The Ethanol Extract of Evodiae Fructus and Its Ingredient, Rutaecarpine, Inhibit Infection of SARS-CoV-2 and Inflammatory Responses.

COVID-19, derived from SARS-CoV-2, has resulted in millions of deaths and caused unprecedented socioeconomic damage since its outbreak in 2019. Although the vaccines developed against SARS-CoV-2 provide some protection, they have unexpected side effects in some people. Furthermore, new viral mutations reduce the effectiveness of the current vaccines. Thus, there is still an urgent need to develop potent non-vaccine therapeutics against this infectious disease. We recently established a series of detecting platforms to screen a large library of Chinese medicinal herbs and phytochemicals. Here, we reveal that the ethanolic extract of Evodiae Fructus and one of its components, rutaecarpine, showed promising potency in inhibiting the activity of 3C-like (3CL) protease, blocking the entry of the pseudo-typed SARS-CoV-2 (including wild-type and omicron) into cultured cells. In addition, inflammatory responses induced by pseudo-typed SARS-CoV-2 were markedly reduced by Evodiae Fructus extract and rutaecarpine. Together our data indicate that the herbal extract of Evodiae Fructus and rutaecarpine are potent anti-SARS-CoV-2 agents, which might be considered as a treatment against COVID-19 in clinical applications.

Neuromasts and Olfactory Organs of Zebrafish Larvae Represent Possible Sites of SARS-CoV-2 Pseudovirus Host Cell Entry.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the acute respiratory disease coronavirus disease 2019 (COVID-19), which has resulted in millions of deaths globally. Here, we explored the mechanism of host cell entry of a luciferase-ZsGreen spike (SARS-CoV-2)-pseudotyped lentivirus using zebrafish embryos/larvae as an in vivo model. Successful pseudovirus entry was demonstrated via the expression of the luciferase (luc) gene, which was validated by reverse transcription-PCR (RT-PCR). Treatment of larvae with chloroquine (a broad-spectrum viral inhibitor that blocks membrane fusion) or bafilomycin A1 (a specific inhibitor of vacuolar proton ATPases, which blocks endolysosomal trafficking) significantly reduced luc expression, indicating the possible involvement of the endolysosomal system in the viral entry mechanism. The pharmacological inhibition of two-pore channel (TPC) activity or use of the tpcn2dhkz1a mutant zebrafish line also led to diminished luc expression. The localized expression of ACE2 and TPC2 in the anterior neuromasts and the forming olfactory organs was demonstrated, and the occurrence of endocytosis in both locations was confirmed. Together, our data indicate that zebrafish embryos/larvae are a viable and tractable model to explore the mechanism of SARS-CoV-2 host cell entry, that the peripheral sense organs are a likely site for viral host cell entry, and that TPC2 plays a key role in the translocation of the virus through the endolysosomal system. IMPORTANCE Despite the development of effective vaccines to combat the COVID-19 pandemic, which help prevent the most life-threatening symptoms, full protection cannot be guaranteed, especially with the emergence of new viral variants. Moreover, some resistance to vaccination remains in certain age groups and cultures. As such, there is an urgent need for the development of new strategies and therapies to help combat this deadly disease. Here, we provide compelling evidence that the peripheral sensory organs of zebrafish possess several key components required for SARS-CoV-2 host cell entry. The nearly transparent larvae provide a most amenable complementary platform to investigate the key steps of viral entry into host cells, as well as its spread through the tissues and organs. This will help in the identification of key viral entry steps for therapeutic intervention, provide an inexpensive model for screening novel antiviral compounds, and assist in the development of new and more effective vaccines.

The Extracts of Polygonum cuspidatum Root and Rhizome Block the Entry of SARS-CoV-2 Wild-Type and Omicron Pseudotyped Viruses via Inhibition of the S-Protein and 3CL Protease.

