About: 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.   Goto Sponge  NotDistinct  Permalink

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  • 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
  • Zoonoses
  • Viral respiratory tract infections
  • Data mining
  • COVID-19
  • Occupational safety and health
  • Medical mnemonics
  • Diagnostic intensive care medicine
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