Coronavirus Disease 2019 (COVID-19): A Perspective from China

Attitudes, Anxiety, and Behavioral Practices Regarding COVID-19 among University Students in Jordan: A Cross-Sectional Study

The COVID-19 pandemic represents a major public health, economic, political, and scientific concern in most countries around the globe where COVID-19 cases and deaths have been confirmed. This study assessed the attitudes, anxiety, and behavioral practices of university students in Jordan regarding COVID-19 during the early period of the infection (March 19-21, 2020) using a validated, self-administered survey questionnaire. Positive attitudes or low-risk practices were given 1 point, whereas negative attitudes or high-risk practices were scored 0. Percentages of the total score were used for categorizing data into negative attitudes or high-risk practices (≤ 60%), moderate attitudes or moderate-risk practices (60.01-80%), and positive attitudes or low-risk practices (> 80%). Generally, the university students displayed positive attitudes and low-risk practices toward preventing COVID-19, with an average score of 81.1% and 84.3%, respectively. Approximately two-thirds (69.1%) of the students showed a positive attitude toward COVID-19 seriousness, concern of contracting the virus, and the appropriate prevention measures, and low-risk practices (67.6%) toward preventing COVID-19 including implementation of social distancing and good hygiene. Female, older, medical, or postgraduate students practiced significantly more (P ≤ 0.05) appropriate hygiene and social distancing behaviors toward COVID-19 than their counterparts of each group. More than two-thirds (69.2%) of the students were anxious that they might become infected with COVID-19. These results are important for health authorities to develop appropriate educational programs and protective health measures including good respiratory etiquette and handwashing practices, to enhance safer lifestyles and prevent COVID-19 transmission.

Overview of coronavirus disease 2019: Treatment updates and advances

In late December 2019, several cases of pneumonia with unknown cause were reported in Wuhan, China, and this new type of pneumonia spread rapidly to across provinces during the subsequent weeks. The pathogen was identified quickly and was named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The infectious disease caused by this virus is referred to as coronavirus disease 2019 (COVID-19). Within months, it has caused a global pandemic and posed a major threat to public health worldwide. As of May 23, 2020, 5 252 452 patients have been confirmed to have the disease, and 339 026 deaths have been reported. Multiple therapeutic trials are ongoing, and some promising results have been released. A vaccine would provide the most effective approach to fight the virus by preventing infection, but none are currently available. To control the COVID-19 outbreak, large-scale measures have been applied to reduce human-to-human transmission of SARS-CoV-2. Susceptible populations, including older adults, children, and healthcare providers, warrant particular attention to avoid transmission and infection. This review introduces current understanding of SARS-CoV-2 infection and treatment strategies, emphasizing the relevant challenges associated with prevention, diagnosis, and management.

Recent progress and challenges in drug development against COVID-19 coronavirus (SARS-CoV-2) - an update on the status

Coronaviruses are a large group of viruses known to cause illnesses that vary between the common cold and more severe diseases to include severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). A novel coronavirus was identified in December 2019 in Wuhan city, Hubei province, China. This virus represents a new strain that has not been previously identified in humans. The virus is now known as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the resulting disease is called coronavirus disease 2019 (COVID-19). The World Health Organization (WHO) declared the novel coronavirus outbreak a global pandemic in March 2020. Despite rigorous global containment and quarantine efforts, the incidence of COVID-19 continues to rise, with more than 1,948,617 laboratory-confirmed cases and over 121,846 deaths worldwide. Currently, no specific medication is recommended to treat COVID-19 patients. However, governments and pharmaceutical companies are struggling to quickly find an effective drug to defeat the coronavirus. In the current review, we summarize the existing state of knowledge about COVID-19, available medications, and treatment options. Favilavir is an antiviral drug that is approved in Japan for common influenza treatment and is now approved to treat symptoms of COVID-19 in China. Moreover, Chloroquine and hydroxychloroquine, drugs used to treat malaria and arthritis, respectively, were recommended by the National Health Commission of the People's Republic of China for treatment of COVID-19. Presently, chloroquine and hydroxychloroquine are under investigation by the US Food and Drug Administration (FDA) as a treatment for COVID-19. The first COVID-19 vaccine is not expected to be ready for clinical trials before the end of the year.

Evaluation of bacterial co-infections of the respiratory tract in COVID-19 patients admitted to ICU

Background

COVID-19 is known as a new viral infection. Viral-bacterial co-infections are one of the biggest medical concerns, resulting in increased mortality rates. To date, few studies have investigated bacterial superinfections in COVID-19 patients. Hence, we designed the current study on COVID-19 patients admitted to ICUs.

Methods

Nineteen patients admitted to our ICUs were enrolled in this study. To detect COVID-19, reverse transcription real-time polymerase chain reaction was performed. Endotracheal aspirate samples were also collected and cultured on different media to support the growth of the bacteria. After incubation, formed colonies on the media were identified using Gram staining and other biochemical tests. Antimicrobial susceptibility testing was carried out based on the CLSI recommendations.

Results

Of nineteen COVID-19 patients, 11 (58%) patients were male and 8 (42%) were female, with a mean age of ~ 67 years old. The average ICU length of stay was ~ 15 days and at the end of the study, 18 cases (95%) expired and only was 1 case (5%) discharged. In total, all patients were found positive for bacterial infections, including seventeen Acinetobacter baumannii (90%) and two Staphylococcus aureus (10%) strains. There was no difference in the bacteria species detected in any of the sampling points. Seventeen of 17 strains of Acinetobacter baumannii were resistant to the evaluated antibiotics. No metallo-beta-lactamases -producing Acinetobacter baumannii strain was found. One of the Staphylococcus aureus isolates was detected as methicillin-resistant Staphylococcus aureus and isolated from the patient who died, while another Staphylococcus aureus strain was susceptible to tested drugs and identified as methicillin-sensitive Staphylococcus aureus.

Conclusions

Our findings emphasize the concern of superinfection in COVID-19 patients due to Acinetobacter baumannii and Staphylococcus aureus. Consequently, it is important to pay attention to bacterial co-infections in critical patients positive for COVID-19.

Current role of imaging in COVID-19 infection with recent recommendations of point of care ultrasound in the contagion: a narrative review

Radiological studies have an important role in the diagnosis and follow up of many infectious diseases. With current pandemic of Coronavirus disease 2019 (COVID-19) though the molecular analysis with reverse transcriptase polymerase chain reaction (RT-PCR) remains the cornerstone of diagnosis, the critical role of chest imaging including CT scan and baseline X-ray became apparent early in the course due to concern for less than optimal sensitivity of PCR testing. Delay in molecular diagnosis due to a shortage of testing kits and laboratory personnel also makes imaging an important modality in early diagnosis for appropriate triage and isolation decisions. CT scan technology is widely available in developed parts of the world but in developing countries, CT scanner is not widely available especially in rural settings. CT imaging usually requires patient movement to the radiology department and the scanner is not easy to disinfect. Point of care ultrasound (POCUS) has been used for many years in the assessment of critically ill patients in emergency departments and intensive care units. It is rapidly gaining popularity across many specialties and part of many general medicine training programs across the United States. It can be learned rapidly and with experienced hands, POCUS can help identify disease patterns in the lung parenchyma, and during the current pandemic has been gaining special attention. In this article, we review the most prominent imaging findings on chest X-ray and CT scan in patients with COVID-19. We also focus on the background and evolution of POCUS with studies showing the promising role of this diagnostic modality in COVID-19 infection. In addition, we describe step by step guidance on the use and disinfection of the portable ultrasound machine.

Observer agreement and clinical significance of chest CT reporting in patients suspected of COVID-19

Objectives

To assess interobserver agreement and clinical significance of chest CT reporting in patients suspected of COVID-19.

Methods

From 16 to 24 March 2020, 241 consecutive patients addressed to hospital for COVID-19 suspicion had both chest CT and SARS-CoV-2 RT-PCR. Eight observers (2 thoracic and 2 general senior radiologists, 2 junior radiologists, and 2 emergency physicians) retrospectively categorized each CT into one out of 4 categories (evocative, compatible for COVID-19 pneumonia, not evocative, and normal). Observer agreement for categorization between all readers and pairs of readers with similar experience was evaluated with the Kappa coefficient. The results of a consensus categorization were correlated to RT-PCR.

Results

Observer agreement across the 4 categories was good between all readers (κ value 0.61 95% CI 0.60–0.63) and moderate to good between pairs of readers (0.54–0.75). It was very good (κ 0.81 95% CI 0.79–0.83), fair (κ 0.32 95% CI 0.29–0.34), moderate (κ 0.56 95% CI 0.54–0.58), and moderate (0.58 95% CI 0.56–0.61) for the categories evocative, compatible, not evocative, and normal, respectively. RT-PCR was positive in 97%, 50%, 31%, and 11% of cases in the respective categories. Observer agreement was lower (p < 0.001) and RT-PCR positive cases less frequently categorized evocative in the presence of an underlying pulmonary disease (p < 0.001).

