Coronavirus disease (COVID-19): a scoping review.

BackgroundIn December 2019, a pneumonia caused by a novel coronavirus (SARS-CoV-2) emerged in Wuhan, China and has rapidly spread around the world since then.AimThis study aims to understand the research gaps related to COVID-19 and propose recommendations for future research.MethodsWe undertook a scoping review of COVID-19, comprehensively searching databases and other sources to identify literature on COVID-19 between 1 December 2019 and 6 February 2020. We analysed the sources, publication date, type and topic of the retrieved articles/studies.ResultsWe included 249 articles in this scoping review. More than half (59.0%) were conducted in China. Guidance/guidelines and consensuses statements (n = 56; 22.5%) were the most common. Most (n = 192; 77.1%) articles were published in peer-reviewed journals, 35 (14.1%) on preprint servers and 22 (8.8%) posted online. Ten genetic studies (4.0%) focused on the origin of SARS-CoV-2 while the topics of molecular studies varied. Nine of 22 epidemiological studies focused on estimating the basic reproduction number of COVID-19 infection (R0). Of all identified guidance/guidelines (n = 35), only ten fulfilled the strict principles of evidence-based practice. The number of articles published per day increased rapidly until the end of January.ConclusionThe number of articles on COVID-19 steadily increased before 6 February 2020. However, they lack diversity and are almost non-existent in some study fields, such as clinical research. The findings suggest that evidence for the development of clinical practice guidelines and public health policies will be improved when more results from clinical research becomes available.

SARS-CoV-2 infection aggravates chronic comorbidities of cardiovascular diseases and diabetes in mice.

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.

Safety and immunogenicity of COVID-19 vaccination in patients with hepatocellular carcinoma (CHESS-NMCID 2101): A multicenter prospective study.

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.

Deep Learning-Based Automatic CT Quantification of Coronavirus Disease 2019 Pneumonia: An International Collaborative Study.

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.

Safety and immunogenicity of COVID-19 vaccination in patients with non-alcoholic fatty liver disease (CHESS2101): A multicenter study.

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.

Erratum: Extension of Coronavirus Disease 2019 (COVID-19) on Chest CT and Implications for Chest Radiograph Interpretation.

[This corrects the article DOI: 10.1148/ryct.2020200107.].

Erratum: Extension of Coronavirus Disease 2019 on Chest CT and Implications for Chest Radiographic Interpretation.

[This corrects the article DOI: 10.1148/ryct.2020200107.].

Extension of Coronavirus Disease 2019 on Chest CT and Implications for Chest Radiographic Interpretation.

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.

Chest CT findings in patients with coronavirus disease 2019 (COVID-19): a comprehensive review.

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.

Impact of exposure to patients with COVID-19 on residents and fellows: an international survey of 1420 trainees.

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.

Machine learning-based CT radiomics method for predicting hospital stay in patients with pneumonia associated with SARS-CoV-2 infection: a multicenter study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) has become a global challenge since the December 2019. The hospital stay is one of the prognostic indicators, and its predicting model based on CT radiomics features is important for assessing the patients' clinical outcome. The study aimed to develop and test machine learning-based CT radiomics models for predicting hospital stay in patients with COVID-19 pneumonia. METHODS: This retrospective, multicenter study enrolled patients with laboratory-confirmed SARS-CoV-2 infection and their initial CT images from 5 designated hospitals in Ankang, Lishui, Lanzhou, Linxia, and Zhenjiang between January 23, 2020 and February 8, 2020. Patients were classified into short-term (≤10 days) and long-term hospital stay (>10 days). CT radiomics models based on logistic regression (LR) and random forest (RF) were developed on features from pneumonia lesions in first four centers. The predictive performance was evaluated in fifth center (test dataset) on lung lobe- and patients-level. RESULTS: A total of 52 patients were enrolled from designated hospitals. As of February 20, 21 patients remained in hospital or with non-findings in CT were excluded. Therefore, 31 patients with 72 lesion segments were included in analysis. The CT radiomics models based on 6 second-order features were effective in discriminating short- and long-term hospital stay in patients with COVID-19 pneumonia, with areas under the curves of 0.97 (95% CI, 0.83-1.0) and 0.92 (95% CI, 0.67-1.0) by LR and RF, respectively, in test. The LR and RF model showed a sensitivity and specificity of 1.0 and 0.89, 0.75 and 1.0 in test respectively. As of February 28, a prospective cohort of six discharged patients were all correctly recognized as long-term stay using RF and LR models. CONCLUSIONS: The machine learning-based CT radiomics features and models showed feasibility and accuracy for predicting hospital stay in patients with COVID-19 pneumonia.