COVID-19, resulting from infection by the SARS-CoV-2 virus, caused a contagious pandemic. Even with the current vaccines, there is still an urgent need to develop effective pharmacological treatments against this deadly disease. Here, we show that the water and ethanol extracts of the root and rhizome of Polygonum cuspidatum (Polygoni Cuspidati Rhizoma et Radix), a common Chinese herbal medicine, blocked the entry of wild-type and the omicron variant of the SARS-CoV-2 pseudotyped virus into fibroblasts or zebrafish larvae, with IC50 values ranging from 0.015 to 0.04 mg/mL. The extracts were shown to inhibit various aspects of the pseudovirus entry, including the interaction between the spike protein (S-protein) and the angiotensin-converting enzyme II (ACE2) receptor, and the 3CL protease activity. Out of the chemical compounds tested in this report, gallic acid, a phytochemical in P. cuspidatum, was shown to have a significant anti-viral effect. Therefore, this might be responsible, at least in part, for the anti-viral efficacy of the herbal extract. Together, our data suggest that the extracts of P. cuspidatum inhibit the entry of wild-type and the omicron variant of SARS-CoV-2, and so they could be considered as potent treatments against COVID-19.

Polygoni multiflori radix extracts inhibit SARS-CoV-2 pseudovirus entry in HEK293T cells and zebrafish larvae.

BACKGROUND: Globally, COVID-19 has caused millions of deaths and led to unprecedented socioeconomic damage. There is therefore, in addition to vaccination, an urgent need to develop complementary effective treatments and/or protective and preventative therapies against this deadly disease. METHODS: Here, a multi-component testing platform was established to screen a library of herbal extracts from traditional Chinese medicine (TCM), to identify potent herbal extracts/phytochemicals as possible therapeutics for COVID-19. We utilized assays for spike protein (S-protein) binding to angiotensin-converting enzyme II (ACE2); the enzymatic inhibition of 3CL protease; and entry of the SARS-CoV-2 pseudovirus into cultured HEK293T cells and zebrafish larvae. RESULTS: Over a thousand herbal extracts were screened and approximately 20 positive hits were identified. Among these, we found that the water and ethanol extracts of Polygoni Multiflori Radix (PMR) significantly inhibited S-protein binding to ACE2, 3CL protease activity, and viral entry into the cell and fish models. The water extract was more effective than the ethanol extract, with IC50 values of 25 to 500 µg/ml. In addition, the polysaccharide-depleted fraction of the former, and epigallocatechin gallate (EGCG) which was found in both extracts, displayed significant antiviral activity. CONCLUSIONS: Our results indicate that the water and ethanol extracts of PMR have an inhibitory effect on SARS-CoV-2 pseudovirus host-cell entry. Furthermore, EGCG might be an active component of PMR, which blocks SARS-CoV-2 entry to cells. Taken together, our findings suggest that PMR might be considered as a potential treatment for COVID-19.

Efficient markets are more connected: An entropy-based analysis of the energy, industrial metal and financial markets

This is the first article to jointly study the efficiency and connectedness of commodity markets, using the novel method combination of fuzzy entropy and multivariate transfer entropy analysis. We examine this issue in the nexus of energy, industrial metals and financial markets. We identify the existence of a relationship between market efficiency and connectedness, which opens a new direction for investigating the sources of market connectedness. The results indicate that the efficient markets process more information and are more connected in the system. Moreover, efficient markets are net transmitters of information to the less efficient markets. Stronger connectedness does not necessarily exist within the same market sector but emerges among the efficient markets irrespective of their sector categorization. The relationship between market efficiency and connectedness is more pronounced during extreme events. During the turbulence of COVID-19, there are stronger connectedness and higher information spillover from the efficient to less efficient markets. Specifically, we find the industrial metals are on average the most efficient sector, followed by the energy and then the financial markets. The relatively more efficient natural gas and industrial metal markets exhibit strong connectedness and transmit information to the less efficient crude oil and financial markets. These findings imply that the market connectedness can be the result of information dissemination and alleviate the concerns that higher connectedness may compromise the price discovery mechanism.

Polygoni Multiflori Radix extracts inhibit SARS-CoV-2 pseudovirus entry in HEK293T cells and zebrafish larvae

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Impacts of the COVID-19 Pandemic on the Bereaved: A Study of Bereaved Weibo Users.

