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.

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.

A critical review of literature to reveal Covid-19 effect on mental health

Over 26,13,73683 cases and 52,12,961 verified fatalities have been documented because of the Corona pandemic so far. As a result of such extensive epidemics, mental health issues are more likely to occur. Keeping this in mind, the medical databases were used to locate relevant research on the Corona epidemic and mental health. Classification and summarization of previously published articles were carried out in accordance with the articles' overarching topics. In the early stages of the Corona pandemic, symptoms of anxiety, sadness, and self-reported stress (ranging from 16–28 percent) are frequent and may be linked to disrupted sleep. Several factors, both personal and institutional, influence this risk. In designing services for these groups, consideration must be given to both the requirements of the individuals affected and the appropriate preventative recommendations. Only a handful of the impacted nations have been documented in the literature, which may not accurately reflect the experiences of people in other areas of the world. As a result of the Corona epidemic, many people have developed subsyndromal mental health issues. For disadvantaged communities in other nations, there is a need for more representative studies. However, the current study explores the four main studies undertaken in China, which were chosen out of a total of 28 articles and after careful selection were delineated for study, the methodology gives the selection criterion in detail. © MEDIC SCIENTIFIC, All rights reserved.

Preliminary detection of covid-19 using deep learning and machine learning techniques on radiological data

Covid-19 is a dangerous pandemic in the year 2020." Covid-19 positive" is the most negative word heard this year, which caused terror worldwide. As it is a contagious pandemic, early detection of this pandemic will minimize its threat. The primary issue is its detection. To detect Covid-19 through a blood test, a person must wait for an extended period to get the results. Using our model, one can primarily detect Covid-19 immediately using Deep Learning algorithm CNN and Machine Learning algorithm Logistic Regression. Input to these techniques is radiological data like CT-Scan and X-ray images. Covid-19 positive cases will be easily detected faster with the help of this model. © 2021, Engg Journals Publications. All rights reserved.