Coronavirus-infected Patients Research Articles

Fully automated unified prognosis of Covid-19 chest X-ray/CT scan images using Deep Covix-Net model.

SARS-COV2 (Covid-19) prevails in the form of multiple mutant variants causing pandemic situations around the world. Thus, medical diagnosis is not accurate. Although several clinical diagnostic methodologies have been introduced hitherto, chest X-ray and computed tomography (CT) imaging techniques complement the analytical methods (for instance, RT-PCR) to a certain extent. In this context, we demonstrate a novel framework by employing various image segmentation models to leverage the available image databases (9000 chest X-ray images and 6000 CT scan images). The proposed methodology is expected to assist in the prognosis of Covid-19-infected individuals through examination of chest X-rays and CT scans of images using the Deep Covix-Net model for identifying novel coronavirus-infected patients effectively and efficiently. The slice of the precision score is analysed in terms of performance metrics such as accuracy, the confusion matrix, and the receiver operating characteristic curve. The result leans on the database obtainable in the GitHub and Kaggle repository, conforming to their endorsed chest X-ray and CT images. The classification performances of various algorithms were examined for a test set with 1800 images. The proposed model achieved a 96.8% multiple-classification accuracy among Covid-19, normal, and pneumonia chest X-ray databases. Moreover, it attained a 97% accuracy among Covid-19 and normal CT scan images. Thus, the proposed mechanism achieves the rigorousness associated with the machine learning technique, providing rapid outcomes for both training and testing datasets.

Astaxanthin protective barrier and its ability to improve the health in patients with COVID-19.

Inflammation acts like a double-edged sword and can be harmful if not appropriately controlled. COVID-19 is created through a novel species of coronavirus SARS-CoV-2 (2019-nCoV). Elevated levels of inflammatory factors such as interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), etc. lead to Acute Respiratory Distress Syndrome (ARDS) and severe complications of infection in the lungs of coronavirus-infected patients. Astaxanthin is a natural and potent carotenoid with powerful antioxidant activity as well as an anti-inflammatory agent that supports good health. The effects of astaxanthin on the regulation of cyclooxygenase-2 (COX-2) pathways and the reduction and suppression of cytokines and other inflammatory agents such as IL-6 and TNF-α have already been identified. Therefore, these unique features can make this natural compound an excellent option to minimize inflammation and its consequences.

Echocardiography in suspected coronavirus infection: indications, limitations and impact on clinical management

ObjectivesTo describe the use of echocardiography in patients hospitalised with suspected coronavirus infection and to assess its impact on clinical management.MethodsWe studied 79 adults from a prospective registry of inpatients...

Deep learning techniques for detection of covid-19 using chest x-rays

The COVID-19 pandemic situation keeps on ruining and affecting the wellbeing and prosperity of the worldwide population and due to this situation, the doctors around the world are working restlessly, as the coronavirus is increasing exponentially and the situation for testing has become quite a problematic and with restricted testing units, it’s impossible for every patient to be tested with available facilities. Effective screening of infected patients through chest X-ray images is a critical step in combating COVID-19. With the help of deep learning techniques, it is possible to train various radiology images and detect COVID-19. The dataset used in our research work is gathered from different sources and a specific new dataset is generated. The proposed methodology implemented is beneficial to the medical practitioner for the diagnosis of coronavirus infected patients where predictions can be done automated using deep learning. The deep learning algorithms that are used to predict the COVID with the help of chest X-ray images are evaluated for their prediction based on performance metrics such as accuracy, precision, Recall, and F1-score. In this work, the proposed model has used deep learning techniques for COVID-19 prediction and the results have shown superior performance in prediction of COVID-19. © 2021, International Institute for General Systems Studies. All rights reserved.

