfunction in Patients with Severe and Fatal COVID-19 Infection: a Systematic Review and Meta-analysis

Qin

Yang

et al. 2022

Clinic Rev Allerg Immunol

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“…Thus, ferritin has been extensively studied in COVID-19, with marked hyperferritinemia being a nearly constant finding in severe disease. In clinical practice, ferritin has been also frequently included in routine evaluation of COVID-19 at hospital admission ( 40 ). Several meta-analyses have evaluated the performance of ferritin as a prognostic index in COVID-19 ( 41 , 42 ).…”

Section: Introductionmentioning

confidence: 99%

Iron metabolism in infections: Focus on COVID-19

Girelli

Marchi

Busti

et al. 2021

Seminars in Hematology

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Iron is a micronutrient essential for a wide range of metabolic processes in virtually all living organisms. During infections, a battle for iron takes place between the human host and the invading pathogens. The liver peptide hepcidin, which is phylogenetically and structurally linked to defensins (antimicrobial peptides of the innate immunity), plays a pivotal role by subtracting iron to pathogens through its sequestration into host cells, mainly macrophages. While this phenomenon is well studied in certain bacterial infections, much less is known regarding viral infections. Iron metabolism also has implications on the functionality of cells of the immune system. Once primed by the contact with antigen presenting cells, lymphocytes need iron to sustain the metabolic burst required for mounting an effective cellular and humoral response. The COVID-19 pandemic has boosted an amount of clinical and translational research over the possible influences of nutrients on SARS-CoV-2 infection, in terms of either susceptibility or clinical course. Here we review the intersections between iron metabolism and COVID-19, belonging to the wider domain of the so-called “nutritional immunity”. A better understanding of such connections has potential broad implications, either from a mechanistic standpoint, or for the development of more effective strategies for managing COVID-19 and possible future pandemics.

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“… 25 Studies have reported that increased WBC, CRP, IL‐6, procalcitonin, ferritin, LDH, AST, ALT, D‐dimer, and troponin levels, and decreased lymphocyte and platelet levels are associated with the severity of COVID‐19. 4 , 26 , 27 , 28 , 29 This study has also shown that laboratory data contribute significantly to the diagnosis, prognosis, and treatment follow‐up of COVID‐19.…”

Section: Discussionmentioning

confidence: 73%

Can laboratory parameters be an alternative to CT and RT‐PCR in the diagnosis of COVID‐19? A machine learning approach

Kalaycı

Ayyıldız

Tuncer

et al. 2022

Int J Imaging Syst Tech

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In this study, a machine learning‐based decision support system that uses routine laboratory parameters has been proposed in order to increase the diagnostic success in COVID‐19. The main goal of the proposed method was to reduce the number of misdiagnoses in the RT‐PCR and CT scans and to reduce the cost of testing. In this study, we retrospectively reviewed the files of patients who presented to the coronavirus outpatient. The demographic, thoracic CT, and laboratory data of the individuals without any symptoms of the disease, who had negative RT‐PCR test and who had positive RT‐PCR test were analyzed. CT images were classified using hybrid CNN methods to show the superiority of the decision support system using laboratory parameters. Detection of COVID‐19 from CT images achieved an accuracy of 97.56% with the AlexNet‐SVM hybrid method, while COVID‐19 was classified with an accuracy of 97.86% with the proposed method using laboratory parameters.

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Clinical laboratory evaluation of COVID-19

Cited by 38 publications

References 112 publications

Identification of Parameters Representative of Immune Dysfunction in Patients with Severe and Fatal COVID-19 Infection: a Systematic Review and Meta-analysis

Identification of Parameters Representative of Immune Dysfunction in Patients with Severe and Fatal COVID-19 Infection: a Systematic Review and Meta-analysis

Iron metabolism in infections: Focus on COVID-19

Can laboratory parameters be an alternative to CT and RT‐PCR in the diagnosis of COVID‐19? A machine learning approach

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