Incubation period, clinical and lung CT features for early prediction of COVID-19 deterioration: development and internal verification of a risk model.

BACKGROUND: Most severe, critical, or mortal COVID-19 cases often had a relatively stable period before their status worsened. We developed a deterioration risk model of COVID-19 (DRM-COVID-19) to predict exacerbation risk and optimize disease management on admission. METHOD: We conducted a multicenter retrospective cohort study with 239 confirmed symptomatic COVID-19 patients. A combination of the least absolute shrinkage and selection operator (LASSO), change-in-estimate (CIE) screened out independent risk factors for the multivariate logistic regression model (DRM-COVID-19) from 44 variables, including epidemiological, demographic, clinical, and lung CT features. The compound study endpoint was progression to severe, critical, or mortal status. Additionally, the model's performance was evaluated for discrimination, accuracy, calibration, and clinical utility, through internal validation using bootstrap resampling (1000 times). We used a nomogram and a network platform for model visualization. RESULTS: In the cohort study, 62 cases reached the compound endpoint, including 42 severe, 18 critical, and two mortal cases. DRM-COVID-19 included six factors: dyspnea [odds ratio (OR) 4.89;confidence interval (95% CI) 1.53-15.80], incubation period (OR 0.83; 95% CI 0.68-0.99), number of comorbidities (OR 1.76; 95% CI 1.03-3.05), D-dimer (OR 7.05; 95% CI, 1.35-45.7), C-reactive protein (OR 1.06; 95% CI 1.02-1.1), and semi-quantitative CT score (OR 1.50; 95% CI 1.27-1.82). The model showed good fitting (Hosmer-Lemeshow goodness, X2(8) = 7.0194, P = 0.53), high discrimination (the area under the receiver operating characteristic curve, AUROC, 0.971; 95% CI, 0.949-0.992), precision (Brier score = 0.051) as well as excellent calibration and clinical benefits. The precision-recall (PR) curve showed excellent classification performance of the model (AUCPR = 0.934). We prepared a nomogram and a freely available online prediction platform ( https://deterioration-risk-model-of-covid-19.shinyapps.io/DRMapp/ ). CONCLUSION: We developed a predictive model, which includes the including incubation period along with clinical and lung CT features. The model presented satisfactory prediction and discrimination performance for COVID-19 patients who might progress from mild or moderate to severe or critical on admission, improving the clinical prognosis and optimizing the medical resources.

Clinical characteristics and viral shedding kinetics of 38 asymptomatic patients with coronavirus disease 2019: A retrospective observational study.

ABSTRACT: This study aims to investigate the clinical characteristics and viral shedding kinetics of asymptomatic patients with coronavirus disease 2019 (COVID-19).The data of 38 asymptomatic patients positive for SARS-CoV-2 nucleic acid were collected from February to March 2020 in Tuanfeng County, Huanggang, Hubei, China. The epidemiology, laboratory examination, chest imaging, viral nucleic acid test results, clinical characteristics, and viral shedding time were summarized in this retrospective study.The study included 20 family members of patients with COVID-19, 10 medical personnel participating in COVID-19 treatment or working in a fever clinic, 6 personnel from quarantine places, 1 individual with a close contact history with confirmed patients, and 1 local epidemic prevention personnel. All were positive for SARS-CoV-2 nucleic acid. The white blood cell (WBC) count, the absolute value of lymphocytes, C-reactive protein (CRP), and D-dimer were normal. Pneumonia manifestations were not found in the chest computed tomography (CT) scan of 36 patients; the remaining 2 cases included a 1-year-old child and a pregnant woman, and they did not undergo chest CT. The viral shedding time was 6 days.All asymptomatic patients with COVID-19 had a history of close contact or exposure. Laboratory tests were normal. Chest imaging did not show any pneumonia manifestation. The viral shedding time was <10 days, which is shorter than that of patients with COVID-19. A timely discovery of such asymptomatic infections is crucial for blocking the spread of the virus and strengthening the prevention and control measures.

A synergistic role of convalescent plasma and mesenchymal stem cells in the treatment of severely ill COVID-19 patients: a clinical case report.

Acute respiratory distress syndrome virus-2 (SARS-CoV-2) responsible for coronavirus disease 2019 (COVID-19) infection, which causes global public health emergencies, has sped widely for more than 5 months and has the risk of long-term transmission. No effective treatment has been discovered to date. In the cases we report, the patient continued to deteriorate even after administration of antiviral drugs such as lopinavir/ritonavir, interferon-α, and ribavirin, as well as intravenous injection of meropenem, methylprednisolone, and immunoglobulin. So, we infused the patient with convalescent plasma (CP), and the absolute lymphocyte count increased the next day and returned to normal on the fourth day. Followed by intravenous infusion of mesenchymal stem cells (MSCs), bilateral infiltrates were absorbed and the pulmonary function was significantly improved. We note that the intravenous infusion of CP and MSCs for the treatment of severe COVID-19 patients may have synergistic characteristics in inhibiting cytokine storm, promoting the repair of lung injury, and recovering pulmonary function. We hope to provide a reference for the research direction of COVID-19 clinical strategies.