Effect of Coronavirus Infection on Fasting Blood Glucose, Kidney Function, and Electrolytes in COVID-19 Patients in the Zawia Region, Western Libya

Background: Coronavirus disease 19 (COVID-19) is a pandemic infectious disease caused by the novel coronavirus. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). It is an aggressive virus that spread worldwide and is a systemic disease involving multiple systems, including respiratory, cardiovascular, gastrointestinal, hematopoietic, neurological, immune, and urinogenital systems. Objectives: The present study aimed to evaluate the alteration in fasting blood glucose, serum urea, creatinine, Na+, K+, and Cl- levels among COVID-19 patients in the Zawia region, Western Libya. Materials and Methods: 416 confirmed COVID-19 patients hospitalized in the Isolation Centre located in Zawia city, Libya. From the 1st May 2020 to the 30th March 2021, were enrolled in this prospective study. Covid-19 patients were defined as positive cases after the detection of SARS-CoV-2 RNA in oro-nasopharyngeal swab samples. Demographic data were extracted from electronic medical records and patient files. Also, 30 healthy individuals without any chronic disease or respiratory symptoms were recruited for the control group. Blood samples were collected via vein puncture for estimating biochemical parameters (fasting blood glucose, serum urea, creatinine, Na+, K+, and Cl- concentrations). The statistical significance of differences between groups was evaluated with the Mann- Whitney (U test). Associations between different parameters were evaluated with the Spearman's test. Results: The results showed that coronavirus infection induced a significant increase in fasting blood glucose, serum urea, and creatinine concentrations. Infections also induced a decrease in serum sodium ion concentration, compared with healthy individuals. Seventy-six percent of corona virus-infected patients had hyperglycemia. Similarly, high levels of serum urea, creatinine, Cl-, Na+, and K+ were found in 40.9%, 39.9%, 27.9%, 8.9% and 6.5% of patients, respectively. Hyponatraemia, hypokalaemia, and hypochloremia were found in 35.5%, 13.7%, and 12.9% of patients. There were recorded a significant positive association between fasting blood glucose and serum urea, creatinine, and K+ concentration, between serum urea concentration and serum creatinine, K+, and Cl- concentrations, between serum creatinine and K+, and Cl- concentrations, and between serum Na+ and Cl- concentration, and a significant negative association between fasting blood glucose and serum Na+ and Cl- concentrations and between serum K+ and Na+ concentrations. Conclusion: It can be concluded that coronavirus infections induced increases in fasting blood glucose, serum urea, and creatinine, and a decrease in Na+ concentrations. There was a significant association between different parameters. These biochemical changes may help the clinicians to understand COVID-19 better and provide more clinical treatment options and prevent the serious complications of the disease. Thus, clinicians should pay special attention to fasting blood glucose, kidney function and electrolyte status of COVID-19 patients. Changes in fasting blood glucose, kidney function, and electrolyte levels can be a good indicator of disease progression.

Artemisia and Artemisia-based products for COVID-19 management: current state and future perspective

The search for a potent anti-coronavirus therapy for severe acute respiratory syndrome coronavirus type-2 (SARS-CoV-2) remains an overwhelming task since the outbreak of COVID-19. It is more evident that most of the existing antiviral and immune-boosting drugs are non-promising and ineffective for the treatment of coronavirus infected patients while the safety of a few drugs/vaccines that have demonstrated high potential remains unclear. With daily records of confirmed infectious cases across the world, it is crucial to emphasize the need for repurposed therapies with a validated ethnomedicinal base focused on well-known active medicines with traceable biochemical, pharmacological and safety profiles for viral infection management. In the present study, recent literature on Artemisia and Artemisia-based products for the management of COVID-19 are reviewed. Artemisia-based products have demonstrated a broad spectrum of biological ability including antiviral properties. Besides its antiviral activity, Artemisia annua have shown to contain appreciable amounts of minerals such as zinc, gallium and selenium among others.Graphic abstract

Epidemiology and clinical features of common community human coronavirus disease.

