Dataset Information

SARS-associated viral hepatitis caused by a novel coronavirus: report of three cases.

ABSTRACT: Liver impairment is commonly reported in up to 60% of patients who suffer from severe acute respiratory syndrome (SARS). Here we report the clinical course and liver pathology in three SARS patients with liver impairment. Three patients who fulfilled the World Health Organization case definition of probable SARS and developed marked elevation of alanine aminotransferase were included. Percutaneous liver biopsies were performed. Liver specimens were examined by light and electron microscopy, and immunohistochemistry. Reverse-transcriptase polymerase chain reaction (RT-PCR) using enhanced real-time PCR was applied to look for evidence of SARS-associated coronavirus infection. Marked accumulation of cells in mitosis was observed in two patients and apoptosis was observed in all three patients. Other common pathologic features included ballooning of hepatocytes and mild to moderate lobular lymphocytic infiltration. No eosinophilic infiltration, granuloma, cholestasis, fibrosis, or fibrin deposition was noted. Immunohistochemical studies revealed 0.5% to 11.4% of nuclei were positive for proliferative antigen Ki-67. RT-PCR showed evidence of SARS-associated coronavirus in the liver tissues, but not in the sera of all 3 patients. However, electron microscopy could not identify viral particles. No giant mitochondria, micro- or macro-vesicular steatosis was observed. In conclusion, hepatic impairment in patients with SARS is due to SARS-associated coronavirus infection of the liver. The prominence of mitotic activity of hepatocytes is unique and may be due to a hyperproliferative state with or without disruption of cell cycle by the coronavirus. With better knowledge of pathogenesis, specific therapy may be targeted to reduce viral replication and modify the disease course.

SUBMITTER: Chau TN

PROVIDER: S-EPMC7165792 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ObjectivesTo develop and validate a radiomics model for predicting 2019 novel coronavirus (COVID-19) pneumonia.MethodsFor this retrospective study, a radiomics model was developed on the basis of a training set consisting of 136 patients with COVID-19 pneumonia and 103 patients with other types of viral pneumonia. Radiomics features were extracted from the lung parenchyma window. A radiomics signature was built on the basis of reproducible features, using the least absolute shrinkage and selection operator method (LASSO). Multivariable logistic regression model was adopted to establish a radiomics nomogram. Nomogram performance was determined by its discrimination, calibration, and clinical usefulness. The model was validated in 90 consecutive patients, of which 56 patients had COVID-19 pneumonia and 34 patients had other types of viral pneumonia.ResultsThe radiomics signature, consisting of 3 selected features, was significantly associated with COVID-19 pneumonia (p?<?0.05) in both training and validation sets. The multivariable logistic regression model included the radiomics signature and distribution; maximum lesion, hilar, and mediastinal lymph node enlargement; and pleural effusion. The individualized prediction nomogram showed good discrimination in the training sample (area under the receiver operating characteristic curve [AUC], 0.959; 95% confidence interval [CI], 0.933-0.985) and in the validation sample (AUC, 0.955; 95% CI, 0.899-0.995) and good calibration. The mixed model achieved better predictive efficacy than the clinical model. Decision curve analysis demonstrated that the radiomics nomogram was clinically useful.ConclusionsThe radiomics model derived has good performance for predicting COVID-19 pneumonia and may help in clinical decision-making.Key points• A radiomics model showed good performance for prediction 2019 novel coronavirus pneumonia and favorable discrimination for other types of pneumonia on CT images. • A central or peripheral distribution, a maximum lesion range?>?10 cm, the involvement of all five lobes, hilar and mediastinal lymph node enlargement, and no pleural effusion is associated with an increased risk of 2019 novel coronavirus pneumonia. • A radiomics model was superior to a clinical model in predicting 2019 novel coronavirus pneumonia.

Dataset Information

SARS-associated viral hepatitis caused by a novel coronavirus: report of three cases.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets