The effectiveness of Tocilizumab in severe covid 19 pneumonia among critically ill patients

Background: Tocilizumab, an interleukin-6 (IL-6) antagonist, is being evaluated for the management of covid-19 pneumonia. The objective of this study was to assess the effectiveness of Tocilizumab in severe covid-19 pneumonia. Method(s): This was a retrospective, observational, single centre study performed in 121 patients diagnosed with severe covid-19 pneumonia. 83 patients received standard of care treatment whereas 38 patients received tocilizumab along with standard of care. Tocilizumab was administered intravenously at 8mg/kg (upto a maximum of 800mg). The second dose of Tocilizumab was given 12 to 24 hours apart. The primary outcome measure was ICU related and hospital related mortality. The secondary outcome measures were change in clinical status of patients measured by WHO (World Health Organisation) 7 category ordinary scale, changes in interleukin-6 (IL-6) levels, secondary infections and duration of ICU stay. Result(s): Tocilizumab was administered between 3-27 days after the patient reported symptoms ( a median of 10.9 days ) and between the 1st to 3rd day of ICU admission (median of 2.1 days) . In Tocilizumab group, 16(42.1%) of 38 patients died in ICU whereas in standard of care group, 27(32.53%) of 83 patients died. The difference in clinical status assessed using WHO (World Health Organisation) 7 category ordinary scale at 28 days between Tocilizumab group and standard of care group was not statistically significant (odds ratio 1.35, 95% confidence interval 0.61 to 2.97, p = 0.44). Conclusion(s): Tocilizumab plus standard care was not superior to standard care alone in reducing mortality and improving clinical outcomes at day 28.Copyright © RJPT All right reserved.

A Machine Learning-driven IoT Architecture for Predicting the Growth and Trend of Covid-19 Epidemic Outbreaks to Identify High-risk Locations

Covid-19 has had a destructive influence on global economics, social life, education, and technologies. The rise of the Covid-19 pandemic has increased the use of digital tools and technologies for epidemic control. This research uses machine learning (ML) models to identify populated areas and predict the disease's risk and impact. The proposed system requires only details about mask utilization, temperature, and distance between individuals, which helps protect the individual's privacy. The gathered data is transferred to an ML engine in the cloud to determine the risk probability of public areas concerning Covid-19. Extracted data are input for multiple ML techniques such as Random Forest (RF), Decision tree (DT), Naive Bayes classifier(NBC), Neural network(NN), and Support vector machine (SVM). Expectation maximization (EM), K-means, Density, Filtered, and Farthest first (FF) clustering algorithms are applied for clustering. Compared to other algorithms, the K-means produces better superior accuracy. The regression technique is utilized for prediction. The outcomes of several methods are compared, and the most suitable ML algorithms utilized in this study are used to identify high-risk locations. In comparison to other identical architectures, the suggested architecture retains excellent accuracies. It is observed that the time taken to build the model using locally weighted learning(LWL) was 0.02 seconds, and the NN took more time to build, which is 0.90 seconds. To test the model, an LWL algorithm took more time which is 1.73 seconds, and the NN took less time to test, which is 0.02 seconds. The NBC has a 99.38 percent accuracy, the RF classifier has a 97.33 percent accuracy, and the DT has a 94.51 percent accuracy for the same data set. These algorithms have significant possibilities for predicting the likelihood of crowd risks of Covid-19 in a public space. This approach generates automatic notifications to concerned government authorities in any aberrant detection. This study is likely to aid researchers in modeling healthcare systems and spur additional research into innovative technology. © 2023 IEEE.

The Effectiveness of Bevacizumab in COVID-19 Pneumonia Among Critically Ill Patients

Background:Bevacizumab, an antiangiogenic drug, is being evaluated for the management of novel coronavirus disease (COVID-19) pneumonia among critically ill patients. The objective of this study was to assess the effectiveness of bevacizumab in severe COVID-19 pneumonia. Methods:This was a retrospective, observational study performed in 111 patients diagnosed with COVID-19 pneumonia. Bevacizumab was administered intravenously at 7.5 mg/kg along with standard care in a non-randomly selected subset of patients (n = 29) with evidence of acute respiratory distress syndrome (ARDS) within 72 hours of worsening of oxygenation. The primary outcome measure was intensive care unit (ICU)-related mortality. Results:Bevacizumab was administered for a median of 9.4 (4-24) days from the onset of symptoms and 2.2 (1-3) days from the day of ICU admission. Bevacizumab-treated patients showed a statistically significant improvement in PF ratio and reduction in radiological severity score. In the bevacizumab group, 13 (44.8%) of 29 patients died in ICU, and in the standard-of-care group, 37 (45.1%) of 82 patients died. The difference in clinical status assessed using the World Health Organization 7-category Ordinary Scale at 28 days between the bevacizumab group and the standard-of-care group was not statistically significant (odds ratio 1.02, 95% confidence interval 0.44-2.4, P = .94). Conclusion:Bevacizumab plus standard care was not superior to standard care alone in reducing mortality and improving clinical outcomes at day 28.

Trajectory Tracking Analysis of Fractional-Order Nonlinear PID Controller for Single Link Robotic Manipulator System

Increasing demand for automation is being observed especially during the recent scenarios like the Covid-19 pandemic, wherein direct contact of the healthcare workers with the patients can be life-threatening. The use of robotic manipulators facilitates in minimizing such risky interactions and thereby providing a safe environment. In this research work, a single link robotic manipulator (SLRM) system is taken, which is a nonlinear multi–input–multi–output system. In order to address the limitations like heavy object movements, uncontrolled oscillations in positional movement, and improper link variations, an adaptive fractional-order nonlinear proportional, integral, and derivative (FONPID) controller has been suggested. This aids in the effective trajectory tracking of the performance of the SLRM system under step input response. Further, by tuning the controller gains using genetic algorithm optimization (GA) based on the minimum objective function (JIAE ) of the integral of absolute error (IAE) index, the suggested controller has been made more robust for trajectory tracking performance. Finally, the comparative analysis of the simulation results of proportional & integral (PI), proportional, integral, & derivative (PID), fractional-order proportional, integral, & derivative (FOPID), and the suggested FONPID controllers validated that the FONPID controller has performed better in terms of minimum JIAE and lower oscillation amplitude in trajectory tracking of positional movement of SLRM system. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

A Novel Approach for Predicting Covid 19 Recovered Cases using Nourishment by Comparing KNN over SVM

To predict the accuracy value of COVID19 recovered number of patients using Nourishment. Material and Methods: For forecasting accuracy percentage of COVID19 recovered patient health diet, Novel K Nearest Neighbour with test size (N=10) and Support Vector Machine with test size (N=10) were iterated 20 times to COVID19 recovered number of patients with g power as 80 %, threshold 0.014 and confidence interval as 95%. Sigmoid function is used in K Nearest Neighbour prediction to probability to help enhance accuracy. Results: In comparison to Support Vector Machine 66% percent Accuracy, Novel K Nearest Neighbour produced substantial results with 94 % Accuracy. Support Vector Machine and K Nearest Neighbour statistical significance is p=1.000(p<0.05) Independent sample T-test value states that the results in the study are significant. Conclusion: KNN is a straightforward and efficient algorithm for quickly building Models of machine learning. KNN predicting COVID19 Health Diet % with more accuracy. © 2022 IEEE.

Outcomes Comparison of Commonly Used Heart Transplant Preservation Solutions During the Covid-19 Pandemic

Orthotopic heart transplantation (OHT) is a necessity for patients with end-stage heart disease. Despite advancements made in cardiac allograft preservation, there remains ambiguity as to which heart preservation solution provides improved outcomes - especially during a national healthcare flux. Many papers compare University of Wisconsin (UW) and Celsior (CS), the two most commonly used solutions in the USA, in abdominal organ transplants but few describe relative outcomes related to the adult heart. Here, we compare the two commonly used preservation solutions and hypothesize that UW shows superior postoperative patient outcomes. The United Network for Organ Sharing (UNOS) database was retrospectively reviewed from 5/31/2020 to 5/31/2021 for adult OHT recipients. Primary stratification was by solution type with evaluation of only UW and CS preservation solutions. Primary endpoints were survival and length of stay. Secondary endpoints were acute graft rejection, intubation status, and use of ECMO, IABP, and inotropes. After exclusion criteria, a total of 2,388 adult OHT recipients were identified. 1,941 (81.3%) transplants utilized UW. Analysis of Cox regression models for survival revealed no significant difference between both solutions. Fisher's exact test showed decreased rates of inotrope use (p = 0.008) and acute rejection episodes (p = 0.002) for UW solution (Fig. 1). There was no statistical significance between UW and CS with length of stay, intubation status, and use of ECMO, IABP at 72-hrs post-transplant (Fig. 1). Evaluation of the two most commonly used heart preservation solutions nationwide reveals that CS is non-inferior to UW with regards to patient survival, length of stay, and use of ECMO and IABP. However, UW shows significantly reduced acute graft rejection and use of inotropes. [ABSTRACT FROM AUTHOR] Copyright of Journal of Heart & Lung Transplantation is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Teledermatology and COVID-19 in a resource-limited country such as Nepal

Background: Teledermatology has become a popular alternative tool for providing dermatology services during the COVID-19 pandemic worldwide. Despite being a rising health care modality, it helped to deliver uninterrupted services. The study aimed to determine the implementation, utilization, and acceptance of teledermatology services during the pandemic. Objectives: The aim was to assess the satisfaction of patients utilizing teledermatology services and to obtain their clinical and epidemiological data. Methods: This was a retrospective, observational, single-center study on patients using teledermatology services. Demographic data was analyzed and a questionnaire survey was conducted through phone calls regarding their experience of the service. Results: The mean age of the patients was 33.48 +or- 17.89 years. Out of 122 teleconsultations, 89 patients could be contacted again for feedback, among which 81 (91%) found the service easy to use, 75 (84.3%) were able to express their problems similarly to visits in person, 49 (55.05%) regarded teleconsultation as the same as an in-person visit, 80 (89.9%) were satisfied, and 85 (95.5%) agreed to use the service in the future. Superficial fungal infection was the most common diagnosis (24.6%). Newly registered patients were more satisfied in comparison to follow-up patients (96.36% of new cases vs. 79.41% of follow-up cases, p = 0.01). Conclusion: Teledermatology was well accepted by the patients in the current scenario. Telehealth services have a promising role in the future in fulfilling public health demands.

Water purification techniques for the developing world

Water, the most basic requirement for life, is the fundamental right of every individual. Yet, it is an extremely rare commodity in many parts of the world, especially in developing countries. Moreover, when water is available in such regions, it is usually contaminated with several impurities that can endanger lives when consumed untreated. Therefore sustainable, efficient, low-priced, and easily deployable water treatment methods are crucial in developing nations. The ongoing Covid-19 pandemic has further aggravated the situation as there is an increased need for water to be used for frequent hand wash and basic hygiene processes to prevent the spread of infection. Hence, conservation of water by way of rainwater harvesting is the need of the hour. Additionally, harvested rainwater must be treated to remove contaminants such as viruses and bacteria if it is to be used for potable purposes. This chapter discusses, compares, and suggests possible water treatment methods for both surface/ground water and harvested rainwater for developing nations. The impact of the Covid-19 pandemic on the water sector is highlighted and some recommendations for future research initiatives in water treatment especially for the developing population are also indicated. © 2022 Elsevier Inc. All rights reserved.

Apprehensions and Optimism among Dental Professionals during the COVID-19 Pandemic-A Nationwide Cross-Sectional Evaluation.

Globally, the pandemic of the coronavirus disease, which started in Wuhan, China, has become a major issue for public health. The COVID-19 epidemic notably causes health professionals to experience significantly more emotional stress than the general populace. The present study proposes to investigate the fear aspect in dentists in the initiation of clinical practice during these times. An online cross-sectional study was conducted among dental practitioners based on a pre-validated questionnaire. The data were expressed as frequency and percentage analyzed using the chi-square test using SPSS version 25. The data was obtained from 271 participants, where clinical practice after the first wave was mostly by freelancers (p-value = 0.01); most of whom were married (p-value = 0.065); 19.1% attached to institutes did not have changes in earnings; 28.1% of private practitioners had less than 10% reduction in cases. A total of 62% of private practitioners are concerned about the vaccine's preventative effects (p-value = 0.026), and 57% of private practitioners worry about being sued for the delay in treatment (p-value = 0.036). Only 33.1% of employees in institutions worry that becoming sick could endanger their family. As dentists continue to work their way through this pandemic, these pressures only occasionally have an impact on them. According to the researchers, this is the first study that has captured the anxiety and apprehensions that dental practitioners experienced during the height of the COVID-19 outbreak in India in April 2021. The study's findings demonstrate that the study population was generally upbeat and confident that they could quickly overcome their fear.

EVALUATING LEARNING EXPERIENCE AND EMOTIONAL TRIGGERS OF VIRTUAL LEARNING ENVIRONMENTS (VLES) USING PSYCHOGALVANIC REFLEXES AND BEHAVIOURAL ANALYSIS

Virtual Environments (VEs) are on the rise as an instrument in various sectors involving emotional states and educational research. Studies till date have tried to explore the effectiveness of VR in a variety of emotional health interventions, treatment of learning phobias, and providing virtual support to students worldwide. Research has demonstrated that VR immersive environments and VR experiences create a significant impact on the users' psyche. A learning experience is related to the emotional state of the person (O'Regan, K. (2003). Therefore, it would be interesting to study the influence of VR experience on the emotional states of the learners. Students around the globe were already struggling with emotional crises even before the pre-covid situation as reported by multiple agencies but now the situation has turned more grievous. Here comes the need for magnified learning experiences in virtual learning environments (VLEs). This study investigates the impact of two different VR-3D learning environments. It draws a comparison between students' emotional states, VR experience, and VR design elements using neurophysiological tools like Galvanic Skin Response (GSR) and self-reporting questionnaires. In the experiment, participants were asked to go through two different VR learning simulations and their physiological responses were recorded for analysis. The two simulations were differentiated based on space and interaction design elements. The study suggests that well-designed Virtual 3D-Environments in an educational setup can help students in reducing stress levels and ways how we can elicit positive emotions and facilitate a better learning experience. © Proceedings of the 24th International Conference on Engineering and Product Design Education: Disrupt, Innovate, Regenerate and Transform, E and PDE 2022. All rights reserved.

SOCIAL MEDIA: ENABLING INCONSPICUOUS BLENDED LEARNING IN DESIGN EDUCATION IN INDIA

Social media has penetrated all strata of society and educational levels and spheres, making it an important channel of communication and knowledge transfer. Even as the Covid-19 pandemic changed the education scenario across the globe, with the medium of instruction majorly shifting to online, things are slowly returning to 'normalcy'. Albeit the use of social media as a conduit for instruction, feedback and learning, which increased during the lockdowns, continues to grow and evolve. This study aims to trace and understand the relationships between online social networking, social connectedness and learning in design education, in online, offline and blended set-ups. This paper reports findings from quantitative studies, done across various design schools in India. Participants responded anonymously to the online survey using the Google Forms platform. This study assesses the amount of course material shared, discussed, and engaged with on various social media. Respondents also marked the amount of connectedness they perceived with peers through social media and whether it impacted their class interaction with each other. It was found that students used various platforms for online communication and exchange of information, though their feedback on online interactions revealed deeper insights into factors that affect their overall experience of design education and learning. Further analysis of data found significant correlation between felt connectedness and interaction on social media with peers and design creativity and learning. © Proceedings of the 24th International Conference on Engineering and Product Design Education: Disrupt, Innovate, Regenerate and Transform, E and PDE 2022. All rights reserved.

SARS-CoV-2 Omicron (B.1.1.529) variant: structural features, biological characteristics, impact on scientifiic research, general precautions and protective procedures. A systematic review

The SARS-CoV-2 mutations that have occurred have alarmed the entire medical community. Thus, global concerns have been expressed regarding the transmission, pathogenicity and immune evasion of the Omicron strain, which shares mutations with the variants of concern Alpha, Beta, and Gamma strains. Still, Omicron transmission has crossed numerous borders worldwide compared to other types of SARS-CoV-2. The number of confirmed cases has increased and is reappearing in India. Given the worrisome situation created by the Omicron outbreak, scientists and postgraduates have had to make decisions about current research programs at institutions around the globe. The Omicron variants under development have significantly heightened worldwide pandemic concerns. In this review, the authors will outline the molecular features and efficacy of vaccination, highlight possible omicron impacts on scientific research, and provide precautions, procedural guidelines for organizing scientific meetings during a pandemic.

Overconfidence bias in the Indian stock market in diverse market situations: an empirical study

Market situations affect investors’ sentiments. Sudden and sharp changes in the market may make investors adjust their beliefs and change their viewpoints. To quote, such sharp changes include the stock market crash of 2008 and the COVID-19 pandemic, which significantly impacted investors' emotions. In this direction, this study attempts to find investors’ overconfidence bias in different market situations, i.e., precrash period (2006–2008), crash period (2008–2010), and post-crash period (2010–2015, 2015–2020, 2020–2021). We have obtained secondary data for this study from the BSE 100 index (as a proxy of the Indian stock market). Econometric techniques used for data analysis include Vector Auto Regression (VAR), Granger causality VAR/Block Exogeneity Wald Test, and Impulse Response Function (IRF). The study finds that the investors were overconfident during pre-crash periods, i.e., before the global market crash of 2008 and the duration between 2015 and March 2020. In postcrash periods, i.e., during 2008–2010, 2010–2015, and 2020–2021, investors were not overconfident.

Covid Explorer- A Web Based Covid Analysis and Tracking

In this paper, Covid Explorer model's aim is to provide information on Covid 19 like-how you can prevent the Corona Virus, symptoms of Corona Virus or how to book slots for the Corona Virus. You can add the current data related to Covid 19 like a graph indicated the increase or decrease of death rate from this virus, a report is given to show the death rate, the number of vaccines doses given on a particular day, state wise cases are also shown through Application Programming Interface (API) in Covid Explorer model. The model is analyzing and tracking Corona Virus. As per the data analysis this pandemic creates mental health issues but if a model gave up-to date data of the current scenario then stress can be overcome and society can fight against this pandemic. © 2022 IEEE.

A Review on Prophylactic Regimen by Evaluation of Asymptomatic SARS CoV-II Carriers

High erythrocyte sedimentation rate and D-dimer were also observed.15 The main pathogenesis of COVID-19 infection as a respiratory system targeting virus was severe pneumonia, RNA anaemia, combined with the incidence of ground-glass opacities, and acute cardiac injury. The comparable viral load in a group of asymptomatic carriers of COVID-19 was higher than that of the symptomatic carriers and increasing level of white blood cell count (12.4×109/L), neutrophil count (7.82×109/L), C-reactive protein level (189.2mg/L), low lymphocyte count (0.84×109/L) and platelet count (88×109/L) was found different than the normal range in asymptomatic patients.22 2.1 Clinical Evaluation of Asymptomatic Carriers: Many asymptomatic persons were actually a source of SARS-CoV-2 infection but were considered healthy before they underwent screening. CRP levels, LDH levels, and white blood cell counts were elevated occurred in 10, 13 and 1 patient, respectively.24 According to the study, asymptomatic infection was seldom seen in young people;the proportion with severe COVID-19 was low, and the proportion with ordinary COVID-19 was high. 2.3 Evaluation of Asymptomatic and Symptomatic Carriers: Table-1: Description of general characteristics responsible for evaluation of asymptomatic carriers of Covid-19. General characteristics Asymptomatic Carriers Symptomatic Carriers Normal range White blood cell count (× 10⁹ cells per L) 5.65 9.43 4.00–10.00 Neutrophil count (× 10⁹ cells per L) 3.62 8.21 1.80–6.30 Lymphocyte count (× 10⁹ cells per L) 1.55 0.69 1.10–3.20 C-reactive protein (mg/L) 0.69 202.03 0.0–5.0 3 Prophylactic Regimens for Prevention from Sars Cov-II Virus: This review aims to interrogate the current evidence base, and present the potential immune-mediating, antioxidant, and antimicrobial roles of vitamins A to E in the context of respiratory disease, and to extrapolate this evidence to evaluate the potential roles in the fight against COVID-19.

Modeling of COVID-19 Outbreak in Reference to Physical Parameters

The spread of coronavirus disease 2019 (COVID-19) in various countries varies in different manners, depending on the demographic and climatic conditions. This needs expediting better strategies to combat the novel coronavirus and also the emergence of new viral strains in the future. Our in-depth analysis suggests the spread of COVID-19 cases worldwide, the timeline of spread among most affected countries as of September 3, 2020. Evaluation of the climatic conditions in 2-week interval is carried out. The study recorded most of the countries getting affected by COVID-19 belong to the range of 25-35°C maximum temperature, 20-30°C minimum temperature, and 60%-80% relative humidity. To get a more generalized view on the spread, the study explored the temperature distribution of affected countries and chronicled in both minimum and maximum temperatures so that the number of COVID-19 cases mostly follows a lognormal distribution. In different ranges of relative humidity, not a single distribution is obtained to explain the spread of COVID-19 cases worldwide. A comparison between theoretic and descriptive parameters is also done to support the spread of COVID-19. © 2022 Elsevier Inc. All rights reserved.