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1.
J Med Virol ; 2022 Jul 10.
Article in English | MEDLINE | ID: covidwho-1925951

ABSTRACT

Data on safety and immunogenicity of coronavirus disease 2019 (COVID-19) vaccinations in hepatocellular carcinoma (HCC) patients are limited. In this multicenter prospective study, HCC patients received two doses of inactivated whole-virion COVID-19 vaccines. The safety and neutralizing antibody were monitored. Totally, 74 patients were enrolled from 10 centers in China, and 37 (50.0%), 25 (33.8%), and 12 (16.2%) received the CoronaVac, BBIBP-CorV, and WIBP-CorV, respectively. The vaccines were well tolerated, where pain at the injection site (6.8% [5/74]) and anorexia (2.7% [2/74]) were the most frequent local and systemic adverse events. The median level of neutralizing antibody was 13.5 (interquartile range [IQR]: 6.9-23.2) AU/ml at 45 (IQR: 19-72) days after the second dose of vaccinations, and 60.8% (45/74) of patients had positive neutralizing antibody. Additionally, lower γ-glutamyl transpeptidase level was related to positive neutralizing antibody (odds ratio = 1.022 [1.003-1.049], p = 0.049). In conclusion, this study found that inactivated COVID-19 vaccinations are safe and the immunogenicity is acceptable or hyporesponsive in patients with HCC. Given that the potential benefits may outweigh the risks and the continuing emergences of novel severe acute respiratory syndrome coronavirus 2 variants, we suggest HCC patients to be vaccinated against COVID-19. Future validation studies are warranted.

3.
J Comput Assist Tomogr ; 46(3): 413-422, 2022.
Article in English | MEDLINE | ID: covidwho-1784429

ABSTRACT

OBJECTIVE: We aimed to develop and validate the automatic quantification of coronavirus disease 2019 (COVID-19) pneumonia on computed tomography (CT) images. METHODS: This retrospective study included 176 chest CT scans of 131 COVID-19 patients from 14 Korean and Chinese institutions from January 23 to March 15, 2020. Two experienced radiologists semiautomatically drew pneumonia masks on CT images to develop the 2D U-Net for segmenting pneumonia. External validation was performed using Japanese (n = 101), Italian (n = 99), Radiopaedia (n = 9), and Chinese data sets (n = 10). The primary measures for the system's performance were correlation coefficients for extent (%) and weight (g) of pneumonia in comparison with visual CT scores or human-derived segmentation. Multivariable logistic regression analyses were performed to evaluate the association of the extent and weight with symptoms in the Japanese data set and composite outcome (respiratory failure and death) in the Spanish data set (n = 115). RESULTS: In the internal test data set, the intraclass correlation coefficients between U-Net outputs and references for the extent and weight were 0.990 and 0.993. In the Japanese data set, the Pearson correlation coefficients between U-Net outputs and visual CT scores were 0.908 and 0.899. In the other external data sets, intraclass correlation coefficients were between 0.949-0.965 (extent) and between 0.978-0.993 (weight). Extent and weight in the top quartile were independently associated with symptoms (odds ratio, 5.523 and 10.561; P = 0.041 and 0.016) and the composite outcome (odds ratio, 9.365 and 7.085; P = 0.021 and P = 0.035). CONCLUSIONS: Automatically quantified CT extent and weight of COVID-19 pneumonia were well correlated with human-derived references and independently associated with symptoms and prognosis in multinational external data sets.


Subject(s)
COVID-19 , Deep Learning , Pneumonia , COVID-19/diagnostic imaging , Humans , Retrospective Studies , Tomography, X-Ray Computed/methods
4.
Lancet Infect Dis ; 20(7): 775-776, 2020 07.
Article in English | MEDLINE | ID: covidwho-1778518
5.
Clin Gastroenterol Hepatol ; 20(8): 1893-1894, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1729616
6.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324715

