Performance Analysis of GAN Approaches in the Portable Chest X-Ray Synthetic Image Generation for COVID-19 Screening

COVID-19 mainly affects lung tissues, aspect that makes chest X-ray imaging useful to visualize this damage. In the context of the global pandemic, portable devices are advantageous for the daily practice. Furthermore, Computer-aided Diagnosis systems developed with Deep Learning algorithms can support the clinicians while making decisions. However, data scarcity is an issue that hinders this process. Thus, in this work, we propose the performance analysis of 3 different state-of-the-art Generative Adversarial Networks (GAN) approaches that are used for synthetic image generation to improve the task of automatic COVID-19 screening using chest X-ray images provided by portable devices. Particularly, the results demonstrate a significant improvement in terms of accuracy, that raises 5.28% using the images generated by the best image translation model. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

[The Dutch covid-19 testing policy urgently needs revision]

A self-test suffices for the diagnosis SARS-CoV-2 infection in the Netherlands since 11 April 2022. Yet, selected groups such as health care workers can still divert to the Public Health Services (PHS) SARS-CoV-2 testing facilities for a nucleic acid amplification test. A survey among 2257 subjects visiting PHS Kennemerland testing sites demonstrates that the majority of participants does however not belong to one of the selected groups. Most subjects visit the PHS to confirm the result of their home test. The infrastructure and personnel needed to maintain the PHS testing sites come at high costs, which are in striking contrast to the government objectives and the low number of current visitors. The Dutch covid-19 testing policy therefore urgently needs revision.

Sociodemographic and clinical characteristics of SARS-CoV-2 infected population during the second and third epidemiological waves in Sri Lanka

Objective: To analyze data on socio-demographic and clinical characteristics of SARS-CoV-2 infected population whose samples were received from Medical Research Institute, Sri Lanka. Method(s): Laboratory based retrospective study was done on patient samples which were tested positive for SARS-CoV-2 by National Reference Virology Laboratory at the Medical Research Institute, Sri Lanka, from November, 2020 to November, 2021. Data on socio-demographic characteristics and clinical presentation of 13 126 patients were examined. Result(s): The mean age of the study population was (36.0+/-7.2) years and the majority were men (64.0%). The highest number of positive cases were found in the 21-30 years-of-age group. Two distinct peaks were noted in the incidence of SARS-CoV-2 positive individuals. In addition, 42.5% of the positive samples tested positive (42.5%) were from Medical Officer of Health collection centres. Furthermore, 60.6% (7 951) of the infected subjects were asymptomatic whereas the remaining were symptomatic. The highest percentage of symptomatic patients were observed in the 91-100 years-of-age group while the highest asymptomatic subjects were found in the 31-40 years-of-age group. The percentage of asymptomatic children (65.3%) was significantly (P<0.05) higher than that of adults (43.4%). Conclusion(s): The findings of this study aid decision makers to focus on the vulnerable groups, and geographic and temporal distribution of patients in the public health strategies that aim at preventing the spread of the disease and reducinig its mortalities.Copyright © 2023 Wolters Kluwer Medknow Publications. All rights reserved.

Problems of PCR diagnostics OF COVID-19.

To date, an adequate and timely assessment of the number of cases is the basis of effective measures aimed at preventing the spread of COVID-19 infection. Real-time reverse transcription polymerase chain reaction (RT-PCR) remains the gold standard for confirming COVID-19. The purpose of the work: to analyze the experience of the city virological center of the S.P. Botkin Clinical Infectious Diseases Hospital (Botkin Hospital) for the examination for the presence of SARS-CoV-2 coronavirus by PCR in the period from 2020 to 2022. Materials and methods. The systematization of PCR studies on COVID-19 for the period 2020-2022 was carried out. A total of 221,901 people were examined, positive results were obtained in 55,372 (24.95%). Among the contingents of the examined patients, patients who underwent inpatient treatment at the Botkin Hospital, Conclusions. This study analyzed the possible causes of false-positive and false-negative PCR results. The correlation of the number of positive results with the dynamics of detection of new cases of COVID-19 in St. Petersburg during the 2020-2022 pandemic is shown. It has been established that the proportion of patients examined more than 3 times during the period of hospitalization remains significant. This fact requires the closest attention, given the high cost and laboriousness of PCR studies.Copyright © 2022 Authors. All rights reserved.

