Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has progressed to a pandemic associated with substantial morbidity and mortality. The WHO and the United States Center for Disease Control and Prevention (CDC) have issued interim clinical guidance for management of patients with confirmed coronavirus disease (COVID-19), but there is limited data on the virologic and clinical characteristics for prognosis of severe COVID-19. Methods: A total of 50 patients with severe COVID-19 were divided into good and poor recovery groups. The dynamic viral shedding and serological characteristics of SARS-CoV-2 were explored. The risk factors associated with poor recovery and lung lesion resolutions were identified. In addition, the potential relationships among the viral shedding, the pro-inflammatory response, and lung lesion evolutions were characterized. Results: A total of 58% of the patients had poor recovery and were more likely to have a prolonged interval of viral shedding. The longest viral shedding was 57 days after symptom onset. Older age, hyperlipemia, hypoproteinemia, corticosteroid therapy, consolidation on chest computed-tomography (CT), and prolonged SARS-CoV-2 IgM positive were all associated with poor recovery. Additionally, the odds of impaired lung lesion resolutions were higher in patients with hypoproteinemia, hyperlipemia, and elevated levels of IL-4 and ferritin. Finally, viral shedding and proinflammatory responses were closely correlated with lung lesion evolutions on chest CT. Conclusions: Patients with severe COVID-19 have prolonged SARS-CoV-2 infection and delayed intermittent viral shedding. Older age, hyperlipemia, hypoproteinemia, corticosteroid usage, and prolonged SARS-CoV-2 IgM positive might be utilized as predicative factors for the patients with poor recovery.

Objective: Patients with decompensated hepatitis B virus (HBV)- and hepatitis C virus (HCV)-related cirrhosis are at high risk of first variceal bleeding, yet etiology-specific and stage-specific prediction models remain limited. This study aimed to develop and internally validate nomogram models for predicting the risk of first variceal bleeding in this population. Methods: This retrospective cohort study included 451 patients with decompensated HBV- or HCV-related cirrhosis (331 HBV-related and 120 HCV-related), of whom 230 experienced first variceal bleeding. Random Forest and XGBoost algorithms were used for feature selection, followed by multivariable logistic regression to develop etiology-specific nomogram models. Internal validation was performed using a training-testing split. Model discrimination, calibration, and clinical utility were assessed using the area under the receiver operating characteristic curve (AUC), bootstrap resampling, and decision curve analysis, respectively. Partial Dependence Plots (PDPs) midpoint risk (≈ 0.5) set clinical thresholds. Results: Seven predictors were retained for HBV (Hemoglobin, Ascites Depth, Total Protein, Prothrombin Activity [PTA], Total Bile Acid [TBA], D-dimer, and White Blood Cell Count [WBC]) and three for HCV (Hemoglobin, PTA, and TBA), with an AUC of 0.9239 (95% CI 0.8941– 0.9537) and 0.9127 (95% CI 0.8646– 0.9609), respectively. The models showed good calibration and clinical utility on decision curve analysis. PDPs indicated 0.5-risk thresholds at 96.12 g/L (Hemoglobin), 60.75 g/L (Total Protein), 30.58 mm (Ascites Depth), 49.2% (PTA), 25.78 μmol/L (TBA), 2.24 mg/L (D-dimer), and 5.33× 10⁹/L (WBC) for HBV, and 46.81% (PTA), 82.4 g/L (Hemoglobin), 47.51 μmol/L (TBA) for HCV. Conclusion: Etiology-specific nomogram models were developed to predict first variceal bleeding in patients with decompensated HBV- and HCV-related cirrhosis. The models showed good discriminative performance in internal validation and may assist in risk stratification. However, further prospective multicenter studies with external validation are needed before clinical implementation.