The global COVID-19 pandemic may significantly affect the experiences of death and bereavement. This study aimed to learn from recent outbreaks of infectious diseases and further understand their impacts on bereavement. We obtained psychological status scores for 32 individuals bereaved due to COVID-19 and 127 individuals bereaved due to non-COVID-19 causes using the online ecological recognition (OER) approach. Next, a sentiment analysis and independent sample t-test were performed to examine the differences between these two groups. The results indicated that the individuals bereaved due to COVID-19 were more insecure and more preoccupied with the grief of the moment than those bereaved due to non-COVID-19 reasons, while the latter group had higher depression scores than the former group. This study can guide policy-makers and clinical practitioners to provide more targeted and sustainable post-bereavement support for both bereaved groups during the COVID-19 period.

Sudden death of COVID-19 patients in Wuhan, China: A retrospective cohort study.

BACKGROUND: In December 2019, coronavirus disease 2019 (COVID-19) emerged in Wuhan city and rapidly spread throughout China. So far, it has caused ~ 4000 deaths in this country. We aimed to systematically characterize clinical features and determine risk factors of sudden death for COVID-19 patients. METHODS: Deceased patients with COVID-19 in Tongji hospital from January 22 to March 23, 2020 were extracted. Patients who died within 24 hours after admission were identified as sudden deaths, and the others formed non-sudden deaths. The differences in clinical characteristics between the two groups were estimated. Risk factors associated with sudden deaths were explored by logistic regression. RESULTS: 281 deceased patients were enrolled in this study. Sudden death occurred in 28 (10.0%) patients, including 4 (14.3%) admitted to the intensive care unit. Fatigue was more common in sudden deaths (11, 47.8%) than in non-sudden deaths (40, 17.2%). Both the count and percentage of eosinophils were lower in sudden deaths than that in non-sudden deaths (P = 0.006 and P = 0.004). Compared with non-sudden deaths, sudden deaths had higher plasma levels of procalcitonin, C-reactive protein, D-dimer, alanine aminotransferase, aspartate aminotransferase, gamma-glutamyl transferase, lactate dehydrogenase, alkaline phosphatase and N-terminal pro-brain natriuretic peptide. There were not significant differences in gender, age, chest CT image features and comorbidities observed. CONCLUSIONS: The differences between the two groups suggested more severe systemic inflammation, multi-organ dysfunction, especially impaired liver and heart function in COVID-19 patients who died suddenly after admission. More researches are needed to verify these points.

Membrane Nanoparticles Derived from ACE2-Rich Cells Block SARS-CoV-2 Infection.

The ongoing COVID-19 pandemic worldwide necessitates the development of therapeutics against SARS-CoV-2. ACE2 is the main receptor of SARS-CoV-2 S1 and mediates viral entry into host cells. Herein, membrane nanoparticles (NPs) prepared from ACE2-rich cells were discovered to have potent capacity to block SARS-CoV-2 infection. The membranes of human embryonic kidney-239T cells highly expressing ACE2 were applied to prepare NPs using an extrusion method. The nanomaterials, termed ACE2-NPs, contained 265.1 ng mg-1 ACE2 on the surface and acted as baits to trap S1 in a dose-dependent manner, resulting in reduced recruitment of the viral ligand to HK-2 human renal tubular epithelial cells. Aside from affecting receptor recongnition, S1 translocated to the cytoplasm and induced apoptosis by reducing optic atrophy 1 expression and increasing cytochrome c release, which was also inhibited by ACE2-NPs. Further investigations revealed that ACE2-NPs efficiently suppressed SARS-CoV-2 S pseudovirions entry into host cells and blocked viral infection in vitro and in vivo. This study characterizes easy-to-produce memrbane nanoantagonists of SARS-CoV-2 that enrich the existing antiviral arsenal and provide possibilities for COVID-19 treatment.

COVID-19 and financial market efficiency: Evidence from an entropy-based analysis.