[Early alert of COVID-19 outbreaks to plan the response in the IMSS]

The Instituto Mexicano del Seguro Social (IMSS) developed and implemented epidemic monitoring and modeling tools to support the organization and planning of an adequate and timely response to the COVID-19 health emergency. The aim of this article is to describe the methodology and results of the early outbreak detection tool called COVID-19 Alert. An early warning traffic light was developed that uses time series analysis and a Bayesian method of early detection of outbreaks from electronic records on COVID-19 for suspected cases, confirmed cases, disabilities, hospitalizations, and deaths. Through Alerta COVID-19, the beginning of the fifth wave of COVID-19 in the IMSS was detected in a timely manner, three weeks before the official declaration. The proposed method is aimed at generating early warnings before the start of a new wave of COVID-19, monitoring the serious phase of the epidemic, and supporting decision-making within the institution;unlike other tools that have an approach aimed at communicating risks to the community. We can conclude that the Alerta COVID-19 is an agile tool that incorporates robust methods for the early detection of outbreaks. Copyright © 2023 Revista Medica del Instituto Mexicano del Seguro Social.

One case of novel coronavirus pneumonia complicated with acute appendicitis in children.

Emergent laparoscopic appendectomy was performed for a boy of occult novel coronavirus pneumonia with a presenting symptom of acute appendicitis at Wuhan Children's Hospital. Postoperative lung computed tomography (CT) indicated a round dense shadow with slightly ground-glass-like margins in the dorsal segment of right lower lung. Pharyngeal swab nucleic acid test was positive for 2019-nCoV and thus a definite diagnosis of COVID-19 was made. Prior to the onset, he had close contacts with his grandmother with a definite diagnosis of COVID -19. It proved that intra-family transmission was an important transmission route for pediatric 2019-nCoV infection. In this case, the respiratory symptoms of COVID-19 were not obvious during an early stage. The major symptoms were nausea, vomiting and abdominal pain. For individuals coming from the epidemic area, with a history of exposure and developing acute surgical conditions, preoperative pulmonary CT scan is necessary for screening COVID-19.Copyright © 2020 by the Chinese Medical Association.

Reactivation of Tuberculosis and COVID-19 in Pediatric Patients

Objective Mycobacterium tuberculosis is an immobile aerobic bacillus that causes tuberculosis (TB) disease. We aimed to evaluate the association between coronavirus disease 2019 (COVID-19), COVID-19-related drugs, TB reactivation, and TB incidence during the pandemic. Methods Eight patients who were diagnosed as having TB in Meram Medical Faculty, Necmettin Erbakan University between March 1, 2020, and December 31, 2021, at the beginning of the pandemic, were enrolled in this study. The presence of COVID-19 infection was confirmed using COVID-19 antibody tests and the patients' COVID-19 history. We evaluated the demographic data, laboratory findings, imaging tests, and pathology results of all patients. Results We checked all our patients with TB using COVID-19 antibodies (immunoglobulin [Ig]G + IgM) or polymerase chain reaction. Seven of the eight patients were female (87.5%). The median age was 16 years. Family screening of all patients was negative, and they had bacillus Calmette-Guerin vaccine scars. Two patients had chronic diseases. One was diagnosed as having primary ciliary dyskinesia in our department (patient no. 8) and the second was under follow-up by the rheumatology department with a diagnosis of juvenile idiopathic rheumatoid arthritis. Conclusion There has been an increase in the incidence of TB in children, especially in adolescents, during the pandemic period. This may be due to the pathogenic structure of the COVID-19 virus with an unknown mechanism. In addition, lifestyle changes and changes in health care policies during the pandemic may have caused this. Further research should be performed on this topic.Copyright © 2023 Authors. All rights reserved.