BackgroundWe would evaluate the epidemiology, clinical aspects, and prognostic factors of patients of all ages admitted with human corona virus (HCoV).MethodsThis study was retrospectively performed at five university teaching hospitals between 1st January 2018 and 31th March 2020. Routine molecular testing using for multiplex real-time reverse transcription-polymerase chain reaction (RT-PCR) methods was conducted on the respiratory viruses. We assessed the demographics, laboratory findings, and treatment of patients infected with coronavirus.ResultsThere were 807 coronavirus-infected patients from 24,311 patients with respiratory virus PCR test admitted to five hospitals over 27 months. All-cause mortality rates of patients admitted for seasonal HCoV disease were 3.1% in all patients and 10.8% in patients aged ≥18 years. The Cox proportional hazard regression analysis was performed in patients aged ≥18 years. After adjusting for other clinical variables, general weakness symptoms [hazard ratio (HR), 2.651; 95% confidence interval (CI), 1.147–6.125, P=0.023], National Early Warning Score (NEWS) ≥2 (HR, 5.485; 95% CI, 1.261–23.858, P=0.023), and coronavirus subtype OC43 (HR, 2.500; 95% CI, 1.060–5.897, P=0.036) were significantly associated with death from coronavirus.ConclusionsCoronavirus infection can reveal a higher mortality rate in patients of ≥18 than those of <18 years, thus, adult patients require more careful treatment. Furthermore, in adult patients, the factors associated with death from coronavirus include general weakness symptoms, NEWS higher than 2, and OC43 subtype.

Micronutrients and Infection with COVID-19: A Critical Mini-Review

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has been the cause of a global pandemic. Given the impact of nutritional status upon immune function, it is crucial to understand the relationship between micronutrient intake and severity of the disease. This mini-review aimed to summarize the known associations between specific micronutrients (vitamin A, D, E, C and zinc, selenium and magnesium) and the health of coronavirus-infected patients. Low serum levels of these micronutrients are associated with the incidence and severity of SARS-CoV-2. However, further studies are needed to evaluate the outcomes of supplementation with these nutrients.

COVID-19: Automatic detection from X-ray images by utilizing deep learning methods

In recent months, a novel virus named Coronavirus has emerged to become a pandemic. The virus is spreading not only humans, but it is also affecting animals. First ever case of Coronavirus was registered in city of Wuhan, Hubei province of China on 31st of December in 2019. Coronavirus infected patients display very similar symptoms like pneumonia, and it attacks the respiratory organs of the body, causing difficulty in breathing. The disease is diagnosed using a Real-Time Reverse Transcriptase Polymerase Chain reaction (RT-PCR) kit and requires time in the laboratory to confirm the presence of the virus. Due to insufficient availability of the kits, the suspected patients cannot be treated in time, which in turn increases the chance of spreading the disease. To overcome this solution, radiologists observed the changes appearing in the radiological images such as X-ray and CT scans. Using deep learning algorithms, the suspected patients’ X-ray or Computed Tomography (CT) scan can differentiate between the healthy person and the patient affected by Coronavirus. In this paper, popular deep learning architectures are used to develop a Coronavirus diagnostic systems. The architectures used in this paper are VGG16, DenseNet121, Xception, NASNet, and EfficientNet. Multiclass classification is performed in this paper. The classes considered are COVID-19 positive patients, normal patients, and other class. In other class, chest X-ray images of pneumonia, influenza, and other illnesses related to the chest region are included. The accuracies obtained for VGG16, DenseNet121, Xception, NASNet, and EfficientNet are 79.01%, 89.96%, 88.03%, 85.03% and 93.48% respectively. The need for deep learning with radiologic images is necessary for this critical condition as this will provide a second opinion to the radiologists fast and accurately. These deep learning Coronavirus detection systems can also be useful in the regions where expert physicians and well-equipped clinics are not easily accessible.

Recovering Infrastructure Public-Private Partnership Projects as Effective «Epinomic» Policy in Fighting the COVID-19 Pandemic

The emergency conditions caused by the coronavirus pandemic in 2020 made the national governments the last resort, which was forced to bear all the financial costs associated with the lockdown in the national economy, with social support of the population and fiscal and monetary help to private firms which business was blocked. Lockdowns, publicly declared in countries around the world to stop the exponential growth of coronavirus-infected patients, have brought unprecedented losses in both human lives and national welfare. As a result, the coronavirus pandemic left two fundamental priorities for the state: (1) to stabilize the epidemiological situation in the country and (2) to reopen the economy in time after the lockdown. On this basis, the term "epinomics" was introduced, which assumes the primary public task to ensure the life and health of citizens, and only under this condition allows the possibility of economic recovery. In this case, the expansion of the practice of implementing public infrastructure projects on the basis of public-private partnership realizes the essence of the state’s epinomic strategy. Moreover, in the post-COVID-19 future, infrastructure projects can become an effective form of implementation of the UN “human-first” model, since they allow solving the immediate problems of ordinary citizens mostly affected in 2020. It is about the growth of employment, the provision of workforce wages, development of socially significant infrastructure, which contribution to the economic revival of countries can hardly be overestimated. At the same time, the government through public-private partnership gets the opportunity to directly broadcast to society the results of the effectiveness of its epinomic strategy in stabilizing the epidemiological situation and reopening the economy after the lockdown.

