Quantitative CT for detecting COVID­19 pneumonia in suspected cases.

BACKGROUND: Corona Virus Disease 2019 (COVID-19) is currently a worldwide pandemic and has a huge impact on public health and socio-economic development. The purpose of this study is to explore the diagnostic value of the quantitative computed tomography (CT) method by using different threshold segmentation techniques to distinguish between patients with or without COVID-19 pneumonia. METHODS: A total of 47 patients with suspected COVID-19 were retrospectively analyzed, including nine patients with positive real-time fluorescence reverse transcription polymerase chain reaction (RT-PCR) test (confirmed case group) and 38 patients with negative RT-PCR test (excluded case group). An improved 3D convolutional neural network (VB-Net) was used to automatically extract lung lesions. Eight different threshold segmentation methods were used to define the ground glass opacity (GGO) and consolidation. The receiver operating characteristic (ROC) curves were used to compare the performance of various parameters with different thresholds for diagnosing COVID-19 pneumonia. RESULTS: The volume of GGO (VOGGO) and GGO percentage in the whole lung (GGOPITWL) were the most effective values for diagnosing COVID-19 at a threshold of - 300 HU, with areas under the curve (AUCs) of 0.769 and 0.769, sensitivity of 66.67 and 66.67%, specificity of 94.74 and 86.84%. Compared with VOGGO or GGOPITWL at a threshold of - 300 Hounsfield units (HU), the consolidation percentage in the whole lung (CPITWL) with thresholds at - 400 HU, - 350 HU, and - 250 HU were statistically different. There were statistical differences in the infection volume and percentage of the whole lung, right lung, and lobes between the two groups. VOGGO, GGOPITWL, and volume of consolidation (VOC) were also statistically different at the threshold of - 300 HU. CONCLUSIONS: Quantitative CT provides an image quantification method for the auxiliary diagnosis of COVID-19 and is expected to assist in confirming patients with COVID-19 pneumonia in suspected cases.

Transcriptome Classification Reveals Molecular Subgroups in Patients with Hepatitis B Virus.

Hepatitis B virus (HBV) specifically infects hepatocytes, which can cause progressive liver fibrosis and a significantly increased risk of liver cancer. Multiple studies indicated host genetic, virological, and immunological factors could affect the HBV infection. However, the underlying mechanism involved in HBV infection remained unclear. Based on the analysis of gene expression data of 124 HBV patients (GEO accession: GSE84044), molecular subgroups of patients infected with hepatitis B virus were identified in this study, including C1, C2, and C3 groups. The age, fiber, degree of chemical and inflammation, and gene expression difference were also compared among the three sampling groups. Furthermore, the liver index was calculated using 93 liver-specific genes. The liver-specific gene expression in different molecular subgroups of HBV patients was thoroughly analyzed and then was compared with fibrosis and inflammation levels. Results showed that the C2 group was the youngest and the C3 group had the highest degree of fibrosis and inflammation. Enrichment analysis showed that metabolism-related pathways were mainly expressed in the C1 and C2 groups, and inflammation-related pathways and proteoglycans in cancer were highly expressed in the C1 and C3 groups. The liver index was higher in the C2 group than in the C1 and C3 groups, and it was the lowest in the C3 group. Macrophage M1/M2 and neutrophils were significantly different in the three groups. M1 was mainly abundant in the C3 group, and M2 and neutrophils were mainly abundant in the C2 group. This study provides novel information to understand the mechanisms of HBV infection in chronic hepatitis B (CHB) patients.

Rescue therapy for lamivudine-resistant chronic hepatitis B: adefovir monotherapy, adefovir plus lamivudine or entecavir combination therapy.

OBJECTIVE: We aimed to compare the cumulative efficacy and resistance of ADV monotherapy, ADV add-on LAM (ADV + LAM), ADV and ETV (ADV + ETV) combination therapy in LAM-resistant patients. METHODS: Ninety-one adult CHB patients with LAM-resistance mutations (YMDD) were identified. Of these 91, 29 patients were treated with ADV monotherapy, 30 were treated with ADV + LAM and 32 were treated with ADV + ETV combination therapy, for at least 24 months. RESULTS: The mean serum HBV-DNA decreases from baseline at 3, 6, 12, and 24 months were -3.23, -4.41, -5.32, and -5.58 log(10) IU/mL in the ADV + ETV combination therapy groups, respectively; the most significant among the three treatment groups (p<0.01). The rate of HBV-DNA PCR undetectability (<60 IU/mL) at 6 months in ADV + ETV combination therapy was 78.1%; also the most significant among the three treatment groups (p=0.024). Viral breakthrough and genotypic mutations were detected in 8 (27.6%) and 4 (13.3%) patients in the ADV monotherapy and ADV+LAM therapy groups, respectively; whereas no case of viral breakthrough and genotypic resistance was detected in the ADV+ETV combination therapy group after 24 months (p<0.05). CONCLUSION: ADV + ETV combination therapy demonstrated faster and significantly greater suppression of HBV DNA compared with ADV add-on LAM combination therapy for patients with LAM-resistance mutations. ADV + ETV was superior to ADV + LAM in achieving initial virological response and long-term suppression activity against HBV. ADV + ETV combination therapy was the most effective to refrain from selecting HBV strains with cross-resistance to three NAs (LAM, ADV and ETV) for LAM-resistance patients.

A prospective clinical study in hepatitis B e antigen-negative chronic hepatitis B patients with stringent cessation criteria for adefovir.

Adefovir is usually applied for therapy of chronic hepatitis B (CHB), but its effectiveness after cessation is still unknown. This study was to evaluate the effectiveness of adefovir treatment with strict cessation criteria in hepatitis B e antigen (HBeAg)-negative patients and to identify potentially important factors. One hundred forty-five HBeAg-negative CHB patients who had received adefovir treatment for at least 24 months and for whom serum hepatitis B virus (HBV) DNA had remained undetectable for at least 18 months before cessation were included. They were followed up monthly during the first four months and at 3-month or 6-month intervals thereafter. Patients with ≥10(4) copies of HBV DNA per mL were defined as relapsed. In total, 95 patients relapsed within the follow-up time, and more than 93% relapsed within 12 months after adefovir cessation. Cumulative relapse rates at months 6, 12, 24, 36, 48 and 60 were 53.8%, 61.4%, 65.5%, 65.5%, 65.5% and 65.5%, respectively. Age was the only factor associated with relapse, with lower relapse rates in younger patients shown by Cox regression analysis. HBsAg seroconversion occurred in 12 patients, and none of them relapsed during follow-up. The effectiveness of adefovir therapy does not persist in HBeAg-negative CHB patients, even when strict cessation criteria are applied, except for patients aged ≤ 25 years. HBsAg seroconversion is the ideal endpoint of adefovir treatment.