ABSTRACT
BACKGROUND AND PURPOSE: Studies have shown that some cytokines in COVID-19 patients were elevated. This study aims to assess whether IL-10, IL-1ß, IL-6, MCP-1, TNF-α, IP-10 and IL-4 serve as potential diagnostic biomarkers of COVID-19. METHODS: The above serum cytokines in COVID-19 patients and non-COVID-19 patients were detected by ELISA and SARS-CoV-2 IgM and IgG were detected by the chemiluminescence method. The independent-sample Mann-Whitney U test was utilised to compare cytokine levels in different groups and courses, the Levene T-test and T'-test were utilised to compare they in different genders and the Spearman correlation test was utilised to analyse the correlation between the cytokine levels with ages and SARS-CoV-2 IgG and IgM. RESULTS: Serum levels of IL-10, IL-1ß, MCP-1, TNF-α and IL-4 in COVID-19 patients were significantly higher than those in non-COVID-19 patients, while IL-6 were only significantly higher than in healthy people, IP-10 were significantly lower than in other diseases patients. AUCs of COVID-19 diagnosed by IL-10, IL-1ß, IL-6, MCP-1, TNF-α, IP-10 and IL-4 were 0.735, 0.775, 0.595, 0.821, 0.848, 0.38 and 0.682, respectively. In the COVID-19 patients' serum, the levels of IL-10 and MCP-1 of male were noticeably higher than those of female, and all cytokines were significantly positively correlated with age, IL-1ß and IL-4 were significantly negatively correlated with SARS-CoV-2 IgM, while IL-10, IL-1ß, IL-6, TNF- and IP-10 were significantly negatively correlated with SARS-CoV-2 IgG. IL-10 on 43-56 days was significantly lower than at 29-42 days, TNF-α at 15-42 days was significantly higher than at 0-14 days, IP-10 at 0-14 days was the highest and IL-4 at 29-42 days was significantly higher than at 0-14 days. CONCLUSIONS: The detection of IL-10, IL-1 ß, IL-6, MCP-1, TNF-α and IL-4 would assist the clinical study of COVID-19, and IP-10 may be the cytokine of early elevation in COVID-19 patients.
Subject(s)
COVID-19 , Tumor Necrosis Factor-alpha , Chemokine CXCL10 , Cytokines , Female , Humans , Interleukin-10 , Interleukin-1beta , Interleukin-4 , Interleukin-6 , Male , SARS-CoV-2ABSTRACT
COVID-19 has developed into a worldwide pandemic; early identification of severe illness is critical for controlling it and improving the prognosis of patients with limited medical resources. The present study aimed to analyze the characteristics of severe COVID-19 and identify biomarkers for differential diagnosis and prognosis prediction. In total, 27 consecutive patients with COVID-19 and 75 patients with flu were retrospectively enrolled. Clinical parameters were collected from electronic medical records. The disease course was divided into four stages: initial, progression, peak, and recovery stages, according to computed tomography (CT) progress. to mild COVID-19, the lymphocytes in the severe COVID-19 progressively decreased at the progression and the peak stages, but rebound in the recovery stage. The levels of C-reactive protein (CRP) in the severe group at the initial and progression stages were higher than those in the mild group. Correlation analysis showed that CRP (R = .62; P < .01), erythrocyte sedimentation rate (R = .55; P < .01) and granulocyte/lymphocyte ratio (R = .49; P < .01) were positively associated with the CT severity scores. In contrast, the number of lymphocytes (R = -.37; P < .01) was negatively correlated with the CT severity scores. The receiver-operating characteristic analysis demonstrated that area under the curve of CRP on the first visit for predicting severe COVID-19 was 0.87 (95% CI 0.10-1.00) at 20.42 mg/L cut-off, with sensitivity and specificity 83% and 91%, respectively. CRP in severe COVID-19 patients increased significantly at the initial stage, before CT findings. Importantly, CRP, which was associated with disease development, predicted early severe COVID-19.
Subject(s)
Betacoronavirus/pathogenicity , C-Reactive Protein/metabolism , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Disease Outbreaks , Influenza, Human/diagnosis , Influenza, Human/epidemiology , Pneumonia, Viral/diagnosis , Pneumonia, Viral/epidemiology , Adolescent , Adult , Aged , Area Under Curve , Betacoronavirus/genetics , Biomarkers/blood , Blood Sedimentation , COVID-19 , China/epidemiology , Coronavirus Infections/blood , Coronavirus Infections/pathology , Early Diagnosis , Electronic Health Records , Female , Granulocytes/pathology , Humans , Influenza, Human/blood , Influenza, Human/pathology , Lymphocytes/pathology , Male , Middle Aged , Orthomyxoviridae/genetics , Orthomyxoviridae/isolation & purification , Pandemics , Pneumonia, Viral/blood , Pneumonia, Viral/pathology , Prognosis , ROC Curve , Retrospective Studies , SARS-CoV-2 , Severity of Illness Index , Tomography, X-Ray ComputedABSTRACT
Recently, some global cases of 2019 novel coronavirus (COVID-19) pneumonia have been caused by second- or third-generation transmission of the viral infection, resulting in no traceable epidemiological history. Owing to the complications of COVID-19 pneumonia, the first symptom and imaging features of patients can be very atypical and early diagnosis of COVID-19 infections remains a challenge. It would aid radiologists and clinicians to be aware of the early atypical symptom and imaging features of the disease and contribute to the prevention of infected patients being missed.