Amantadine in the prevention of clinical symptoms caused by SARS-CoV-2.

BackgroundAmantadine is a drug that can help in the prevention of SARS-CoV-2 symptomatology, as has been demonstrated in observational clinical studies.MethodsWe searched in the PubMed database Clinical Studies of coronavirus-infected patients who have been treated with amantadine in a preventive manner as well as patients with Parkinson’s disease.ResultsFour clinical studies were found in which relatives of patients with COVID-19 had been prescribed the use of amantadine in a preventive manner to avoid the symptoms caused by the coronavirus.ConclusionAmantadine is a drug that can be prescribed as a prophylactic that prevents symptomatology caused by SARS-CoV-2 coronavirus.

Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients

The SARS-COV-2 pandemic has put pressure on intensive care units, so that identifying predictors of disease severity is a priority. We collect 58 clinical and biological variables, and chest CT scan data, from 1003 coronavirus-infected patients from two French hospitals. We train a deep learning model based on CT scans to predict severity. We then construct the multimodal AI-severity score that includes 5 clinical and biological variables (age, sex, oxygenation, urea, platelet) in addition to the deep learning model. We show that neural network analysis of CT-scans brings unique prognosis information, although it is correlated with other markers of severity (oxygenation, LDH, and CRP) explaining the measurable but limited 0.03 increase of AUC obtained when adding CT-scan information to clinical variables. Here, we show that when comparing AI-severity with 11 existing severity scores, we find significantly improved prognosis performance; AI-severity can therefore rapidly become a reference scoring approach.

Developments in Nano-materials and Analysing its role in Fighting COVID-19

Nanomaterials like silver, iron, ceramic, graphene carbon nanotubes, etc. These are used to develop and create multifunctional materials to fight the corona virus. This work focuses on analyzing and discussing the developments of Nano-materials and their effectiveness in fighting and preventing the spread of the corona virus. The paper also analyses the use of Nano-materials in the development of vaccines and anti-viral drugs. However, the use of carbon-based materials like carbon dots and other forms of carbon has not only helped in increasing the protection levels in human life but also provided greater security and freedom for people to carry out day-to-day activities without any fear of being infected by the virus. The application of graphene-based materials for making unique face masks and germ trap technologies is presented. Nano-compounds blended with hand sanitizers have played an active role in the control of coronavirus along with soap-based liquids that are used for handwashing. Some of the Nano-materials like gold nanoparticles are extensively used in the making of detection devices like RT-PCR, etc. The use of Nano-polymer coatings has created a safe environment for users by preventing the spread of coronavirus through surfaces. Different coating methods used for the application of nanomaterials are explained with suitable technical interpretations The anti-viral efficiency of different coatings is also discussed through surfaces. Nano-materials and contributions from the synthetic biology area have helped to develop vaccines and anti-viral drugs which are presently used to cure and prevent the spread of coronavirus infected patients. The method followed in analyzing the Nano-materials and their applications mainly focused on tracing the development and applications of Nano-materials. This analysis proves and shows that Nano-materials are playing a vital role in fighting the corona virus.

Состояние плазменного звена гемостаза у пациентов с коронавирусной инфекцией, вызванной вирусом SARS-CоV-2.