Integrated smart analytics of nucleic acid amplification tests via paper microfluidics and deep learning in cloud computing

Pandemics such as COVID-19 have exposed global inequalities in essential health care. Here, we proposed a novel analytics of nucleic acid amplification tests (NAATs) by combining paper microfluidics with deep learning and cloud computing. Real-time amplifications of synthesized SARS-CoV-2 RNA templates were performed in paper devices. Information pertained to on-chip reactions in time-series format were transmitted to cloud server on which deep learning (DL) models were preloaded for data analysis. DL models enable prediction of NAAT results using partly gathered real-time fluorescence data. Using information provided by the G-channel, accurate prediction can be made as early as 9 min, a 78% reduction from the conventional 40 min mark. Reaction dynamics hidden in amplification curves were effectively leveraged. Positive and negative samples can be unbiasedly and automatically distinguished. Practical utility of the approach was validated by cross-platform study using clinical datasets. Predicted clinical accuracy, sensitivity and specificity were 98.6%, 97.6% and 99.1%. Not only the approach reduced the need for the use of bulky apparatus, but also provided intelligent, distributable and robotic insights for NAAT analysis. It set a novel paradigm for analyzing NAATs, and can be combined with the most cutting-edge technologies in fields of biosensor, artificial intelligence and cloud computing to facilitate fundamental and clinical research.Copyright © 2023 Elsevier Ltd

[Prolonged Post-Covid-19 Anemia]

INTRODUCTION: In February 2020, the World Health Organization (WHO) designated Covid-19 as a global pandemic, resulting in a growing population of individuals with a wide range of persistent symptoms after acute SARS-CoV-2 infection. According to the categories proposed by the WHO, the symptoms can be regarded as post-Covid if they developed during or after the Covid-19, continue >2 months and are not explained by an alternative diagnosis. Common persistent symptoms include fatigue, dyspnea, and decreased exercise capacity. Even though at diagnosis Covid- 19 has prominent hematologic manifestations, they mostly resolve after recovery from acute illness. We present a case of a 58-year-old male, without prior medical conditions, who developed a profound and prolonged anemia following mild Covid-19.

[Prolonged Post-Covid-19 Anemia]

INTRODUCTION: In February 2020, the World Health Organization (WHO) designated Covid-19 as a global pandemic, resulting in a growing population of individuals with a wide range of persistent symptoms after acute SARS-CoV-2 infection. According to the categories proposed by the WHO, the symptoms can be regarded as post-Covid if they developed during or after the Covid-19, continue >2 months and are not explained by an alternative diagnosis. Common persistent symptoms include fatigue, dyspnea, and decreased exercise capacity. Even though at diagnosis Covid- 19 has prominent hematologic manifestations, they mostly resolve after recovery from acute illness. We present a case of a 58-year-old male, without prior medical conditions, who developed a profound and prolonged anemia following mild Covid-19.

Potential Health Survey of Traditional Spices & Herbs in Prevention and Treatment of COVID-19: A Review

The coronavirus (COVID-19) is a global public health pandemic disease emerged from the novel strain of the coronavirus 2 (SARS-CoV-2) that caused severe acute respiratory syndrome. It is the most significant respiratory illness that has affected the world since World War II. Currently, there is no globally approved drug for the treatment of pandemic COVID-19 except for some recently approved vaccines. Instead, various non-specific treatment options are being utilized by different countries. While some of these are effective, there is a lack of well-documented studies on the impact of traditional medicines on the management of SARS-CoV-2 in vitro and in silico. For thousands of years, traditional healers have been using various herbs and spices products and dietary plants to treat various diseases. This review aims to provide information on the use of traditional spices & herbs in COVID-19 protection and treatment and present the main characteristics of these products and their potential antiviral actions. Various databases were searched for articles related to the use of various herbs for the treatment of viral infections. Many of these studies show that various plant compounds can be utilized for the treatment of viral infections. This study aims to summarize the common used of herbal products and dietary supplements with potent bioactive compounds in treatment or prevent of COVID-19.