Conclusion

Interobserver agreement for chest CT reporting using categorization of findings is good in patients suspected of COVID-19. Among patients considered for hospitalization in an epidemic context, CT categorized evocative is highly predictive of COVID-19, whereas the predictive value of CT decreases between the categories compatible and not evocative.

Key Points

• In patients suspected of COVID-19, interobserver agreement for chest CT reporting into categories is good, and very good to categorize CT “evocative.”

• Chest CT can participate in estimating the likelihood of COVID-19 in patients presenting to hospital during the outbreak, CT categorized “evocative” being highly predictive of the disease whereas almost a third of patients with CT “not evocative” had a positive RT-PCR in our study.

• Observer agreement is lower and CTs of positive RT-PCR cases less frequently “evocative” in presence of an underlying pulmonary disease.

Detecting the Coronavirus (COVID-19)

The COVID-19 pandemic has created huge damage to society and brought panic around the world. Such panic can be ascribed to the seemingly deceptive features of COVID-19: Compared to other deadly viral outbreaks, it has medium transmission and mortality rates. As a result, the severity of the causative coronavirus, SARS-CoV-2, was deeply underestimated by society at the beginning of the COVID-19 outbreak. Based on this, in this review, we define the viruses with features similar to those of SARS-CoV-2 as the Panic Zone viruses. To contain those viruses, accurate and fast diagnosis followed by effective isolation and treatment of patients are pivotal at the early stage of virus breakouts. This is especially true when there is no cure or vaccine available for a transmissible disease, which is the case for the current COVID-19 pandemic. As of July 2020, more than 100 kits for COVID-19 diagnosis on the market have been surveyed in this review, while emerging sensing techniques for SARS-CoV-2 are also discussed. It is of critical importance to rationally use these kits for efficient management and control of the Panic Zone viruses. Therefore, we discuss guidelines to select diagnostic kits at different outbreak stages of the Panic Zone viruses, SARS-CoV-2 in particular. While it is of utmost importance to use nucleic acid based detection kits with low false negativity (high sensitivity) at the early stage of an outbreak, the low false positivity (high specificity) gains importance at later stages of the outbreak. When society is set to reopen from the lockdown stage of the COVID-19 pandemic, it becomes critical to have immunoassay based kits with high specificity to identify people who can safely return to society after their recovery from SARS-CoV-2 infections. Finally, since a massive attack from a viral pandemic requires a massive defense from the whole society, we urge both government and the private sector to research and develop affordable and reliable point-of-care testing (POCT) kits, which can be used massively by the general public (and therefore called massive POCT) to contain Panic Zone viruses in the future.

Protocol for the process evaluation of the Promoting Activity, Independence and Stability in Early Dementia (PrAISED), following changes required by the COVID-19 pandemic

INTRODUCTION

The Promoting Activity, Independence and Stability in Early Dementia (PrAISED) randomised controlled trial (RCT) is evaluating a home-based, face-to-face, individually tailored, activity and exercise programme for people living with dementia. Social distancing requirements following the COVID-19 pandemic necessitated rapid changes to intervention delivery.

METHODS AND ANALYSIS

A mixed-methods process evaluation will investigate how the changes were implemented and the impact that these have on participants' experience. An implementation study will investigate how the intervention was delivered during the pandemic. A study on the mechanisms of impact and context will investigate how these changes were experienced by the PrAISED participants, their carers and the therapists delivering the intervention. The study will commence in May 2020.

ETHICS AND DISSEMINATION

The PrAISED RCT and process evaluation have received ethical approval number 18/YH/0059. The PrAISED process evaluation will enable us to understand how distancing and isolation affected participants, their activity and exercise routines and whether the therapy programme could be continued with remote support. This will be valuable both in explaining trial results and also contribute to understanding and designing new ways of delivering home-based services and rehabilitation interventions for people with dementia and their carers.

TRIAL REGISTRATION NUMBER

ISRCTN15320670; Pre-results.

Clinical course and findings of 14 patients with COVID-19 compared with 5 patients with conventional human coronavirus pneumonia

OBJECTIVE

To clarify what future problems must be resolved and how clinical findings of SARS-CoV-2 infection differ from those of cHCoV infection.

METHODS

Patients and Methods Clinical characteristics of 14 patients with laboratory-confirmed Coronavirus disease 2019 (COVID-19) and 5 patients with cHCoV pneumonia admitted to our institution and treated up to March 8, 2020, were retrospectively analyzed.

RESULTS

On admission, 10 patients had pneumonia, 5 of whom had pulmonary shadows detectable only via computed tomography (CT). During hospitalization, another patient with no pulmonary shadows on admission developed pneumonia. In total, 11 (78.6%) of the 14 patients developed pneumonia, indicating its high prevalence in COVID-19. During hospitalization, the patients' symptoms spontaneously relapsed and resolved, and gastrointestinal symptoms were frequently found. C-reactive protein values showed correlation with the patients' clinical courses. Ritonavir/lopinavir were administered to 5 patients whose respiratory conditions worsened during admission, all of whom improved. However, the pneumonia in the 6 other patients improved without antivirals. None of the 14 patients died, whereas 5 other patients with cHCoV pneumonia were in respiratory failure on admission, and one patient (20%) died.

CONCLUSION

Both SARS-CoV-2 and cHCoV can cause severe pneumonia. Problems for future resolution include whether antiviral agents administered in cases of mild or moderate severity can reduce the number of severe cases, and whether antivirals administered in severe cases can reduce mortality.

Assigning computed tomography involvement score in COVID-19 patients: prognosis prediction and impact on management

OBJECTIVE

Chest CT can provide a simple quantitative assessment of the extent of the parenchymal opacities in COVID-19 patients. In this study, we postulate that CT findings can be used to ascertain the overall disease burden and predict the clinical outcome.

METHODS

In this prospective study undertaken from March 28, 2020, until May 20, 2020, 142 patients with CT features suggestive of viral pneumonia, and positive RT-PCR for COVID-19 were enrolled. A dedicated spiral CT scanner was used for all COVID-19 suspects. CT features were reported as typical, indeterminate, or atypical for COVID-19 pneumonia. A CT involvement score (CT-IS) was given to each scan and assigned mild, moderate, or severe category depending on the score range. The patients were followed up for at least 15 days.

RESULTS

Ground glass opacity was present in 100% of the patients. There was a significant association between CT-IS and the final outcome of the patients. A statistically significant increasing trend of mortality and requirement of critical medical attention was observed with the rising value of CT-IS in COVID-19.

CONCLUSION

The severe CT-IS score group has a high mortality. The CT-IS score could be valuable in predicting clinical outcome and could also be useful in triage of patients needing hospital admission. In situations where healthcare resources are limited, and patient load high, a more careful approach for patients with higher CT-IS scores could be indispensable.

ADVANCES IN KNOWLEDGE

CT-IS is a simple quantitative method for assessing the disease burden of COVID-19 cases. It can be invaluable in places with limited resources and high patient load to segregate patients requiring critical medical attention.

Repurposing Drugs, Ongoing Vaccine, and New Therapeutic Development Initiatives Against COVID-19

As the COVID-19 is still growing throughout the globe, a thorough investigation into the specific immunopathology of SARS-CoV-2, its interaction with the host immune system and pathogen evasion mechanism may provide a clear picture of how the pathogen can breach the host immune defenses in elderly patients and patients with comorbid conditions. Such studies will also reveal the underlying mechanism of how children and young patients can withstand the disease better. The study of the immune defense mechanisms and the prolonged immune memory from patients population with convalescent plasma may help in designing a suitable vaccine candidate not only for the current outbreak but also for similar outbreaks in the future. The vital drug candidates, which are being tested as potential vaccines or therapeutics against COVID-19, include live attenuated vaccine, inactivated or killed vaccine, subunit vaccine, antibodies, interferon treatment, repurposing existing drugs, and nucleic acid-based vaccines. Several organizations around the world have fast-tracked the development of a COVID-19 vaccine, and some drugs already went to phase III of clinical trials. Hence, here, we have tried to take a quick glimpse of the development stages of vaccines or therapeutic approaches to treat this deadly disease.

Diagnostic Value of Imaging Modalities for COVID-19: Scoping Review

BACKGROUND

Coronavirus disease (COVID-19) is a serious infectious disease that causes severe respiratory illness. This pandemic represents a serious public health risk. Therefore, early and accurate diagnosis is essential to control disease progression. Radiological examination plays a crucial role in the early identification and management of infected patients.