Введение. Пандемия COVID-19 стала глобальной проблемой мирового сообщества. Основным патогенетическим механизмом заболевания представляется развитие иммунного тромбоза, результатом которого являются нарушение микроциркуляции, артериальные и венозные тромбозы, респираторный дистресс-синдром, полиорганная недостаточность. Изучение механизмов развития гиперкоагуляционных изменений у пациентов с COVID-19 вызывает огромный интерес и позволит улучшить исходы заболевания. Цель исследования: оценка состояния плазменного звена гемостаза у пациентов с коронавирусной инфекцией в остром периоде заболевания. Материалы и методы. Обследованы 59 пациентов с тяжелым и среднетяжелым течением коронавирусной инфекции, получавшие антикоагулянтную профилактику. Определяли следующие параметры системы гемостаза: активированное парциальное тромбопластиновое время, протромбиновый тест, концентрацию фибриногена, активность фактора VIII, антитромбина, протеинов C и S, содержание D-димера, фактора Виллебранда и гомоцистеина, а также генерацию тромбина методом калиброванной автоматизированной тромбинографии. Результаты. У пациентов с COVID-19 по сравнению со здоровыми лицами было выявлено увеличение концентрации фибриногена, уровня фактора Виллебранда, гомоцистеина и D-димера, значительное снижение уровня свободного протеина S, усиление генерации тромбина, снижение чувствительности к тромбомодулину. Была выявлена прямая корреляция между тяжестью состояния пациентов и уровнями фактора Виллебранда и гомоцистеина. Заключение. Несмотря на проводимую антикоагулянтную терапию, у пациентов с коронавирусной инфекцией отмечены выраженные признаки активации системы гемостаза, которые характеризуются как повышением отдельных маркеров гиперкоагуляции, так и значимым усилением генерации тромбина на фоне угнетения работы системы протеина С. Повышенный уровень гомоцистеина плазмы крови является дополнительным фактором риска, ухудшающим течение заболевания. Значительное повышение уровня фактора Виллебранда может быть неблагоприятным прогностическим признаком течения заболевания. Background. The COVID-19 pandemic is a global health care challenge. The concept of immunothrombosis has established as a central pathogenic factor leading to thrombosis complications, respiratory insufficiency and multiple organ failure. The study of hypercoagulability mechanisms in patients with COVID-19 may be useful for improving disease’s outcomes. Objectives: to evaluate plasma hemostasis in patients with coronavirus infection at the acute period of the disease. Patients / Methods. We examined 59 patients with severe and moderate coronavirus infection who received anticoagulant treatment. The following hemostasis parameters were determined: activated partial thromboplastin time, prothrombin test, fibrinogen, factor VIII, von Willebrand factor, D-dimer, protein C and S, homocysteine, and thrombin generation. Results. Fibrinogen, von Willebrand factor, D-dimer, homocysteine, and thrombin generation were higher in patients with COVID-19 than in healthy people, protein S was reduced. The direct correlation between the severity of the patient’s condition and the levels of von Willebrand factor and homocysteine was found. Conclusions. Patients with COVID-19 had significant hypercoagulability despite of the anticoagulant treatment. Signs of hemostasis activation are characterized by both increasing of hypercoagulation individual markers and thrombin generation with inhibition of protein C system. High level of plasma homocysteine is an additional risk factor that worsens the disease course. High level of von Willebrand factor may be an unfavorable prognostic sign of the disease course.

A blood transcriptome-based analysis of disease progression, immune regulation, and symptoms in coronavirus-infected patients

COVID-19 patients show heterogeneity in clinical presentation and outcomes that makes pandemic control and strategy difficult; optimizing management requires a systems biology approach of understanding the disease. Here we sought to potentially understand and infer complex disease progression, immune regulation, and symptoms in patients infected with coronaviruses (35 SARS-CoV and 3 SARS-CoV-2 patients and 57 samples) at two different disease progression stages. Further, we compared coronavirus data with healthy individuals (n = 16) and patients with other infections (n = 144; all publicly available data). We applied inferential statistics (the COVID-engine platform) to RNA profiles (from limited number of samples) derived from peripheral blood mononuclear cells (PBMCs). Compared to healthy individuals, a subset of integrated blood-based gene profiles (signatures) distinguished acute-like (mimicking coronavirus-infected patients with prolonged hospitalization) from recovering-like patients. These signatures also hierarchically represented multiple (at the system level) parameters associated with PBMC including dysregulated cytokines, genes, pathways, networks of pathways/concepts, immune status, and cell types. Proof-of-principle observations included PBMC-based increases in cytokine storm-associated IL6, enhanced innate immunity (macrophages and neutrophils), and lower adaptive T and B cell immunity in patients with acute-like disease compared to those with recovery-like disease. Patients in the recovery-like stage showed significantly enhanced TNF, IFN-γ, anti-viral, HLA-DQA1, and HLA-F gene expression and cytolytic activity, and reduced pro-viral gene expression compared to those in the acute-like stage in PBMC. Besides, our analysis revealed overlapping genes associated with potential comorbidities (associated diabetes) and disease-like conditions (associated with thromboembolism, pneumonia, lung disease, and septicemia). Overall, our COVID-engine inferential statistics platform and study involving PBMC-based RNA profiling may help understand complex and variable system-wide responses displayed by coronavirus-infected patients with further validation.