Increasing the Level of Neopterin in patients infected with SARS-CoV-2 Indicates Fatal Mortality

Background: The severity of Coronavirus Disease-2019 (COVID-19) cases is associated with hyperinflammation. Patients with critical and severe COVID-19 have been observed to have high amounts of circulating cytokines. Neopterin, a crucial cytokine in the antiviral immune response that is released by macrophages upon stimulation with interferon-gamma, can be utilized to forecast the severity of illness in COVID-19 patients. Methods: The study included 185 patients with COVID-19. The patients with COVID-19 were divided into three groups according to disease severity as critical disease (n=51), severe disease (n=81), and moderate disease (n=53). All basic demographic and clinical data of the patients were recorded and blood samples were collected. Results: Neopterin levels were significantly higher in critical COVID-19 patients compared with severe and moderate COVID-19 patients (p < 0.0001). Further, neopterin showed significantly higher levels in the age group >50 years of patients with COVID-19 than in the age group <50 years. Neopterin levels were correlated with WBCs, Platelet, CRP, D-Dimer, Ferritin, Fibrinogen, IL-6, and Procalcitonin levels positively (ρ= 0.569, 0.474, 0.338, 0.696, 0.605, 0.77, 0.727, and 0.585;p < 0.01 respectively), and correlated with BMI, SpO2, and lymphocyte negatively (ρ= - 0.165;p < 0.05, p= - 0.754, - 0. 548;p < 0.01 respectively). A cutoff value of 23.62 nmol/L for neopterin predicted COVID-19 with a sensitivity of 95.7% and a specificity of 95.5% (AUC: 0.986;p < 0.0001). Conclusion: Neopterin may be a useful prognostic biomarker for assessing the severity of COVID-19.

National consensus on perioperative managements for congenital heart disease in children infected with Corona Virus Disease 2019.

As a severe acute respiratory infectious disease, novel coronavirus pneumonia (COVID -19) appeared in Wuhan China in December 2019. The pathogen of COVID -19 is identified to be 2019 novel coronavirus (2019-nCoV) and children are susceptible to 2019-nCoV. Spreading mostly through respiratory tract and close contacts, the virus invades heart, lung, kidney and gastrointestinal tract. Since the clinical symptoms of viral infection are similar to those of congenital heart disease (CHD), the therapeutic complexity of CHD becomes more troublesome. COVID -19 is definitely diagnosed by nucleic acid detection and CT imaging. With the in-depth understandings and the accumulation of experiences of diagnosing and treating COVID -19 and coping with the gravest challenges of prevention and management, Section of Cardiothoracic Surgery of Branch of Pediatric Surgery of Chinese Medical Association has convened domestic experts and specialists from such an epidemic areas as Wuhan to discuss and formulate the Expert Consensus of Perioperative Management of CHD Children Infected by 2019-nCoV. COVID -19, 2019-nCoV infection, surgical options, protective measures and essential therapeutic points for COVID -19 were summarized for CHD children.Copyright © 2020 by the Chinese Medical Association.

Neuro-Behcet's disease in the setting of active COVID-19 infection

Background: Cases of SARS-COV-2 triggering or exacerbating autoimmune responses has been described in the literature, and it has shown that use of steroids in non-severe COVID-19 may potentially increase mortality. Case presentation: A 22 year-old African-American man presented with headache, weight, loss, and oral/scrotal ulcerations. Case report: Neurological exam revealed somnolence and right hemiplegia. MRI was remarkable multiple enhancing lesions involving the brainstem and left hemisphere. He was found to have a positive SARS-CoV-2 test. Work-up was unrevealing, and he was diagnosed with Neuro-Behcet's disease (NBD) based on the International Criteria for Behcet's Disease (ICBD)ackspaceD)BackspaceBackspacep. The patient was treated with systemic steroids, which resulted in both clinical and radiological improvement of his disease without exacerbation of his SAR-CoV-2 infection. Conclusion(s): This case presentation suggests that IV steroids may be safe in the treatment of NBD in adult patients presenting with SARS-CoV-2 infection.Copyright © 2021