OBJECTIVE

The aim of this review was to identify the diagnostic value of different imaging modalities used for diagnosis of COVID-19.

METHODS

A comprehensive literature search was conducted using the PubMed, Scopus, Web of Science, and Google Scholar databases. The keywords diagnostic imaging, radiology, respiratory infection, pneumonia, coronavirus infection and COVID-19 were used to identify radiology articles focusing on the diagnosis of COVID-19 and to determine the diagnostic value of various imaging modalities, including x-ray, computed tomography (CT), ultrasound, and nuclear medicine for identification and management of infected patients.

RESULTS

We identified 50 articles in the literature search. Studies that investigated the diagnostic roles and imaging features of patients with COVID-19, using either chest CT, lung ultrasound, chest x-ray, or positron emission topography/computed tomography (PET/CT) scan, were discussed. Of these imaging modalities, chest x-ray and CT scan are the most commonly used for diagnosis and management of COVID-19 patients, with chest CT scan being more accurate and sensitive in identifying COVID-19 at early stages. Only a few studies have investigated the roles of ultrasound and PET/CT scan in diagnosing COVID-19.

CONCLUSIONS

Chest CT scan remains the most sensitive imaging modality in initial diagnosis and management of suspected and confirmed patients with COVID-19. Other diagnostic imaging modalities could add value in evaluating disease progression and monitoring critically ill patients with COVID-19.

Social Network Analysis of COVID-19 Sentiments: Application of Artificial Intelligence

Background

The coronavirus disease (COVID-19) pandemic led to substantial public discussion. Understanding these discussions can help institutions, governments, and individuals navigate the pandemic.

Objective

The aim of this study is to analyze discussions on Twitter related to COVID-19 and to investigate the sentiments toward COVID-19.

Methods

This study applied machine learning methods in the field of artificial intelligence to analyze data collected from Twitter. Using tweets originating exclusively in the United States and written in English during the 1-month period from March 20 to April 19, 2020, the study examined COVID-19–related discussions. Social network and sentiment analyses were also conducted to determine the social network of dominant topics and whether the tweets expressed positive, neutral, or negative sentiments. Geographic analysis of the tweets was also conducted.

Results

There were a total of 14,180,603 likes, 863,411 replies, 3,087,812 retweets, and 641,381 mentions in tweets during the study timeframe. Out of 902,138 tweets analyzed, sentiment analysis classified 434,254 (48.2%) tweets as having a positive sentiment, 187,042 (20.7%) as neutral, and 280,842 (31.1%) as negative. The study identified 5 dominant themes among COVID-19–related tweets: health care environment, emotional support, business economy, social change, and psychological stress. Alaska, Wyoming, New Mexico, Pennsylvania, and Florida were the states expressing the most negative sentiment while Vermont, North Dakota, Utah, Colorado, Tennessee, and North Carolina conveyed the most positive sentiment.

Conclusions

This study identified 5 prevalent themes of COVID-19 discussion with sentiments ranging from positive to negative. These themes and sentiments can clarify the public’s response to COVID-19 and help officials navigate the pandemic.

Evaluating Clinical Course and Risk Factors of Infection and Demographic Characteristics of Pregnant Women with COVID-19 in Hamadan Province, West of Iran

BACKGROUND

COVID-19 is a new viral disease with a rapid outbreak. Pregnant women are at a higher risk of contracting viral infections including COVID-19. We aimed to evaluate the clinical course and risk factors of pregnant women diagnosed with COVID 19 in Hamadan Province, west of Iran.

STUDY DESIGN

A retrospective cohort study.

METHODS

The convenience sampling was performed using 50 papers and electronic files of pregnant women diagnosed with COVID-19 according to the WHO's temporary guidelines. They were hospitalized in health centers and clinics of Hamadan Province. The data-collecting tool employed was a researcher-made questionnaire. The data were analyzed via SPSS software version 19.

RESULTS

The mean age of pregnant women with COVID 19 was estimated to be 29.20 ± 5.8 yr and their average gestational age estimated to be 28.8 ± 8.20 weeks. About 32% of them had an underlying disease, 32% a history of influenza, and 40% recently traveled to infected areas. The most common findings were CT scans and multiple mottling and ground-glass opacity chest radiology. The most common symptoms were fever, cough, and shortness of breath. About 8% of the women required ICU hospitalization and the average length of hospital stay was 4.04 ± 2.38 and 29% had premature births. Moreover, 28% of infected mothers had a normal delivery and 20% had a cesarean section.

CONCLUSION

Early diagnosis of Covid-19 disease is essential in pregnant women. Because there is a possibility of worsening complications in the mother and fetus.

Understanding COVID-19: From Origin to Potential Therapeutics

Currently, a global pandemic era of public health concerns is going on with the Coronavirus Disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The first case of COVID-19 was reported from Wuhan's Huanan seafood market in China late December 2019. Bats, pangolins, and snakes have been nominated as salient carriers of the virus. Thanks to its high pathogenicity, it can cause severe respiratory infections. Fever, dry cough, sore throat, pneumonia, septic shock, and ground-glass opacities are the foremost clinical manifestations of COVID-19. Immunocompromised patients are at high risk for COVID-19 infection and may lead to death. Scientist and government agencies around the globe are putting forward their best efforts and resources for the effective treatment of human coronavirus infections; however, neither vaccines nor antiviral drugs are available for the treatment of human coronaviruses (HCoV) infections such as SARS (severe acute respiratory syndrome), MERS (Middle Eastern respiratory syndrome), and COVID-19. Since the outbreak, a plethora of research and review articles have been published. Moreover, the mass media has bombarded the public with conflicting opinions about the pandemic. There is a dire need for accurate and reliable information concerning this pandemic. In this review, we have compiled the up to date information about the origins, evolution, epidemiology, and pathogenesis of this disease. Moreover, very few reports have addressed the clinical features and current status of treatment for COVID-19; we have adequately addressed these topics in detail in this review. Finally, a detailed account of clinical trials of vaccines and other therapeutics currently in progress has been delineated.

Performance of Two Risk-Stratification Models in Hospitalized Patients With Coronavirus Disease

Background: Despite an increase in the familiarity of the medical community with the epidemiological and clinical characteristics of coronavirus disease 2019 (COVID-19), there is presently a lack of rapid and effective risk stratification indicators to predict the poor clinical outcomes of COVID-19 especially in severe patients.

Methods: In this retrospective single-center study, we included 117 cases confirmed with COVID-19. The clinical, laboratory, and imaging features were collected and analyzed during admission. The Multi-lobular infiltration, hypo-Lymphocytosis, Bacterial coinfection, Smoking history, hyper-Tension and Age (MuLBSTA) Score and Confusion, Urea, Respiratory rate, Blood pressure, Age 65 (CURB65) score were used to assess the death and intensive care unit (ICU) risks in all patients.

Results: Among of all 117 hospitalized patients, 21 (17.9%) patients were admitted to the ICU care, and 5 (4.3%) patients were died. The median hospital stay was 12 (10–15) days. There were 18 patients with MuLBSTA score ≥ 12 points and were all of severe type. In severe type, ICU care and death patients, the proportion with MuLBSTA ≥ 12 points were greater than that of CURB65 score ≥ 3 points (severe type patients, 50 vs. 27.8%; ICU care, 61.9 vs. 19.0%; death, 100 vs. 40%). For the MuLBSTA score, the ROC curve showed good efficiency of diagnosis death (area under the curve [AUC], 0.956; cutoff value, 12; specificity, 89.5%; sensitivity, 100%) and ICU care (AUC, 0.875; cutoff value, 11; specificity, 91.7%; sensitivity, 71.4%). The K–M survival analysis showed that patients with MuLBSTA score ≥ 12 had higher risk of ICU (log-rank, P = 0.001) and high risk of death (log-rank, P = 0.000).

Conclusions: The MuLBSTA score is valuable for risk stratification and could effectively screen high-risk patients at admission. The higher score at admission have higher risk of ICU care and death in patients infected with COVID.

Impact on clinical practice of the preoperative screening of Covid-19 infection in surgical oncological patients. Prospective cohort study

BACKGROUND

In the oncological patient, an COVID-19-Infection, whether symptomatic or asymptomatic, a surgical procedure may carry a higher postoperative morbidity and mortality. The aim of this study was to describe the impact on clinical practice of sequential preoperative screening for COVID-19-infection in deciding whether to proceed or postpone surgery.

METHODS

Prospective, cohort study, based on consecutive patients' candidates for an oncological surgical intervention. Sequential preoperative screening for COVID-19-infection: two-time medical history (telematic and face-to-face), PCR and chest CT, 48 h before of surgical intervention. COVID-19-infection was considered positive if the patient had a suggestive medical history and/or PCR-positive and/or CT of pneumonia.