PRS81 Insights into the Coronavirus Disease Perceptions in Pakistan

Pakistan is the last country among its immediate neighbors (China, Iran, Afghanistan, and India) to report coronavirus infected patients despite the virus outbreak in December-2019 in China. First case of coronavirus (COVID-19) was reported on February 26, 2020 in Pakistan. Since then, amid social distancing and lock-downs, more Pakistanis are looking to connect on social media for work as well as seeking government apps to address COVID-19 concerns. However, the lack of verified facts and floating rumors through social media is a big cause of this panic during once-in-a-century pandemic.

A deep transfer learning model with classical data augmentation and CGAN to detect COVID-19 from chest CT radiography digital images.

The Coronavirus disease 2019 (COVID-19) is the fastest transmittable virus caused by severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2). The detection of COVID-19 using artificial intelligence techniques and especially deep learning will help to detect this virus in early stages which will reflect in increasing the opportunities of fast recovery of patients worldwide. This will lead to release the pressure off the healthcare system around the world. In this research, classical data augmentation techniques along with Conditional Generative Adversarial Nets (CGAN) based on a deep transfer learning model for COVID-19 detection in chest CT scan images will be presented. The limited benchmark datasets for COVID-19 especially in chest CT images are the main motivation of this research. The main idea is to collect all the possible images for COVID-19 that exists until the very writing of this research and use the classical data augmentations along with CGAN to generate more images to help in the detection of the COVID-19. In this study, five different deep convolutional neural network-based models (AlexNet, VGGNet16, VGGNet19, GoogleNet, and ResNet50) have been selected for the investigation to detect the Coronavirus-infected patient using chest CT radiographs digital images. The classical data augmentations along with CGAN improve the performance of classification in all selected deep transfer models. The outcomes show that ResNet50 is the most appropriate deep learning model to detect the COVID-19 from limited chest CT dataset using the classical data augmentation with testing accuracy of 82.91%, sensitivity 77.66%, and specificity of 87.62%.

Cutaneous Manifestation of COVID-19: A Short Clinical Case

Much is now known about the respiratory presentation of coronavirus SARS-CoV-2 (COVID-19) but it can also show up with clinical manifestations in other locations, such as on the skin. Herein, we describe a case with cutaneous symptoms that emerged during the recovery phase in a SARS-CoV-2 coronavirus infected patient. It is important for the healthcare professionals as well as the patients to know about such scenarios, so that appropriate action can be readily taken.

Pharmacists as Frontline Responders During COVID-19: Roles and Responsibilities Need to be Revisited.

The ongoing pandemic has disrupted the health care system, creating challenges for health care workers and patients alike. As workflows and job responsibilities have been adapted to provide care to coronavirus-infected patients, many primary care services have been postponed. This change has led to significant financial impacts that will be difficult to overcome. Ambulatory care pharmacists can help fill gaps both in access to primary care services and in the financial deficit, if given the opportunity to practice at the top of their skillset and bill for their face-to-face and telehealth services both during and after the pandemic.

Medical Potential Of A Locally Sourced Lipids Mixture On Confirmed Corona Virus Infected Patients And Those At Risk of Infection, Attending National Hospital Abuja, Nigeria.-An Evidence Based Approach

Medical Potential Of A Locally Sourced Lipids Mixture On Confirmed Corona Virus Infected Patients And Those At Risk of Infection, Attending National Hospital Abuja, Nigeria.-An Evidence Based Approach