This study assesses the market efficiency of S&P 500 Index, gold, Bitcoin and US Dollar Index during the extreme event of COVID-19 pandemic. Market efficiency is estimated by a multiscale entropy-based method for the scales of hourly and 1 to 30 business days. At all scales, four markets' efficiency decreases sharply and persistently during February-March 2020. Market efficiency decreases the most in S&P 500 Index and the least in Bitcoin market. Bitcoin market efficiency is more resilient than others during the extreme event, which is an attractive feature to serve as a safe haven asset.

Repurposed Tocilizumab in Patients with Severe COVID-19.

The coronavirus disease 2019 (COVID-19) has caused a global pandemic, resulting in considerable morbidity and mortality. Tocilizumab, an inhibitor of IL-6, has been widely repurposed as a treatment of severely ill patients without robust evidence supporting its use. In this study, we aimed to systematically describe the effectiveness of treatment and prevention of the cytokine storms in COVID-19 patients with tocilizumab. In this multicentered retrospective and observational cohort study, 65 patients with COVID-19 receiving tocilizumab and 130 not receiving tocilizumab were propensity score matched at a ratio of 2:1 based on age, sex, and comorbidities from January 20, 2020 to March 18, 2020 in Wuhan, China. After adjusting for confounding, the detected risk for in-hospital death was lower in the tocilizumab group versus nontocilizumab group (hazard ratio = 0.47; 95% confidence interval = 0.25-0.90; p = 0.023). Moreover, use of tocilizumab was associated with a lower risk of acute respiratory distress syndrome (odds ratio = 0.23; 95% confidence interval = 0.11-0.45; p < 0.0001). Furthermore, patients had heightened inflammation and more dysregulated immune cells before treatment, which might aggravate disease progression. After tocilizumab administration, abnormally elevated IL-6, C-reactive protein, fibrinogen, and activated partial thromboplastin time decreased. Tocilizumab may be of value in prolonging survival in patients with severe COVID-19, which provided a novel strategy for COVID-19-induced cytokine release syndrome. Our findings could inform bedside decisions until data from randomized, controlled clinical trials become available.

Clinical and radiographic characteristics, management and short-term outcomes of patients with COVID-19 in Wenzhou, China.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is an emerging viral disease. Here, we report the clinical features, management, and short-term outcomes of COVID-19 patients in Wenzhou, China, an area outside Wuhan. METHODS: Patients admitted to the Infectious Diseases Department of Ruian People's Hospital in Wenzhou, from January 21 to February 7, 2020, were recruited. Medical data on epidemiological history, demographics, clinical characteristics, laboratory tests, chest computerized tomography (CT) examination, treatment, and short-term outcomes were retrospectively reviewed. Blood biochemistry and routine tests were examined using standard methods and automatic machines. CT examination was performed several times during hospitalization as necessary. RESULTS: A total of 67 confirmed COVID-19 cases were diagnosed; 64 (95.4%) were common cases and three (4.5%) were severe cases. The most common symptoms at admission were fever (86.6%), cough (77.6%), productive cough (52.2%), chest distress (17.9%), and sore throat (11.9%), followed by diarrhea (7.4%), headache (7.4%), shortness of breath (6.0%), dizziness (4.5%), muscular soreness (4.5%), and running nose (4.5%). Thirty patients (47.8%) had increased C-reactive protein levels. The CT radiographs at admission showed abnormal findings in 54 (80.6%) patients. The patients were treated mainly by oxygen therapy and antiviral drugs. By March 3, 2020, all 67 patients completely recovered and had negative nucleic acid tests. The patients were discharged from the hospital and transferred to a medical observation isolation center for further observation. CONCLUSION: Cases of COVID-19 in Wenzhou are milder and have a better prognosis, compared to those in Wuhan. Timely and appropriate screening, diagnosis, and treatment are the key to achieve good outcomes.

Chest Computed Tomography and Clinical Follow-Up of Discharged Patients with COVID-19 in Wenzhou City, Zhejiang, China.