RESULTS

Between April 15th and May 4th, 2020, 179 patients were studied, 97 were male (54%), mean (sd) age 66.7 (13,6). Sequential preoperative screening was performed within 48 h before to surgical intervention. The prevalence of preoperative COVID-19-infection was 4.5%, 95%CI:2.3-8.6% (8 patients). Of the operated patients (171), all had a negative medical history, PCR and chest CT. The complications was 14.8% (I-II) and 2.5% (III-IV). There was no mortality. The hospital stay was 3.1 (sd 2.7) days.In the 8 patients with COVID-19-infection, the medical history was suggestive in all of them, 7 presented PCR-positive and 5 had a chest CT suggestive of pneumonia. The surgical intervention was postponed between 15 and 21 days.

CONCLUSION

Preoperative screening for COVID-19-infection using medical history and PCR helped the surgeon to decide whether to go ahead or postpone surgery in oncological patients. The chest CT may be useful in unclear cases.

Outbreak and Regression of COVID-19 Epidemic Among Chinese Medical Staff

Coronavirus disease 2019 (COVID-19) broke out first in Wuhan City, Hubei Province, China. In the process of controlling the pandemic, many Chinese medical staff (MS) were infected. We used government data, post mortem reports, and the medical literature on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, as well as prevention-and-control guidelines from the government, hospitals and media, to discuss the main risks factors faced by MS. We suggest that, when dealing with a similar pandemic in the future, guidance on personal protective equipment must be provided and materials reserved in advance. Also, the emergency response of medical institutions should be enhanced, and information shared with other countries facing identical severe challenges.

Typical and atypical COVID-19 computed tomography findings

In December 2019 a novel coronavirus, named severe acute respiratory syndrome coronavirus 2 was identified and the disease associated was named coronavirus disease 2019 (COVID-19). Fever, cough, myalgia, fatigue associated to dyspnea represent most common clinical symptoms of the disease. The reference standard for diagnosis of severe acute respiratory syndrome coronavirus 2 infection is real time reverse-transcription polymerase chain reaction test applied on respiratory tract specimens. Despite of lower specificity, chest computed tomography (CT), as reported in manifold scientific studies, showed high sensitivity, therefore it may help in the early detection, management and follow-up of COVID-19 pneumonia. Patients affected by COVID-19 pneumonia usually showed on chest CT some typical features, such as: Bilateral ground glass opacities characterized by multilobe involvement with posterior and peripheral distribution; parenchymal consolidations with or without air bronchogram; interlobular septal thickening; crazy paving pattern, represented by interlobular and intralobular septal thickening surrounded by ground-glass opacities; subsegmental pulmonary vessels enlargement (> 3 mm). Halo sign, reversed halo sign, cavitation and pleural or pericardial effusion represent some of atypical findings of COVID-19 pneumonia. On the other hand lymphadenopathy's and bronchiectasis' frequency is unclear, indeed conflicting data emerged in literature. Radiologists play a key role in recognition of high suspicious findings of COVID-19 on chest CT, both typical and atypical ones. Thus, the aim of this review is to illustrate typical and atypical CT findings of COVID-19.

Determination of risk factors for predicting the onset of symptoms in asymptomatic COVID-19 infected patients

Background: The number of asymptomatic infected patients with coronavirus disease 2019 (COVID-2019) is rampaging around the world but limited information aimed on risk factors of asymptomatic infections. The purpose of this study is to investigate the risk factors of symptoms onset and clinical features in asymptomatic COVID-19 infected patients. Methods: A retrospective study was performed in 70 asymptomatic COVID-2019 infected patients confirmed by nucleic acid tests in Hunan province, China between 28 January 2020 and 18 February, 2020. The epidemiological, clinical features and laboratory data were reviewed and analyzed. Presence or absence at the onset of symptoms was taken as the outcome. A Cox regression model was performed to evaluate the potential predictors of the onset of symptoms. Results: The study included 36 males and 34 females with a mean age of 33.24±20.40 years (range, 0.5-84 years). There were 22 asymptomatic carriers developed symptoms during hospitalization isolated observation, and diagnosed as confirmed cases, while 48 cases remained asymptomatic throughout the course of disease. Of 70 asymptomatic patients, 14 (14/70, 20%) had underlying diseases, 3 (3/70, 4.3%) had drinking history, and 11 (11/70, 15.7%) had smoking history. 22 patients developed symptoms onset of fever (4/22, 18.2%), cough (13/22, 59.1%), chest discomfort (2/22, 9.1%), fatigue (1/22, 4.5%), pharyngalgia (1/22, 4.5%) during hospitalization; only one (1/22, 4.5%) patient developed signs of both cough and pharyngalgia. Abnormalities on chest CT were detected among 35 of the 69 patients (50.7%) after admission, except for one pregnant woman had not been examined. 4 (4/70, 5.7%) and 8 (8/70, 11.4%) cases showed leucopenia and lymphopenia. With the effective antiviral treatment, all the 70 asymptomatic infections had been discharged, none cases developed severe pneumonia, admission to intensive care unit, or died. The mean time from nucleic acid positive to negative was 13.2±6.84 days. Cox regression analysis showed that smoking history (P=0.028, hazard ratio=4.49, 95% CI 1.18-17.08) and existence of pulmonary disease (P=0.038, hazard ratio=7.09, 95% CI 1.12-44.90) were risk factors of the onset of symptoms in asymptomatic carries. Conclusion: The initially asymptomatic patients can develop mild symptoms and have a good prognosis. History of smoking and pulmonary disease was prone to illness onset in asymptomatic patients, and it is necessary to be highly vigilant to those patients.

Clinical Pathway for Early Diagnosis of COVID-19: Updates from Experience to Evidence-Based Practice

The COVID-19 pandemic is a significant global event in the history of infectious diseases. The SARS-CoV-2 appears to have originated from bats but is now easily transmissible among humans, primarily through droplet or direct contact. Clinical features of COVID-19 include high fever, cough, and fatigue which may progress to ARDS. Respiratory failure can occur rapidly after this. The primary laboratory findings include lymphopenia and eosinopenia. Elevated D-dimer, procalcitonin, and CRP levels may correlate with disease severity. Imaging findings include ground-glass opacities and patchy consolidation on CT scan. Mortality is higher in patients with hypertension, cardiac disease, diabetes mellitus, cancer, and COPD. Elderly patients are more susceptible to severe disease and death, while children seem to have lower rates of infection and lower mortality. Diagnostic criteria and the identification of persons under investigation have evolved as more data has emerged. However, the approach to diagnosis is still very variable from region to region, country to country, and even among different hospitals in the same city. The importance of a clinical pathway to implement the most effective and relevant diagnostic strategy is of critical importance to establish the control of this virus that is responsible for more and more deaths each day.

Point-of-Care Lung Ultrasound for Detecting Severe Presentations of Coronavirus Disease 2019 in the Emergency Department: A Retrospective Analysis

OBJECTIVES

Analyze the diagnostic test characteristics of point-of-care lung ultrasound for patients suspected to have novel coronavirus disease 2019.

DESIGN

Retrospective cohort.

SETTING

Two emergency departments in Detroit, Michigan, United States, during a local coronavirus disease 2019 outbreak (March 2020 to April 2020).

PATIENTS

Emergency department patients receiving lung ultrasound for clinical suspicion of coronavirus disease 2019 during the study period.

INTERVENTIONS

None, observational analysis only.

MEASUREMENTS AND MAIN RESULTS

By a reference standard of serial reverse transcriptase-polymerase chain reactions, 42 patients were coronavirus disease 2019 positive, 16 negative, and eight untested (test results lost, died prior to testing, and/or did not meet hospital guidelines for rationing of reverse transcriptase-polymerase chain reaction tests). Thirty-three percent, 44%, 38%, and 17% had mortality, ICU admission, intubation, and venous or arterial thromboembolism, respectively. Receiver operating characteristics, area under the curve, sensitivity, and specificity with 95% CIs were calculated for five lung ultrasound patterns coded by a blinded reviewer and chest radiograph. Chest radiograph had area under the curve = 0.66 (95% CI, 0.54-0.79), 74% sensitivity (95% CI, 48-93%), and 53% specificity (95% CI, 32-75%). Two lung ultrasound patterns had a statistically significant area under the curve: symmetric bilateral pulmonary edema (area under the curve, 0.57; 95% CI, 0.50-0.64), and a nondependent bilateral pulmonary edema pattern (edema in superior lung ≥ inferior lung and no pleural effusion; area under the curve, 0.73; 95% CI, 0.68-0.90). Chest radiograph plus the nondependent bilateral pulmonary edema pattern showed a statistically improved area under the curve (0.80; 95% CI, 0.68-0.90) compared to either alone, but at the ideal cutoff had sensitivity and specificity equivalent to nondependent bilateral pulmonary edema only (69% and 77%, respectively). The strongest combination of clinical, chest radiograph, and lung ultrasound factors for diagnosis was nondependent bilateral pulmonary edema pattern with temperature and oxygen saturation (area under the curve, 0.86; 95% CI, 0.76-0.94; sensitivity = 77% [58-93%]; specificity = 76% [53-94%] at the ideal cutoff), which was superior to chest radiograph alone.