ABSTRACT

Objectives: We aimed to develop and validate the automatic quantification of COVID-19 pneumonia on CT images. Methods: This retrospective study included 176 chest CT scans of 131 COVID-19 patients from 13 Korean and Chinese institutions. Two experienced radiologists semi-automatically drew pneumonia, preparing 49,830 positive and negative CT slices to develop the 2D U-Net for segmenting pneumonia. The 2D U-Net was distributed as downloadable software. External validation for quantifications’ accuracy was performed using Japanese, Italian, Radiopaedia, Chinese datasets. Primary measures for the accuracy of the network were correlation coefficients for extent (%) and weight (g) of pneumonia. Logistic regression analyses were performed to evaluate the clinical implication of the extent and weight regarding the presence of symptoms in the Japanese dataset and the occurrence of composite outcome in the Spanish dataset. Results: In the internal validation dataset, the intraclass correlation coefficients between the 2D U-Net and reference values for the extent and weight were 0.990 and 0.993, respectively. In the Japanese dataset, the Pearson correlation coefficients between the U-Net outcomes and visual CT severity scores were 0.908 and 0.899, respectively. In the other external validation datasets, the intraclass correlation coefficients between the U-Net and reference values were between 0.951-0.970 (extent) and between 0.970-0.995 (weight), respectively. In multivariate logistic regression analyses, the extent and weight of pneumonia were independently associated with symptoms (OR, 4.142 and 4.434;p=.013 and .009, respectively), and poor prognosis (OR, 7.446 and 4.677;p=.004 and .029, respectively). Conclusions: CT extent and weight of COVID-19 pneumonia were automatically quantifiable and independently associated with symptoms and prognosis.

7.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-320782

ABSTRACT

Background and Aims: COVID-19 is a dominant pulmonary disease, with multisystem involvement, depending upon co morbidities. Its profile in patients with pre-existing chronic liver disease (CLD) is largely unknown. We studied the liver injury patterns of SARS-Cov-2 in CLD patients, with or without cirrhosis. Methods: Data was collected from 13 Asian countries on patients with CLD, known or newly diagnosed, with confirmed COVID-19. Result: Altogether , 228 patients [ 185 CLD without cirrhosis and 43 with cirrhosis] were enrolled, with comorbidities in nearly 80%. Metabolism associated fatty liver disease (113, 61%) and viral etiology (26, 60%) were common. In CLD without cirrhosis, diabetes [57.7% vs 39.7%, OR=2.1(1.1-3.7), p=0.01] and in cirrhotics, obesity, [64.3% vs. 17.2%, OR=8.1(1.9-38.8), p=0.002) predisposed more to liver injury than those without these . Forty three percent of CLD without cirrhosis presented as acute liver injury and 20% cirrhotics presented with either acute-on-chronic liver failure [5(11.6%)] or acute decompensation [4(9%)]. Liver related complications increased (p<0.05) with stage of liver disease;a Child-Turcotte Pugh score of 9 or more at presentation predicted high mortality [AUROC-0.94, HR=19.2(95CI 2.3-163.3), p<0.001, sensitivity 85.7% and specificity 94.4%). In decompensated cirrhotics, the liver injury was progressive in 57% patients, with 43% mortality. Rising bilirubin and AST/ALT ratio predicted mortality among cirrhosis. Conclusions: : SARS-Cov-2 infection causes significant liver injury in CLD patients, decompensating one fifth of cirrhosis, and worsening the clinical status of the already decompensated. The CLD patients with diabetes and obesity are more vulnerable and should be closely monitored.

8.
J Hepatol ; 75(2): 439-441, 2021 08.
Article in English | MEDLINE | ID: covidwho-1454288

ABSTRACT

BACKGROUND & AIMS: The development of COVID-19 vaccines has progressed with encouraging safety and efficacy data. Concerns have been raised about SARS-CoV-2 vaccine responses in the large population of patients with non-alcoholic fatty liver disease (NAFLD). The study aimed to explore the safety and immunogenicity of COVID-19 vaccination in NAFLD. METHODS: This multicenter study included patients with NAFLD without a history of SARS-CoV-2 infection. All patients were vaccinated with 2 doses of inactivated vaccine against SARS-CoV-2. The primary safety outcome was the incidence of adverse reactions within 7 days after each injection and overall incidence of adverse reactions within 28 days, and the primary immunogenicity outcome was neutralizing antibody response at least 14 days after the whole-course vaccination. RESULTS: A total of 381 patients with pre-existing NAFLD were included from 11 designated centers in China. The median age was 39.0 years (IQR 33.0-48.0 years) and 179 (47.0%) were male. The median BMI was 26.1 kg/m2 (IQR 23.8-28.1 kg/m2). The number of adverse reactions within 7 days after each injection and adverse reactions within 28 days totaled 95 (24.9%) and 112 (29.4%), respectively. The most common adverse reactions were injection site pain in 70 (18.4%), followed by muscle pain in 21 (5.5%), and headache in 20 (5.2%). All adverse reactions were mild and self-limiting, and no grade 3 adverse reactions were recorded. Notably, neutralizing antibodies against SARS-CoV-2 were detected in 364 (95.5%) patients with NAFLD. The median neutralizing antibody titer was 32 (IQR 8-64), and the neutralizing antibody titers were maintained. CONCLUSIONS: The inactivated COVID-19 vaccine appears to be safe with good immunogenicity in patients with NAFLD. LAY SUMMARY: The development of vaccines against coronavirus disease 2019 (COVID-19) has progressed rapidly, with encouraging safety and efficacy data. This study now shows that the inactivated COVID-19 vaccine appears to be safe with good immunogenicity in the large population of patients with non-alcoholic fatty liver disease.


