| Literature DB >> 32281668 |
Chaochao Tan1, Ying Huang2, Fengxia Shi3, Kui Tan1, Qionghui Ma4, Yong Chen4, Xixin Jiang5, Xiaosong Li6.
Abstract
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.Entities:
Keywords: C-reactive protein; COVID-19; SARS-COVID-2
Mesh:
Substances:
Year: 2020 PMID: 32281668 PMCID: PMC7262341 DOI: 10.1002/jmv.25871
Source DB: PubMed Journal: J Med Virol ISSN: 0146-6615 Impact factor: 20.693
Figure 1CT Score example: 0 point, Five lobes of lungs are not involved, 0 point for every lobe; 1 point, Minimal involvement (<25%) in right middle lobe, right lower lobe, left upper lobe and left lower lobe, 1 point for each lung lobe, 4 points in total; 2 points, Mild involvement (26‐50%) in the left lower lobe, 2 points in the left lower lobe; 3 points, Moderate involvement (51‐75%) in the right upper lobe, and 3 points in the right upper lobe; 4 points, Severe involvement (>75%) in right lower lobe, left upper lobe and left lower lobe, 4 points for each lung lobe, 12 points in total
Demographics and laboratory characteristics of patients with SARS‐COV2 and with flu
| Variables | SARS‐COV‐2 | Influenza A or B |
|
|---|---|---|---|
| N | N=27 | N=75 | |
| Median age, y | 48.89 ± 18.47 | 29.40 ± 13.70 | <.01 |
| Male sex, N (%) | 11 (41%) | 27 (36%) | .631 |
| Exposure | |||
| Close contact with infected patients, N (%) | 12 (44%) | NA | |
| Visit to Wuhan, N (%) | 11 (41%) | NA | |
| None, N (%) | 4 (15%) | NA | |
| Comorbidities | |||
| Hypertension, N (%) | 6 (22%) | 5 (7%) | <.01 |
| Cardiovascular disease, N (%) | 3 (11%) | 2 (2.6%) | .034 |
| Diabetes, N (%) | 2 (7%) | 4 (5.2%) | .653 |
| Symptoms | |||
| Fever, N (%) | 24 (88%) | NA | |
| Fatigue, N (%) | 9 (33%) | NA | |
| Cough, N (%) | 12 (44%) | NA | |
| Headache, N (%) | 3 (11%) | NA | |
| Expectoration, N (%) | 2 (7%) | NA | |
| Muscle soreness, N (%) | 4 (15%) | NA | |
| Hemoptysis, N (%) | 1 (4%) | NA | |
| Diarrhea, N (%) | 1 (4%) | NA | |
| Nausea, N (%) | 1 (4%) | NA | |
| Disease severity | |||
| Hospitalization, N (%) | 27 (100%) | 15 (20%) | <.01 |
| Clinical outcomes | <.01 | ||
| Discharge from hospital, N (%) | 26 (96%) | 14 (100%) | |
| Death, N (%) | 0 | 0 | |
| Staying in hospital, N (%) | 1 (4%) | 0 | |
| Clinical laboratory | |||
| WBC, ×109/L | 5.60 ± 1.81 | 6.18 ± 2.29 | .114 |
| Granulocyte, ×109/L | 3.75 ± 1.47 | 4.26 ± 2.14 | .024 |
| Lymphocyte, ×109/L | 1.38 ± 0.56 | 1.17 ± 0.47 | .308 |
| NLR (IQR) | 2.58 (1.91‐3.82) | 3.70 (2.10‐6.04) | .034 |
| Monocytes | 0.44 ± 0.18 | 0.69 ± 0.33 | .007 |
| RBC, ×1012/L | 4.79 ± 0.45 | 4.58 ± 0.48 | .980 |
| Hemoglobin, g/L | 146.41 ± 13.07 | 138.52 ± 15.78 | .566 |
| Hematocrit, % | 42.86 ± 3.94 | 41.22 ± 5.68 | .433 |
| Platelet, ×109/L | 206.00 ± 68.77 | 195.68 ± 59.01 | .241 |
Abbreviations; IQR, interquartile range; NLR, granulocyte/lymphocyte ratio; RBC, red blood cell; WBC, white blood cell.
Figure 2The alteration of biomarkers in the disease course
Figure 3Correlation analysis between CT scores and biomarkers. CT, computed tomographic
The receiver operating characteristic curves for severity in COVID‐19 patients
| Variables | Cut‐off | AUC (95% CI) | Sensitivity | Specificity | PPV | NPV | Youden index |
|---|---|---|---|---|---|---|---|
| WBC, ×109/L | 4.61 | 0.51 (0.24‐0.79) | 83% | 38% | 63% | 89% | 0.21 |
| N, ×109/L | 3.15 | 0.57 (0.30‐0.85) | 83% | 43% | 29% | 90% | 0.26 |
| L, ×109/L | 1.49 | 0.40 (0.13‐0.67) | 33% | 67% | 22% | 78% | 0.10 |
| NLR | 2.41 | 0.61 (0.33‐0.90) | 83% | 43% | 29% | 90% | 0.26 |
| CRP, mg/L | 20.42 | 0.87 (0.18‐1.00) | 83% | 91% | 71% | 95% | 0.74 |
| ESR, mm/L | 19.50 | 0.78 (0.39‐1.00) | 83% | 81% | 56% | 94% | 0.64 |
| CT scores | 7.00 | 0.71 (0.44‐0.98) | 50% | 91% | 60% | 86% | 0.41 |
Note: The 95% confidence interval is shown in parentheses.
Abbreviations: AUC, area under curve; CRP, C‐reactive protein; ESR, erythrocyte sedimentation rate; L, lymphocyte; N, neutrophils; NLR, granulocyte/lymphocyte ratio; NPV, negative predictive value; PPV, positive predictive value; WBC, white blood cell.
Figure 4The receiver operating characteristic analysis of biomarkers on first visit