CONCLUSIONS

Lung ultrasound diagnosed severe presentations of coronavirus disease 2019 with similar sensitivity to chest radiograph, CT, and reverse transcriptase-polymerase chain reaction (on first testing) and improved specificity compared to chest radiograph. Diagnostically useful lung ultrasound patterns differed from those hypothesized by previous, nonanalytical, reports (case series and expert opinion), and should be evaluated in a rigorous prospective study.

Correlation between climate indicators and COVID-19 pandemic in New York, USA

This study analyzed the association between COVID-19 and climate indicators in New York City, USA. We used secondary published data from New York city health services and National weather service, USA. The climate indicators included in the study are average temperature, minimum temperature, maximum temperature, rainfall, average humidity, wind speed, and air quality. Kendall and Spearman rank correlation tests were chosen for data analysis. We find that average temperature, minimum temperature, and air quality were significantly associated with the COVID-19 pandemic. The findings of this study will help World Health Organization and health regulators such as Center for Disease Control (CDC) to combat COVID-19 in New York and the rest of the world.

Initial chest CT findings in COVID-19: correlation with clinical features

In December 2019, coronavirus disease 2019 (COVID-19), a new de novo infectious disease, was first identified in Wuhan, China and quickly spread across China and around the world. The etiology was a novel betacoronavirus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (Lu et al., 2020). On Mar. 11, 2020, World Health Organization (WHO) characterized COVID-19 as a global pandemic. As of Mar. 22, 2020, over 292 000 confirmed COVID-19 cases have been reported globally. To date, COVID-19, with its high infectivity, has killed more people than severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) combined (Wu and McGoogan, 2020).

False negative chest X-Rays in patients affected by COVID-19 pneumonia and corresponding chest CT findings

Due to the wide availability, rapid execution, low cost, and possibility of being acquired at the patient's bed, chest X-Ray is a fundamental tool in the diagnosis, follow-up and evaluation of the treatment effectiveness of patients with pneumonia, also in the context of COVID-19 infection. However, false negative cases are possible. We report 4 cases of false negative chest X-Rays, in patients who were diagnosed positive for COVID-19 by real-time transverse-transcript-polymerase chain reaction (RT-PCR), and executed chest unenhanced CTs just after the X-Rays, demonstrating signs of COVID-19 pneumonia.

Impact of temperature on the dynamics of the COVID-19 outbreak in China

A COVID-19 outbreak emerged in Wuhan, China at the end of 2019 and developed into a global pandemic during March 2020. The effects of temperature on the dynamics of the COVID-19 epidemic in China are unknown. Data on COVID-19 daily confirmed cases and daily mean temperatures were collected from 31 provincial-level regions in mainland China between Jan. 20 and Feb. 29, 2020. Locally weighted regression and smoothing scatterplot (LOESS), distributed lag nonlinear models (DLNMs), and random-effects meta-analysis were used to examine the relationship between daily confirmed cases rate of COVID-19 and temperature conditions. The daily number of new cases peaked on Feb. 12, and then decreased. The daily confirmed cases rate of COVID-19 had a biphasic relationship with temperature (with a peak at 10 °C), and the daily incidence of COVID-19 decreased at values below and above these values. The overall epidemic intensity of COVID-19 reduced slightly following days with higher temperatures with a relative risk (RR) was 0.96 (95% CI: 0.93, 0.99). A random-effect meta-analysis including 28 provinces in mainland China, we confirmed the statistically significant association between temperature and RR during the study period (Coefficient = -0.0100, 95% CI: -0.0125, -0.0074). The DLNMs in Hubei Province (outside of Wuhan) and Wuhan showed similar patterns of temperature. Additionally, a modified susceptible-exposed-infectious-recovered (M-SEIR) model, with adjustment for climatic factors, was used to provide a complete characterization of the impact of climate on the dynamics of the COVID-19 epidemic.

COVID-19 paraclinical diagnostic tools: Updates and future trends

MOTIVATION

COVID-19 is one of the most widely affecting pandemics. As for many respiratory viruses-caused diseases, diagnosis of COVID-19 relies on two main compartments: clinical and paraclinical diagnostic criteria. Rapid and accurate diagnosis is vital in such a pandemic. On one side, rapidity may enhance management effectiveness, while on the other, coupling efficiency and less costly procedures may permit more effective community-scale management.

METHODOLOGY AND MAIN STRUCTURE

In this review, we shed light on the most used and the most validated diagnostic tools. Furthermore, we intend to include few under-development techniques that may be potentially useful in this context. The practical intent of our work is to provide clinicians with a realistic summarized review of the essential elements in the applied paraclinical diagnosis of COVID-19.

Correlation between climate indicators and COVID-19 pandemic in New York, USA

This study analyzed the association between COVID-19 and climate indicators in New York City, USA. We used secondary published data from New York city health services and National weather service, USA. The climate indicators included in the study are average temperature, minimum temperature, maximum temperature, rainfall, average humidity, wind speed, and air quality. Kendall and Spearman rank correlation tests were chosen for data analysis. We find that average temperature, minimum temperature, and air quality were significantly associated with the COVID-19 pandemic. The findings of this study will help World Health Organization and health regulators such as Center for Disease Control (CDC) to combat COVID-19 in New York and the rest of the world.

COVID-19 in the radiology department: What radiographers need to know

OBJECTIVES

The aim is to review current literature related to the diagnosis, management, and follow-up of suspected and confirmed Covid-19 cases.

KEY FINDINGS

Medical Imaging plays an important auxiliary role in the diagnosis of Covid-19 patients, mainly those most seriously affected. Practice differs widely among different countries, mainly due to the variability of access to resources (viral testing and imaging equipment, specialised staff, protective equipment). It has been now well-documented that chest radiographs should be the first-line imaging tool and chest CT should only be reserved for critically ill patients, or when chest radiograph and clinical presentation may be inconclusive.

CONCLUSION

As radiographers work on the frontline, they should be aware of the potential risks associated with Covid-19 and engage in optimal strategies to reduce these. Their role in vetting, conducting and often reporting the imaging examinations is vital, as well as their contribution in patient safety and care. Medical Imaging should be limited to critically ill patients, and where it may have an impact on the patient management plan.

IMPLICATIONS FOR PRACTICE

At the time of publication, this review offers the most up-to-date recommendations for clinical practitioners in radiology departments, including radiographers. Radiography practice has to significantly adjust to these new requirements to support optimal and safe imaging practices for the diagnosis of Covid-19. The adoption of low dose CT, rigorous infection control protocols and optimal use of personal protective equipment may reduce the potential risks of radiation exposure and infection, respectively, within Radiology departments.

COVID-19: clinical issues from the Japan Surgical Society

In this unprecedented COVID-19 pandemic, several key issues must be addressed to ensure safe treatment and prevent rapid spread of the virus and a consequential medical crisis. Careful evaluation of a patient's condition is crucial for deciding the triage plan, based on the status of the disease and comorbidities. As functionality of the medical care system is greatly affected by the environmental situation, the treatment may differ according to the medical and infectious disease circumstances of the institution. Importantly, all medical staff must prevent nosocomial COVID-19 by minimizing the effects of aerosol spread and developing diagnostic and surgical procedures. Polymerase chain reaction (PCR) screening for COVID-19 infection, particularly in asymptomatic patients, should be encouraged as these patients are prone to postoperative respiratory failure. In this article, the Japan Surgical Society addresses the general principles of surgical treatment in relation to COVID-19 infection and advocates preventive measures against viral transmission during this unimaginable COVID-19 pandemic.