Subject(s)
Antibodies, Neutralizing/blood , Antibodies, Viral/blood , COVID-19 , Immunogenicity, Vaccine/immunology , Non-alcoholic Fatty Liver Disease , Vaccination , Vaccines, Inactivated , Adult , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines/administration & dosage , COVID-19 Vaccines/adverse effects , China/epidemiology , Female , Humans , Male , Non-alcoholic Fatty Liver Disease/diagnosis , Non-alcoholic Fatty Liver Disease/epidemiology , Outcome Assessment, Health Care , SARS-CoV-2/immunology , Vaccination/adverse effects , Vaccination/methods , Vaccination/statistics & numerical data , Vaccines, Inactivated/administration & dosage , Vaccines, Inactivated/adverse effects
12.
Radiol Cardiothorac Imaging ; 2(2): e200107, 2020 Apr.
Article in English | MEDLINE | ID: covidwho-1155975

ABSTRACT

PURPOSE: To study the extent of pulmonary involvement in coronavirus 19 (COVID-19) with quantitative CT and to assess the impact of disease burden on opacity visibility on chest radiographs. MATERIALS AND METHODS: This retrospective study included 20 pairs of CT scans and same-day chest radiographs from 17 patients with COVID-19, along with 20 chest radiographs of controls. All pulmonary opacities were semiautomatically segmented on CT images, producing an anteroposterior projection image to match the corresponding frontal chest radiograph. The quantitative CT lung opacification mass (QCTmass) was defined as (opacity attenuation value + 1000 HU)/1000 × 1.065 (g/mL) × combined volume (cm3) of the individual opacities. Eight thoracic radiologists reviewed the 40 radiographs, and a receiver operating characteristic curve analysis was performed for the detection of lung opacities. Logistic regression analysis was performed to identify factors affecting opacity visibility on chest radiographs. RESULTS: The mean QCTmass per patient was 72.4 g ± 120.8 (range, 0.7-420.7 g), and opacities occupied 3.2% ± 5.8 (range, 0.1%-19.8%) and 13.9% ± 18.0 (range, 0.5%-57.8%) of the lung area on the CT images and projected images, respectively. The radiographs had a median sensitivity of 25% and specificity of 90% among radiologists. Nineteen of 186 opacities were visible on chest radiographs, and a median area of 55.8% of the projected images was identifiable on radiographs. Logistic regression analysis showed that QCTmass (P < .001) and combined opacity volume (P < .001) significantly affected opacity visibility on radiographs. CONCLUSION: QCTmass varied among patients with COVID-19. Chest radiographs had high specificity for detecting lung opacities in COVID-19 but a low sensitivity. QCTmass and combined opacity volume were significant determinants of opacity visibility on radiographs.Earlier incorrect version appeared online. This article was corrected on April 6, 2020 and December 14, 2020.Supplemental material is available for this article.© RSNA, 2020.

13.
Animal Model Exp Med ; 4(1): 2-15, 2021 03.
Article in English | MEDLINE | ID: covidwho-1122088

ABSTRACT

Background: Cardiovascular diseases (CVDs) and diabetes mellitus (DM) are top two chronic comorbidities that increase the severity and mortality of COVID-19. However, how SARS-CoV-2 alters the progression of chronic diseases remain unclear. Methods: We used adenovirus to deliver h-ACE2 to lung to enable SARS-CoV-2 infection in mice. SARS-CoV-2's impacts on pathogenesis of chronic diseases were studied through histopathological, virologic and molecular biology analysis. Results: Pre-existing CVDs resulted in viral invasion, ROS elevation and activation of apoptosis pathways contribute myocardial injury during SARS-CoV-2 infection. Viral infection increased fasting blood glucose and reduced insulin response in DM model. Bone mineral density decreased shortly after infection, which associated with impaired PI3K/AKT/mTOR signaling. Conclusion: We established mouse models mimicked the complex pathological symptoms of COVID-19 patients with chronic diseases. Pre-existing diseases could impair the inflammatory responses to SARS-CoV-2 infection, which further aggravated the pre-existing diseases. This work provided valuable information to better understand the interplay between the primary diseases and SARS-CoV-2 infection.