Rationale: Many clinical studies have focused on the epidemiological and clinical characteristics of inpatients with coronavirus disease (COVID-19). However, there are few reports about the clinical follow-up of discharged patients.Objectives: To describe the follow-up of patients with COVID-19 in Wenzhou City, Zhejiang, China.Methods: We retrospectively reviewed 4-week follow-ups in patients with COVID-19, including computed tomographic (CT) chest scanning, blood testing, and oropharyngeal-swab testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ribonucleic acid. The chest CT scans and blood tests were performed on the last day before discharge and 2 weeks and 4 weeks after discharge. The oropharyngeal-swab tests were performed at both 1 week and 2 weeks after discharge. Fifty-one patients with common COVID-19 were enrolled in the study. All the CT and clinical data were collected between January 23 and March 28, 2020.Results: Compared with the abnormalities found on the the last CT scans before discharge, the abnormalities in the lungs at the first and second follow-ups after discharge had been gradually absorbed. The cases with focal ground-glass opacity were reduced from 17.7% to 9.8% of cases. The cases with multiple ground-glass opacities decreased from 80.4% to 23.5%. The cases with consolidation were reduced from 49.0% to 2.0%. The cases with interlobular septal thickening were reduced from 80.4% to 35.3%. The cases with subpleural lines were reduced from 29.4% to 7.8%. The cases with irregular lines were reduced from 41.2% to 15.7%. The lung lesions of 25.5% patients were shown to be fully absorbed on the first CT scans after discharge, and the rate of lung recovery increased to 64.7% after the second follow-up. Nucleic-acid test results became recurrently positive in 17.6% of discharged patients, of whom only 33.3% complained of clinical symptoms. There were no differences in the characteristics of the last CT scans before discharge between the patients with recurrently positive test results and the patients with negative test results. The lung damage was fully absorbed in 55.6% of discharged patients with recurrence of positive test results for SARS-CoV-2 ribonucleic acid.Conclusions: The lung damage due to COVID-19 could be reversible for patients with common COVID-19. A few cases showed recurring positive results of nucleic-acid tests after discharge.

COVID-19 and early-stage lung cancer both featuring ground-glass opacities: a propensity score-matched study.

BACKGROUND: Radiological manifestations of coronavirus disease 2019 (COVID-19) featured ground-glass opacities (GGOs), especially in the early stage, which might create confusion in differential diagnosis with early lung cancer. We aimed to specify the radiological characteristics of COVID-19 and early lung cancer and to unveil the discrepancy between them. METHODS: One hundred and fifty-seven COVID-19 patients and 374 early lung cancer patients from four hospitals in China were retrospectively enrolled. Epidemiological, clinical, radiological, and pathological characteristics were compared between the two groups using propensity score-matched (PSM) analysis. RESULTS: COVID-19 patients had more distinct symptoms, tended to be younger (P<0.0001), male (P<0.0001), and had a higher body mass index (P=0.014). After 1:1 PSM, 121 matched pairs were identified. Regarding radiological characteristics, patients with a single lesion accounted for 17% in COVID-19 and 89% in lung cancer (P<0.0001). Most lesions were peripherally found in both groups. Lesions in COVID-19 involved more lobes (median 3.5 vs. 1; P<0.0001) and segments (median 6 vs. 1; P<0.0001) and tended to have multiple types (67%) with patchy form (54%). Early lung cancer was more likely to have a single type (92%) with oval form (66%). Also, COVID-19 and early lung cancer either had some distinctive features on computed tomography (CT) images. CONCLUSIONS: Both COVID-19 and early lung cancers showed GGOs, with similar but independent features. The imaging characteristics should be fully understood and combined with epidemiological history, pathogen detection, laboratory tests, short-term CT reexamination, and pathological results to aid differential diagnosis.