Dual-Sampling Attention Network for Diagnosis of COVID-19 From Community Acquired Pneumonia

The coronavirus disease (COVID-19) is rapidly spreading all over the world, and has infected more than 1,436,000 people in more than 200 countries and territories as of April 9, 2020. Detecting COVID-19 at early stage is essential to deliver proper healthcare to the patients and also to protect the uninfected population. To this end, we develop a dual-sampling attention network to automatically diagnose COVID-19 from the community acquired pneumonia (CAP) in chest computed tomography (CT). In particular, we propose a novel online attention module with a 3D convolutional network (CNN) to focus on the infection regions in lungs when making decisions of diagnoses. Note that there exists imbalanced distribution of the sizes of the infection regions between COVID-19 and CAP, partially due to fast progress of COVID-19 after symptom onset. Therefore, we develop a dual-sampling strategy to mitigate the imbalanced learning. Our method is evaluated (to our best knowledge) upon the largest multi-center CT data for COVID-19 from 8 hospitals. In the training-validation stage, we collect 2186 CT scans from 1588 patients for a 5-fold cross-validation. In the testing stage, we employ another independent large-scale testing dataset including 2796 CT scans from 2057 patients. Results show that our algorithm can identify the COVID-19 images with the area under the receiver operating characteristic curve (AUC) value of 0.944, accuracy of 87.5%, sensitivity of 86.9%, specificity of 90.1%, and F1-score of 82.0%. With this performance, the proposed algorithm could potentially aid radiologists with COVID-19 diagnosis from CAP, especially in the early stage of the COVID-19 outbreak.

Frequency and Distribution of Chest Radiographic Findings in Patients Positive for COVID-19

Background Current coronavirus disease 2019 (COVID-19) radiologic literature is dominated by CT, and a detailed description of chest radiography appearances in relation to the disease time course is lacking. Purpose To describe the time course and severity of findings of COVID-19 at chest radiography and correlate these with real-time reverse transcription polymerase chain reaction (RT-PCR) testing for severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, nucleic acid. Materials and Methods This is a retrospective study of patients with COVID-19 confirmed by using RT-PCR and chest radiographic examinations who were admitted across four hospitals and evaluated between January and March 2020. Baseline and serial chest radiographs (n = 255) were reviewed with RT-PCR. Correlation with concurrent CT examinations (n = 28) was performed when available. Two radiologists scored each chest radiograph in consensus for consolidation, ground-glass opacity, location, and pleural fluid. A severity index was determined for each lung. The lung scores were summed to produce the final severity score. Results The study was composed of 64 patients (26 men; mean age, 56 years ± 19 [standard deviation]). Of these, 58 patients had initial positive findings with RT-PCR (91%; 95% confidence interval: 81%, 96%), 44 patients had abnormal findings at baseline chest radiography (69%; 95% confidence interval: 56%, 80%), and 38 patients had initial positive findings with RT-PCR testing and abnormal findings at baseline chest radiography (59%; 95% confidence interval: 46%, 71%). Six patients (9%) showed abnormalities at chest radiography before eventually testing positive for COVID-19 with RT-PCR. Sensitivity of initial RT-PCR (91%; 95% confidence interval: 83%, 97%) was higher than that of baseline chest radiography (69%; 95% confidence interval: 56%, 80%) (P = .009). Radiographic recovery (mean, 6 days ± 5) and virologic recovery (mean, 8 days ± 6) were not significantly different (P = .33). Consolidation was the most common finding (30 of 64; 47%) followed by ground-glass opacities (21 of 64; 33%). Abnormalities at chest radiography had a peripheral distribution (26 of 64; 41%) and lower zone distribution (32 of 64; 50%) with bilateral involvement (32 of 64; 50%). Pleural effusion was uncommon (two of 64; 3%). The severity of findings at chest radiography peaked at 10-12 days from the date of symptom onset. Conclusion Findings at chest radiography in patients with coronavirus disease 2019 frequently showed bilateral lower zone consolidation, which peaked at 10-12 days from symptom onset. © RSNA, 2020.

COVIDiag: a clinical CAD system to diagnose COVID-19 pneumonia based on CT findings

Objectives

CT findings of COVID-19 look similar to other atypical and viral (non-COVID-19) pneumonia diseases. This study proposes a clinical computer-aided diagnosis (CAD) system using CT features to automatically discriminate COVID-19 from non-COVID-19 pneumonia patients.

Methods

Overall, 612 patients (306 COVID-19 and 306 non-COVID-19 pneumonia) were recruited. Twenty radiological features were extracted from CT images to evaluate the pattern, location, and distribution of lesions of patients in both groups. All significant CT features were fed in five classifiers namely decision tree, K-nearest neighbor, naïve Bayes, support vector machine, and ensemble to evaluate the best performing CAD system in classifying COVID-19 and non-COVID-19 cases.

Results

Location and distribution pattern of involvement, number of the lesion, ground-glass opacity (GGO) and crazy-paving, consolidation, reticular, bronchial wall thickening, nodule, air bronchogram, cavity, pleural effusion, pleural thickening, and lymphadenopathy are the significant features to classify COVID-19 from non-COVID-19 groups. Our proposed CAD system obtained the sensitivity, specificity, and accuracy of 0.965, 93.54%, 90.32%, and 91.94%, respectively, using ensemble (COVIDiag) classifier.

Conclusions

This study proposed a COVIDiag model obtained promising results using CT radiological routine features. It can be considered an adjunct tool by the radiologists during the current COVID-19 pandemic to make an accurate diagnosis.

Key Points

• Location and distribution of involvement, number of lesions, GGO and crazy-paving, consolidation, reticular, bronchial wall thickening, nodule, air bronchogram, cavity, pleural effusion, pleural thickening, and lymphadenopathy are the significant features between COVID-19 from non-COVID-19 groups.

• The proposed CAD system, COVIDiag, could diagnose COVID-19 pneumonia cases with an AUC of 0.965 (sensitivity = 93.54%; specificity = 90.32%; and accuracy = 91.94%).

• The AUC, sensitivity, specificity, and accuracy obtained by radiologist diagnosis are 0.879, 87.10%, 88.71%, and 87.90%, respectively.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-07087-y) contains supplementary material, which is available to authorized users.

Performance of Radiologists in Differentiating COVID-19 from Non-COVID-19 Viral Pneumonia at Chest CT

Background Despite its high sensitivity in diagnosing coronavirus disease 2019 (COVID-19) in a screening population, the chest CT appearance of COVID-19 pneumonia is thought to be nonspecific. Purpose To assess the performance of radiologists in the United States and China in differentiating COVID-19 from viral pneumonia at chest CT. Materials and Methods In this study, 219 patients with positive COVID-19, as determined with reverse-transcription polymerase chain reaction (RT-PCR) and abnormal chest CT findings, were retrospectively identified from seven Chinese hospitals in Hunan Province, China, from January 6 to February 20, 2020. Two hundred five patients with positive respiratory pathogen panel results for viral pneumonia and CT findings consistent with or highly suspicious for pneumonia, according to original radiologic interpretation within 7 days of each other, were identified from Rhode Island Hospital in Providence, RI. Three radiologists from China reviewed all chest CT scans (n = 424) blinded to RT-PCR findings to differentiate COVID-19 from viral pneumonia. A sample of 58 age-matched patients was randomly selected and evaluated by four radiologists from the United States in a similar fashion. Different CT features were recorded and compared between the two groups. Results For all chest CT scans (n = 424), the accuracy of the three radiologists from China in differentiating COVID-19 from non-COVID-19 viral pneumonia was 83% (350 of 424), 80% (338 of 424), and 60% (255 of 424). In the randomly selected sample (n = 58), the sensitivities of three radiologists from China and four radiologists from the United States were 80%, 67%, 97%, 93%, 83%, 73%, and 70%, respectively. The corresponding specificities of the same readers were 100%, 93%, 7%, 100%, 93%, 93%, and 100%, respectively. Compared with non-COVID-19 pneumonia, COVID-19 pneumonia was more likely to have a peripheral distribution (80% vs 57%, P < .001), ground-glass opacity (91% vs 68%, P < .001), fine reticular opacity (56% vs 22%, P < .001), and vascular thickening (59% vs 22%, P < .001), but it was less likely to have a central and peripheral distribution (14% vs 35%, P < .001), pleural effusion (4% vs 39%, P < .001), or lymphadenopathy (3% vs 10%, P = .002). Conclusion Radiologists in China and in the United States distinguished coronavirus disease 2019 from viral pneumonia at chest CT with moderate to high accuracy. © RSNA, 2020 Online supplemental material is available for this article. A translation of this abstract in Farsi is available in the supplement. ترجمه چکیده این مقاله به فارسی، در ضمیمه موجود است.

CT chest for COVID-19, a multicenter study—experience with 220 Egyptian patients

Background

COVID-19 has become a national and an international pre-occupation to all doctors. Dealing with patients with clinical suspicion of COVID-19 is a daily markedly growing professional issue for radiologists. The number of COVID-19 cases we deal with is peaking since last March and so is our experience in recognizing the disease patterns and in assessing its severity. The purpose of this study is to assess the role of CT chest in the diagnosis of COVID-19 based on our experience with 220 Egyptian cases.