Clinical characteristics of coronavirus disease 2019 in Gansu province, China.

BACKGROUND: The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has outbreak in the world. Little is known about the clinical characteristics of patients with SARS-CoV-2 infection in the high-altitude region of China. We reported the clinical characteristics of patients with coronavirus disease 2019 (COVID-19) in Gansu province, China. METHODS: In this retrospective study, patients with laboratory-confirmed SARS-CoV-2 infection were consecutively enrolled from January 21, 2020 to February 11, 2020. The information on the epidemiological, clinical characteristics, laboratory tests, radiological features on admission, treatment and outcome were obtained with the final follow-up of March 13, 2020. On the basis of the median length of hospital stay, patients were further analyzed in two groups (long- vs. short-hospital stay). RESULTS: Of the 86 patients of COVID-19 in 11 cities of Gansu Province, the median hospital stay was 14.0 days (interquartile rang, 11.0-19.0 days). In the overall cohort, the median age was 41.0 years (interquartile rang, 31.0-54.3 years), and 48 (55.8%) patients were female. Forty (46.5%) had a history of exposure to epidemic regions, but none exposed to the Huanan seafood market in Wuhan. Common symptoms included fever (41, 47.7%), and cough (37, 43.0%). On admission, 30 (34.9%) and 58 (67.4%) patients had leukopenia and lymphopenia. According to chest CT scans, 53 (66.3%) of 80 patients showed bilateral pneumonia, and 19 (23.8%) of 80 patients showed unilateral pneumonia. Of the 15 asymptomatic cases, 10 (66.6%) cases were found CT findings of pneumonia. Besides, there were 65 (75.6%) patients with mild and moderate type of COVID-19. All 86 patients received antiviral and traditional Chinese medicine therapy, 53 (61.6%) received antibacterial therapy, and 3 (3.5%) patients received invasive ventilator mechanical ventilation. The proportion of patients received antibiotic treatment in long-hospital stay group was significantly higher than that in the short-hospital stay group (P=0.045). As of March 13, 2020, 84 (97.7%) patients were discharged, and two (2.3%) cases died. CONCLUSIONS: In the Gansu province cohort of 86 patients of COVID-19, most patients were with mild or moderate type, and most asymptomatic cases showed CT imaging findings of SARS-CoV-2 related pneumonia.

Systematic review with meta-analysis: liver manifestations and outcomes in COVID-19.

BACKGROUND: The incidence of elevated liver chemistries and the presence of pre-existing chronic liver disease (CLD) have been variably reported in COVID-19. AIMS: To assess the prevalence of CLD, the incidence of elevated liver chemistries and the outcomes of patients with and without underlying CLD/elevated liver chemistries in COVID-19. METHODS: A comprehensive search of electronic databases from 1 December 2019 to 24 April 2020 was done. We included studies reporting underlying CLD or elevated liver chemistries and patient outcomes in COVID-19. RESULTS: 107 articles (n = 20 874 patients) were included for the systematic review. The pooled prevalence of underlying CLD was 3.6% (95% CI, 2.5-5.1) among the 15 407 COVID-19 patients. The pooled incidence of elevated liver chemistries in COVID-19 was 23.1% (19.3-27.3) at initial presentation. Additionally, 24.4% (13.5-40) developed elevated liver chemistries during the illness. The pooled incidence of drug-induced liver injury was 25.4% (14.2-41.4). The pooled prevalence of CLD among 1587 severely infected patients was 3.9% (3%-5.2%). The odds of developing severe COVID-19 in CLD patients was 0.81 (0.31-2.09; P = 0.67) compared to non-CLD patients. COVID-19 patients with elevated liver chemistries had increased risk of mortality (OR-3.46 [2.42-4.95, P < 0.001]) and severe disease (OR-2.87 [95% CI, 2.29-3.6, P < 0.001]) compared to patients without elevated liver chemistries. CONCLUSIONS: Elevated liver chemistries are common at presentation and during COVID-19. The severity of elevated liver chemistries correlates with the outcome of COVID-19. The presence of CLD does not alter the outcome of COVID-19. Further studies are needed to analyse the outcomes of compensated and decompensated liver disease.

Pre-existing liver disease is associated with poor outcome in patients with SARS CoV2 infection; The APCOLIS Study (APASL COVID-19 Liver Injury Spectrum Study).

BACKGROUND AND AIMS: COVID-19 is a dominant pulmonary disease, with multisystem involvement, depending upon comorbidities. 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. RESULTS: 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 (95 CI 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 patients. 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.