Highly accurate multiclass classification of respiratory system diseases from chest radiography images using deep transfer learning technique

Chest X-ray radiographic (CXR) imaging aids in the early and accurate diagnosis of lung disease. The diagnosis process can be automated and accelerated by analyzing chest CXR images with artificial intelligence tools, particularly Convolutional Neural Network (CNN). Due to few medical images have been labeled, the most significant obstacle is utilizing these images accurately for diagnosing and tracking disease progression, and accordingly, the difficulty of automating the classification of these images into positive and negative cases. To address this issue, a deep CNN model was proposed to classify respiratory system diseases from X-ray images using a transfer learning technique based on the EfficientNetV2 model that acts as a backbone to enhance the efficacy and accuracy of Computer-Assisted Diagnosis (CAD) performance. Moreover, the latest data augmentation methods and fine-tuning for the last block in the convolutional base have also been carried out. In addition, Grad-CAM is used to highlight the important features and make the deep learning model more comprehensible. The proposed model is trained to work on the triple classification, COVID-19, normal, and pneumonia. It uses CXR images from three publicly accessible datasets. The following performance was achieved on the testing set: sensitivity = 98.66 %, specificity = 99.51 %, and accuracy = 99.4 %. Thereby, the proposal outperforms the four most recent classification techniques in the literature.Copyright © 2023 Elsevier Ltd

Covid-19 Diagnosis Using a Deep Learning Ensemble Model with Chest X-Ray Images

Covid-19 is a deadly virus that is rapidly spread around the world towards the end of the 2020. The consequences of this virus are quite frightening, especially when accompanied by an underlying disease. The novelty of the virus, the constant emergence of different variants and its rapid spread have a negative impact on the control and treatment process. Although the new test kits provide almost certain results, chest X-rays are extremely important to detect the progression and degree of the disease. In addition to the Covid-19 virus, pneumonia and harmless opacity of the lungs also complicate the diagnosis. Considering the negative results caused by the virus and the treatment costs, the importance of fast and accurate diagnosis is clearly seen. In this context, deep learning methods appear as an extremely popular approach. In this study, a hybrid model design with superior properties of convolutional neural networks is presented to correctly classify the Covid-19 disease. In addition, in order to contribute to the literature, a suitable dataset with balanced case numbers that can be used in all artificial intelligence classification studies is presented. With this ensemble model design, quite remarkable results are obtained for the diagnosis of three and four-class Covid-19. The proposed model can classify normal, pneumonia, and Covid-19 with 92.6% accuracy and 82.6% for normal, pneumonia, Covid-19, and lung opacity. © 2023 CRL Publishing. All rights reserved.

Hey Team: An E-Health Application for Promoting Quality of Life and Safety for Employees and Employers

The COVID(19) pandemic created a sense of urgency for the early identification of its symptoms. Besides preventing the advancement of the disease, it allows for a more effective treatment for the patient. In this context, this work describes the Hey Team collaborative application: a strategy used by some companies in Brazil, and aims to provide support with information, contact with doctors, psychological support, among other features to its employees during the pandemic. Through the application, employees report their health situation daily so that they can be monitored individually. For this strategy to work, technological, legal, ethical, and cultural challenges were overcome. Comparing Hey Team with similar approaches through common indicators, we concluded that the use of a collaborative application, based on mutual trust, managed to achieve its goals, disseminating information and helping employees to get through this difficult time. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

When Is Software a Medical Device? Understanding and Determining the “Intention” and Requirements for Software as a Medical Device in European Union Law

The role of software in society has changed drastically since the start of the twenty-first century. Software can now partially or fully facilitate diagnosis and treatment of a disease, regardless of whether it is psychological or pathological. Consequently, software plays a role comparable to medical equipment with a physical footprint. Understanding when software as a medical device must comply with applicable rules is vital for both manufacturers and regulators. We therefore examine the Medical Device Regulation to expand on the notion of intention, as this is the key basis for the classification of medical devices. Finally, we develop objective criteria that software must fulfil to be considered a medical device under European Union law.