Results

A cross-sectional multicenter study involving 220 patients; 68 (30.9%) females and 152 (69.1%) males, their age range was 10-92 years (average 49.198 years). Non-contrast MSCT chest was done to patients with clinically suspected COVID-19. Data assessment and analysis for lesions probability, pattern, localization, and severity were done.

Bilateral affection was seen in 168/220 cases (76.36%). Multilobar affection was noted in 186/220 cases (84.54%). Lower lobes affection was noted in 179/220 cases (81.36%). Peripheral/subpleural affection was noted in 203/220 cases (92.27%). The common CT patterns (ground-glass opacities, consolidation, crazy paving, vascular thickening, traction bronchiectasis, vacuolar sign, architectural distortion signs, and reversed halo sign) and the uncommon CT patterns (halo sign, masses, nodules, lobar affection, tree in-bud-pattern and cysts) were discussed. Associated extra-pulmonary lesions described. Temporal changes, severity scoring, reporting, and possible pitfalls were all assessed.

Conclusion

In our experience, CT plays a basic essential role in diagnosing COVID-19 in the current declared pandemic.

Imaging Manifestations of Lung Injury During the COVID-19 Outbreak: What Have We Learned?

Coronavirus disease-19 (COVID-19) is a pandemic infectious disease caused by a novel coronavirus. Infection can result in a wide range of clinical outcomes, from an asymptomatic condition to severe bilateral pneumonia and life-threatening conditions. Diagnosis is based on the combination of a history of exposure, clinical presentation, and real-time polymerase chain reaction (RT-PCR) assays. In endemic areas, imaging tests including computed tomography (CT), chest X-ray (CXR), and ultrasound (US) have been included in the diagnostic workup. Multiple and peripheral areas of parenchymal injury is the hallmark of COVID-19 lung infection, seen as ground-glass opacification and consolidation on CT, as hazy opacities on CXR, and as multiple B-lines and subpleural consolidations on US. Of these modalities, CT has the best sensitivity and specificity, while CXR has moderate sensitivity and unknown specificity. Both CT and CXR involve ionizing radiation, increase the risk of cross-infection, and require a long sterilization time. Ultrasound is the only modality used by clinicians. Early reports have shown promising results, comparable to CT. With high availability, the lowest risk of cross-infection, and a rapid sterilization process, US may potentially become the primary imaging tool for COVID-19 pulmonary injury. Lung US training programs are needed to provide clinicians with the ability to better implement this technique.

The Coronavirus Disease 2019 (COVID-19) in Children: A Study in an Iranian Children's Referral Hospital

BACKGROUND

Despite the worldwide spread of the coronavirus disease 2019 (COVID-19), the epidemiological and clinical patterns of the COVID-19 infection remain largely unclear, particularly among children. In this study, we explored the epidemiological characteristics, clinical patterns, and laboratory and imaging findings of pediatric patients with COVID-19.

MATERIALS AND METHODS

From March 7 to March 30, 2020, there were a total of 35 patients who had confirmed COVID-19 infection by laboratory virus nucleic acid test (RT-PCR) assay with throat swab samples or typical chest CT manifestation compatible with COVID-19, in addition to a history of close contact with suspected or confirmed SARS-CoV-2 in family members. Information recorded included demographic data, medical history, exposure history, underlying comorbidities, symptoms, signs, laboratory findings and radiologic assessments, severity of disease, treatment, and mortality.

RESULTS

The median age of the patients was 7.5 years (IQR=4-11; range=4 months to 15 years). A total of 63% were male. Cough was present in 80% of the patients, followed by fever (77%), nausea or vomiting (29%), diarrhea (26%), shortness of breath (29%), headache (20%), and myalgia (14%). Lymphopenia was present in 43% of the patients, thrombocytopenia in 9%, neutopenia in 8%, and leucopenia in 26%. We reported severe pneumonia in 40% of the hospitalized patients and 18 (51%) had underlying diseases. Of 35 patients, 11 had positive RT-PCR results (31%). The chest CT images of 24 patients (69%) suggested COVID-19, while their RT-PCR assays from throat swab samples were negative.

CONCLUSION

This study demonstrates different clinical findings of pediatrics compared to the previous reports of children. Since a high rate of false negative RT-PCR test was observed, early detection of children with COVID-19 infection by CT is conducive to reasonable management and early treatment.

Effects of policies and containment measures on control of COVID-19 epidemic in Chongqing

BACKGROUND

Coronavirus disease 2019 (COVID-19) is an emerging, rapidly evolving disease that spreads through the respiratory system and is highly contagious. In March 2020, the World Health Organization declared the COVID-19 outbreak a pandemic. In China, the pandemic was controlled after 2 mo through effective policies and containment measures. Describing the detailed policies and containment measures used to control the epidemic in Chongqing will provide a reference for the prevention and control of COVID-19 in other areas of the world.

AIM

To explore the effects of different policies and containment measures on the control of the COVID-19 epidemic in Chongqing.

METHODS

Epidemiological data on COVID-19 in Chongqing were prospectively collected from January 21 to March 15, 2020. The policies and prevention measures implemented by the government during the epidemic period were also collected. Trend analysis was performed to explore the impact of the main policy measures on the effectiveness of the control of COVID-19 in Chongqing.

RESULTS

As of March 15, the cumulative incidence of COVID-19 in Chongqing was 1.84/100000 (576 cases) and the infection fatality rate was 1.04% (6/576). The spread of COVID-19 was controlled by effective policies that involved establishing a group for directing the COVID-19 epidemic control effort; strengthening guidance and supervision; ensuring the supply of daily necessities and medical supplies and equipment to residents; setting up designated hospitals; implementing legal measures; and enhancing health education. Medical techniques were implemented to improve the recovery rate and control the epidemic. Policies such as "the lockdown of Wuhan", "initiating a first-level response to major public health emergencies", and "implementing the closed management of residential communities" significantly curbed the spread of COVID-19. Optimizing the diagnosis process, shortening the diagnosis time, and constructing teams of clinical experts facilitated the provision of "one team of medical experts for each patient" treatment for severe patients, which significantly improved the recovery rate and reduced the infection fatality rate.

CONCLUSION

The prevention policies and containment measures implemented by the government and medical institutions are highly effective in controlling the spread of the epidemic and increasing the recovery rate of COVID-19 patients.

Development and Validation of a Prognostic Nomogram Based on Clinical and CT Features for Adverse Outcome Prediction in Patients with COVID-19

Objective

The purpose of our study was to investigate the predictive abilities of clinical and computed tomography (CT) features for outcome prediction in patients with coronavirus disease (COVID-19).

Materials and Methods

The clinical and CT data of 238 patients with laboratory-confirmed COVID-19 in our two hospitals were retrospectively analyzed. One hundred sixty-six patients (103 males; age 43.8 ± 12.3 years) were allocated in the training cohort and 72 patients (38 males; age 45.1 ± 15.8 years) from another independent hospital were assigned in the validation cohort. The primary composite endpoint was admission to an intensive care unit, use of mechanical ventilation, or death. Univariate and multivariate Cox proportional hazard analyses were performed to identify independent predictors. A nomogram was constructed based on the combination of clinical and CT features, and its prognostic performance was externally tested in the validation group. The predictive value of the combined model was compared with models built on the clinical and radiological attributes alone.

Results

Overall, 35 infected patients (21.1%) in the training cohort and 10 patients (13.9%) in the validation cohort experienced adverse outcomes. Underlying comorbidity (hazard ratio [HR], 3.35; 95% confidence interval [CI], 1.67–6.71; p < 0.001), lymphocyte count (HR, 0.12; 95% CI, 0.04–0.38; p < 0.001) and crazy-paving sign (HR, 2.15; 95% CI, 1.03–4.48; p = 0.042) were the independent factors. The nomogram displayed a concordance index (C-index) of 0.82 (95% CI, 0.76–0.88), and its prognostic value was confirmed in the validation cohort with a C-index of 0.89 (95% CI, 0.82–0.96). The combined model provided the best performance over the clinical or radiological model (p < 0.050).

Conclusion

Underlying comorbidity, lymphocyte count and crazy-paving sign were independent predictors of adverse outcomes. The prognostic nomogram based on the combination of clinical and CT features could be a useful tool for predicting adverse outcomes of patients with COVID-19.