COVID-19, supply chain disruption and China's hog market: a dynamic analysis

Purpose The authors explicitly evaluate the dynamic impact of five most concerned supply chain disruption scenarios, including: (1) a short-term shortage and price jump of corn supply in hog farms;(2) a shortage of market hogs to packing facilities;(3) disruption in breeding stock adjustments;(4) disruption in pork import;and (5) a combination of scenario (1)-(4). Design/methodology/approach The agricultural supply chain experienced tremendous disruptions from the COVID-19 pandemic. To evaluate the impact of disruptions, the authors employ a system dynamics model of hog market to simulate and project the impact of COVID-19 on China hog production and pork consumption. In the model the authors explicitly characterize the cyclical pattern of hog market. The hog cycle model is calibrated using market data from 2018-2019 to represent the market situation during an ongoing African swine fever. Findings The authors find that the impacts of supply chain disruption are generally short-lived. Market hog transportation disruption has immediate impact on price and consumption. But the impact is smoothed out in six months. Delay in import shipment temporarily reduces consumption and raises hog price. A temporary increase of corn price or delay in breeding stock acquisition does not produce significant impact on national hog market as a whole, despite mass media coverage on certain severely affected regions. Originality/value This is the first evaluation of short-term supply chain disruption on China hog market from COVID-19. The authors employ a system dynamics model of hog markets with an international trade component. The model allows for monthly time step analysis and projection of the COVID-19 impact over a five-year period. The results and discussion have far-reaching implications for agricultural markets around the world.

Differentiating novel coronavirus pneumonia from general pneumonia based on machine learning.

BACKGROUND: Chest CT screening as supplementary means is crucial in diagnosing novel coronavirus pneumonia (COVID-19) with high sensitivity and popularity. Machine learning was adept in discovering intricate structures from CT images and achieved expert-level performance in medical image analysis. METHODS: An integrated machine learning framework on chest CT images for differentiating COVID-19 from general pneumonia (GP) was developed and validated. Seventy-three confirmed COVID-19 cases were consecutively enrolled together with 27 confirmed general pneumonia patients from Ruian People's Hospital, from January 2020 to March 2020. To accurately classify COVID-19, region of interest (ROI) delineation was implemented based on ground-glass opacities (GGOs) before feature extraction. Then, 34 statistical texture features of COVID-19 and GP ROI images were extracted, including 13 gray-level co-occurrence matrix (GLCM) features, 15 gray-level-gradient co-occurrence matrix (GLGCM) features and 6 histogram features. High-dimensional features impact the classification performance. Thus, ReliefF algorithm was leveraged to select features. The relevance of each feature was the average weights calculated by ReliefF in n times. Features with relevance larger than the empirically set threshold T were selected. After feature selection, the optimal feature set along with 4 other selected feature combinations for comparison were applied to the ensemble of bagged tree (EBT) and four other machine learning classifiers including support vector machine (SVM), logistic regression (LR), decision tree (DT), and K-nearest neighbor with Minkowski distance equal weight (KNN) using tenfold cross-validation. RESULTS AND CONCLUSIONS: The classification accuracy (ACC), sensitivity (SEN), specificity (SPE) of our proposed method yield 94.16%, 88.62% and 100.00%, respectively. The area under the receiver operating characteristic curve (AUC) was 0.99. The experimental results indicate that the EBT algorithm with statistical textural features based on GGOs for differentiating COVID-19 from general pneumonia achieved high transferability, efficiency, specificity, sensitivity, and impressive accuracy, which is beneficial for inexperienced doctors to more accurately diagnose COVID-19 and essential for controlling the spread of the disease.

COVID-19 patients with progressive and non-progressive CT manifestations.

OBJECTIVE: To explore the clinical and radiological characteristics of COVID-19 patients with progressive and non-progressive CT manifestations. METHODS: 160 patients with COVID-19 were retrospectively included from Wenzhou and Wuhan, China. CT features including lesion position, attenuation, form and total scores (0-4) at the segment level were evaluated. Other images signs were also assessed. 65 patients were classified as progressive (group 1) and 95 as non-progressive CT (group 2) groups according to score changes between the initial and second CT. RESULTS: Symptoms onset-initial CT interval time in group 1 [5 (2, 7) days] were significantly shorter than that in group 2 [10 (8, 14) days] (P < 0.001). Group 2 had higher radiological scores, with more lobes and segments affected, and other CT signs (P < 0.05). In group 1, radiological scores, the number of lobes and segments affected as well as lesions in both peripheral and central distribution, mixed ground grass opacity and consolidation density, and patchy form increased in the second CT (P < 0.05). More reticular pattern, subpleural linear opacity and bronchial dilatation were also found (P < 0.05). CONCLUSION: Typically radiological characteristics of progressive CT patients could potentially help to predict changes and increase understanding of the natural history of COVID-19.