Subject(s)
COVID-19/complications , COVID-19/physiopathology , Cardiovascular Diseases/complications , Cardiovascular Diseases/physiopathology , Diabetes Complications/physiopathology , Animals , Comorbidity , Diabetes Mellitus , Disease Models, Animal , Male , Mice , SARS-CoV-2
18.
Diagn Interv Radiol ; 27(5): 621-632, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-902820

ABSTRACT

The objective of this review was to summarize the most pertinent CT imaging findings in patients with coronavirus disease 2019 (COVID-19). A literature search retrieved eligible studies in PubMed, EMBASE, Cochrane Library and Web of Science up to June 1, 2020. A comprehensive review of publications of the Chinese Medical Association about COVID-19 was also performed. A total of 84 articles with more than 5340 participants were included and reviewed. Chest CT comprised 92.61% of abnormal CT findings overall. Compared with real-time polymerase chain reaction result, CT findings has a sensitivity of 96.14% but a low specificity of 40.48% in diagnosing COVID-19. Ground glass opacity (GGO), pure (57.31%) or mixed with consolidation (41.51%) were the most common CT features with a majority of bilateral (80.32%) and peripheral (66.21%) lung involvement. The opacity might associate with other imaging features, including air bronchogram (41.07%), vascular enlargement (54.33%), bronchial wall thickening (19.12%), crazy-paving pattern (27.55%), interlobular septal thickening (42.48%), halo sign (25.48%), reverse halo sign (12.29%), bronchiectasis (32.44%), and pulmonary fibrosis (26.22%). Other accompanying signs including pleural effusion, lymphadenopathy and pericardial effusion were rare, but pleural thickening was common. The younger or early stage patients tended to have more GGOs, while extensive/multilobar involvement with consolidation was prevalent in the older or severe population. Children with COVID-19 showed significantly lower incidences of some ancillary findings than those of adults and showed a better performance on CT during follow up. Follow-up CT showed GGO lesions gradually decreased, and the consolidation lesions first increased and then remained relatively stable at 6-13 days, and then absorbed and fibrosis increased after 14 days. Chest CT imaging is an important component in the diagnosis, staging, disease progression and follow-up of patients with COVID-19.


Subject(s)
COVID-19 , Humans , Lung , Retrospective Studies , SARS-CoV-2 , Thorax , Tomography, X-Ray Computed
19.
Postgrad Med J ; 97(1153): 706-715, 2021 Nov.
Article in English | MEDLINE | ID: covidwho-889925

ABSTRACT

OBJECTIVES: To determine how self-reported level of exposure to patients with novel coronavirus 2019 (COVID-19) affected the perceived safety, training and well-being of residents and fellows. METHODS: We administered an anonymous, voluntary, web-based survey to a convenience sample of trainees worldwide. The survey was distributed by email and social media posts from April 20th to May 11th, 2020. Respondents were asked to estimate the number of patients with COVID-19 they cared for in March and April 2020 (0, 1-30, 31-60, >60). Survey questions addressed (1) safety and access to personal protective equipment (PPE), (2) training and professional development and (3) well-being and burnout. RESULTS: Surveys were completed by 1420 trainees (73% residents, 27% fellows), most commonly from the USA (n=670), China (n=150), Saudi Arabia (n=76) and Taiwan (n=75). Trainees who cared for a greater number of patients with COVID-19 were more likely to report limited access to PPE and COVID-19 testing and more likely to test positive for COVID-19. Compared with trainees who did not take care of patients with COVID-19 , those who took care of 1-30 patients (adjusted OR [AOR] 1.80, 95% CI 1.29 to 2.51), 31-60 patients (AOR 3.30, 95% CI 1.86 to 5.88) and >60 patients (AOR 4.03, 95% CI 2.12 to 7.63) were increasingly more likely to report burnout. Trainees were very concerned about the negative effects on training opportunities and professional development irrespective of the number of patients with COVID-19 they cared for. CONCLUSION: Exposure to patients with COVID-19 is significantly associated with higher burnout rates in physician trainees.


Subject(s)
Attitude of Health Personnel , COVID-19/prevention & control , Infectious Disease Transmission, Patient-to-Professional/prevention & control , Internship and Residency/organization & administration , Adult , COVID-19/epidemiology , COVID-19/transmission , Female , Humans , Infection Control/organization & administration , Male , Personal Protective Equipment , Personnel Staffing and Scheduling , Safety , Self Report , Surveys and Questionnaires , Telemedicine , Young Adult
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