Quantitative lung lesion features and temporal changes on chest CT in patients with common and severe SARS-CoV-2 pneumonia

The purpose of this study was to describe the temporal evolution of quantitative lung lesion features on chest computed tomography (CT) in patients with common and severe types of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia. Records of patients diagnosed with SARS-CoV-2 pneumonia were reviewed retrospectively from 24 January 2020 to 15 March 2020. Patients were classified into common and severe groups according to the diagnostic criteria of severe pneumonia. The quantitative CT features of lung lesions were automatically calculated using artificial intelligence algorithms, and the percentages of ground-glass opacity volume (PGV), consolidation volume (PCV) and total lesion volume (PTV) were determined in both lungs. PGV, PCV and PTV were analyzed based on the time from the onset of initial symptoms in the common and severe groups. In the common group, PTV increased slowly and peaked at approximately 12 days from the onset of the initial symptoms. In the severe group, PTV peaked at approximately 17 days. The severe pneumonia group exhibited increased PGV, PCV and PTV compared with the common group. These features started to appear in Stage 2 (4-7 days from onset of initial symptoms) and were observed in all subsequent stages (p<0.05). In severe SARS-CoV-2 pneumonia patients, PGV, PCV and PTV began to significantly increase in Stage 2 and decrease in Stage 5 (22-30 days). Compared with common SARS-CoV-2 pneumonia patients, the patients in the severe group exhibited increased PGV, PCV and PTV as well as a later peak time of lesion and recovery time.

A twisted tale-radiological imaging features of COVID-19 on 18F-FDG PET/CT

The COVID-19 pandemic has had a major impact on health care systems across the globe in a short period of time. There is a growing body of evidence surrounding the findings on hybrid imaging with FDG-PET/CT, and this case highlights the importance of molecular imaging in better understanding of the biomarkers of the disease which ultimately determine the success in building a model to predict the disease severity and monitoring the response to treatment.

Comparison of Chest CT Manifestations of Coronavirus Disease 2019 (COVID-19) and Pneumonia Associated with Lymphoma

Objective: To retrospectively compare the clinical features and chest computed tomography (CT) characteristics of coronavirus disease 2019 (COVID-19) and pneumonia in lymphoma patients. Materials and Methods: Ten lymphoma patients with pneumonia and 12 patients with COVID-19 infections were enrolled from January 15 to March 14, 2020. The clinical features were recorded. All pulmonary lesions on chest CT were assessed for location, shape, density and diffusion degree. Other typical CT features were also evaluated. Results: The most commonly observed patchy lesions were ground-glass opacities (GGOs) and mixed GGOs in both groups. Regarding the diffusion degree, 82% (92/112) of the lesions in the COVID-19 group were relatively limited, while 69% (52/75) of those in the lymphoma group were diffuse (p < 0.001). The proportions of interlobular septal thickening, vascular thickening, pleural involvement and fibrous stripes observed in the lymphoma cases were statistically compatible with those observed in the COVID-19 cases (p > 0.05). Air bronchograms were observed more frequently in COVID-19 patients (45%, 50/112) than in lymphoma patients with pneumonia (5%, 4/75) (p < 0.001). Halo sign (6%) and reversed halo sign (1%) were observed in several COVID-19 patients but not in lymphoma-associated pneumonia patients. Conclusion: Both lymphoma-associated pneumonia and COVID-19 generally manifested as patchy GGOs and mixed GGOs in more than one lobe. Compared to COVID-19, lymphoma-associated pneumonia tended to be relatively diffuse, with fewer air bronchograms, and no halo or reversed halo signs observed on chest CT.

COVID-19 severity scoring systems in radiological imaging - a review

The current reference standard to make a definitive diagnosis of SARS-CoV-2 infection is the reverse transcription- polymerase chain reaction assay (rt-PCR). However, radiological imaging plays a crucial role in evaluating the course of COVID-19 and in choosing proper management of infected patients. Chest X-ray (CXR) is generally considered not to be sensitive for the detection of pulmonary abnormalities in the early stage of the disease. However, in the emergency setting CXR can be a useful diagnostic tool for monitoring the rapid progression of lung involvement in COVID-19, especially in patients admitted to intensive care units. The rapid course of SARS-CoV-2 infection and the severity and progression of lung aberrations require a method of radiological evaluation to implement and manage the appropriate treatment for infected patients. Computed tomography (CT) imaging is considered to be the most effective method for the detection of lung abnormalities, especially in the early stage of the disease. Moreover, serial chest CT imaging with different time intervals is also effective in estimating the evolution of the disease from initial diagnosis to discharge from hospital. Despite having low specificity in distinguishing abnormalities in viral infections, the high sensitivity of CT makes this method ideal for assessing the severity of the disease in patients with confirmed COVID-19. In this review, we present and discuss currently available scales that can be used to assess the severity of lung involvement in COVID-19 patients in everyday work, both for CXR and CT imaging.

Early rehabilitation in post-acute COVID-19 patients: data from an Italian COVID-19 Rehabilitation Unit and proposal of a treatment protocol

BACKGROUND

Coronavirus disease 2019 (COVID-19) pandemic is quickly spreading, putting under heavy stress health systems worldwide and especially Intensive Care Units (ICU). Rehabilitation Units have a crucial role in reducing disability in order to reintroduce patients in the community.

AIM

The aim of this study is to characterize pulmonary function and disability status and to propose an early rehabilitation protocol in a cohort of post-acute COVID-19 patients admitted to an Italian Rehabilitation Unit.

DESIGN

Cross-sectional observational study.

SETTING

Inpatients Rehabilitation Unit.

POPULATION

Post-acute COVID-19 patients.

METHODS

Demographic, anamnestic and clinical characteristics, laboratory exams and medical imaging findings were collected for the entire cohort. Outcome measures evaluated at the admission in Rehabilitation Unit were: type of respiratory supports needed, fraction of inspired oxygen (FiO<inf>2</inf>), partial pressure of oxygen (PaO<inf>2</inf>), FiO<inf>2</inf>/PaO<inf>2</inf>, Barthel Index (BI), modified Medical Research Council (mMRC) Dyspnoea Scale, and 6-Minute Walking Test (6-MWT). Furthermore, we proposed an early rehabilitation protocol for COVID-19 patients based on baseline FiO2.

RESULTS

We included 32 post-acute COVID-19 patients (22 male and 10 female), mean aged 72.6±10.9 years. BI was 45.2±27.6, with patients in need of higher FiO<inf>2</inf> (≥40%) showing lower values: 39.6±25.7 vs. 53.3±29.3. All patients had grade 4 or 5 on the mMRC Dyspnea Scale. Only 14 COVID-19 patients were able to walk (43.7%). 6-MWT was feasible in 6 (18.8%) patients with a mean distance of 45.0±100.6 meters.

CONCLUSIONS

Taken together, our findings suggest that post-acute COVID-19 patients suffered from dyspnea and shortness of breath even for minimal activities, with a resulting severe disability, and only a few of them were able to perform 6-MWT with poor results. An early rehabilitation protocol was proposed according to the baseline conditions of the patients.

CLINICAL REHABILITATION IMPACT

This study could provide an accurate description of COVID-19 sub-acute patients admitted to a Rehabilitation Unit along with a proposal of treatment to help physicians to tailor the best possible rehabilitative treatment.

Automated detection and quantification of COVID-19 pneumonia: CT imaging analysis by a deep learning-based software

BACKGROUND

The novel coronavirus disease 2019 (COVID-19) is an emerging worldwide threat to public health. While chest computed tomography (CT) plays an indispensable role in its diagnosis, the quantification and localization of lesions cannot be accurately assessed manually. We employed deep learning-based software to aid in detection, localization and quantification of COVID-19 pneumonia.

METHODS

A total of 2460 RT-PCR tested SARS-CoV-2-positive patients (1250 men and 1210 women; mean age, 57.7 ± 14.0 years (age range, 11-93 years) were retrospectively identified from Huoshenshan Hospital in Wuhan from February 11 to March 16, 2020. Basic clinical characteristics were reviewed. The uAI Intelligent Assistant Analysis System was used to assess the CT scans.

RESULTS

CT scans of 2215 patients (90%) showed multiple lesions of which 36 (1%) and 50 patients (2%) had left and right lung infections, respectively (> 50% of each affected lung's volume), while 27 (1%) had total lung infection (> 50% of the total volume of both lungs). Overall, 298 (12%), 778 (32%) and 1300 (53%) patients exhibited pure ground glass opacities (GGOs), GGOs with sub-solid lesions and GGOs with both sub-solid and solid lesions, respectively. Moreover, 2305 (94%) and 71 (3%) patients presented primarily with GGOs and sub-solid lesions, respectively. Elderly patients (≥ 60 years) were more likely to exhibit sub-solid lesions. The generalized linear mixed model showed that the dorsal segment of the right lower lobe was the favoured site of COVID-19 pneumonia.

CONCLUSION

Chest CT combined with analysis by the uAI Intelligent Assistant Analysis System can accurately evaluate pneumonia in COVID-19 patients.