CT findings of patients infected with SARS-CoV-2.

BACKGROUND: We aimed to describe the chest CT findings in sixty-seven patients infected by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We retrospectively reviewed 67 patients hospitalized in Ruian People's Hospital. All the patients received the positive diagnosis of SARS-CoV-2 infection. The CT and clinical data were collected between January 23rd, 2020 and February 10th, 2020. The CT images were analyzed by the senior radiologists. RESULTS: There are 54 patients with positive CT findings and 13 patients with negative CT findings. The typical CT findings in hospitalized patients with SARS-CoV-2 infection were ground glass opacities (42/54), lesions located in the peripheral area (50/54), multiple lesions (46/54), and lesions located in the lower lobes (42/54). There were less typical CT findings, including air bronchogram (18/54), pleural thickening or pleural effusion (14/54), consolidation (12/54), lesions in the upper lobes (12/54), interlobular septal thickening (11/54), reversed halo sign (9/54), single lesion (8/54), air cavities (4/54), bronchial wall thickening (3/54), and intrathoracic lymph node enlargement (2/54). CONCLUSIONS: CT features can play an important role in the early diagnosis and follow-up of COVID-19 patients.

A predictive model and scoring system combining clinical and CT characteristics for the diagnosis of COVID-19.

OBJECTIVES: To develop a predictive model and scoring system to enhance the diagnostic efficiency for coronavirus disease 2019 (COVID-19). METHODS: From January 19 to February 6, 2020, 88 confirmed COVID-19 patients presenting with pneumonia and 80 non-COVID-19 patients suffering from pneumonia of other origins were retrospectively enrolled. Clinical data and laboratory results were collected. CT features and scores were evaluated at the segmental level according to the lesions' position, attenuation, and form. Scores were calculated based on the size of the pneumonia lesion, which graded at the range of 1 to 4. Air bronchogram, tree-in-bud sign, crazy-paving pattern, subpleural curvilinear line, bronchiectasis, air space, pleural effusion, and mediastinal and/or hilar lymphadenopathy were also evaluated. RESULTS: Multivariate logistic regression analysis showed that history of exposure (ß = 3.095, odds ratio (OR) = 22.088), leukocyte count (ß = - 1.495, OR = 0.224), number of segments with peripheral lesions (ß = 1.604, OR = 1.604), and crazy-paving pattern (ß = 2.836, OR = 2.836) were used for establishing the predictive model to identify COVID-19-positive patients (p < 0.05). In this model, values of area under curve (AUC) in the training and testing groups were 0.910 and 0.914, respectively (p < 0.001). A predicted score for COVID-19 (PSC-19) was calculated based on the predictive model by the following formula: PSC-19 = 2 × history of exposure (0-1 point) - 1 × leukocyte count (0-2 points) + 1 × peripheral lesions (0-1 point) + 2 × crazy-paving pattern (0-1 point), with an optimal cutoff point of 1 (sensitivity, 88.5%; specificity, 91.7%). CONCLUSIONS: Our predictive model and PSC-19 can be applied for identification of COVID-19-positive cases, assisting physicians and radiologists until receiving the results of reverse transcription-polymerase chain reaction (RT-PCR) tests. KEY POINTS: • Prediction of RT-PCR positivity is crucial for fast diagnosis of patients suspected of having coronavirus disease 2019 (COVID-19). • Typical CT manifestations are advantageous for diagnosing COVID-19 and differentiation of COVID-19 from other types of pneumonia. • A predictive model and scoring system combining both clinical and CT features were herein developed to enable high diagnostic efficiency for COVID-19.