ABSTRACT
Background: SARS-CoV-2 virus infection was detected and discovered in Wuhan, China, in December 2019, and it was declared a pandemic by WHO in March 2020. Since then a lot of changes were noticed in surgical practice. Various recommendations were released by eminent surgical associations all over the world. This study was designed to study and analyze the findings and experience after resuming elective minimal invasive surgery during the pandemic. Materials and methods: This observational study was conducted at St Joseph’s Hospital, Ghaziabad, from May 2020 to May 2021. Various preoperative and postoperative findings were noticed and analyzed. The presence of SARS-CoV-2 virus was also analyzed in endotracheal aspirate and surgical smoke. Observation and results: A total of 287 cases underwent surgery. Most commonly performed surgery was laparoscopic cholecystectomy. The positivity rate for SARS-CoV-2 during preoperative work-up was 2.87%. Slightly more than 5% of cases in postoperative period had COVID-19-like symptoms. None of those patients were found positive on RT-PCR, and X-ray/CT findings were also suggestive of early postoperative changes only. Presence of SARS-CoV-2 virus was not detected in either endotracheal aspirate or surgical smoke. Neither surgery team nor OT staff had infection during this period. There was no mortality, and only 1 patient was found to be infected 2 weeks after discharge. Conclusion: Minimal invasive surgery for elective cases can be safely performed by taking precautions like PPE and smoke evacuation system during the COVID-19 pandemic. There is no evidence of transmission of infection through endotracheal aspirate or surgical smoke.
ABSTRACT
The cutting-edge age of innovation has developed at high speed to make our lives quiet. The progression in security administrations of the advanced world has prompted the working of frameworks and gadgets all the more effectively and precisely by giving the greatest to most extreme wellbeing and security. The significant method of getting our frameworks and gadgets is passwords or passphrases however this has a few bugs which can undoubtedly be broken or hacked, this prompted the appropriation of further developed procedures, i.e., biometric finger impression scanner, this gives sufficient measure of safety to frameworks like opening the telephone and section in schools or workplaces. In any case, examining the current situation of this gigantic pandemic Covid-19, some control is needed for the protection of individuals which advances touchless registration into workplaces, schools, and universities. This examination paper denotes the use of Computer Vision innovation by carrying out python programming language and its libraries. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The world's worst outbreak, the second COVID-19 wave, not only unleashed unprecedented devastation of human life, but also made an impact of lockdown in the Indian capital, New Delhi, in particulate matter (PM: PM2.5 and PM10) virtually ineffective during April to May 2021. The air quality remained not only unabated but also was marred by some unusual extreme pollution events. SAFAR-framework model simulations with different sensitivity experiments were conducted using the newly developed lockdown emission inventory to understand various processes responsible for these anomalies in PM. Model results well captured the magnitude and variations of the observed PM before and after the lockdown but significantly underestimated their levels in the initial period of lockdown followed by the first high pollution event when the mortality counts were at their peak (â¼400 deaths/day). It is believed that an unaccounted emission source was playing a leading role after balancing off the impact of curtailed lockdown emissions. The model suggests that the unprecedented surge in PM10 (690⯵g/m3) on May 23, 2021, though Delhi was still under lockdown, was associated with large-scale dust transport originating from the north west part of India combined with the thunderstorm. The rainfall and local dust lifting played decisive roles in other unusual events. Obtained results and the proposed interpretation are likely to enhance our understanding and envisaged to help policymakers to frame suitable strategies in such kinds of emergencies in the future.
Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , COVID-19/epidemiology , Cities , Communicable Disease Control , Dust , Environmental Monitoring , Humans , Particulate Matter/analysis , SARS-CoV-2ABSTRACT
The basic concept for use of convalescent plasma in COVID-19 is as a delivery system for viral neutralizing antibodies, that is to confer passive immunity. Given the fact that they do not have reliable targeted drugs or a vaccine yet, the option of convalescent plasma seems reasonable to boost the immune system of infected patients or susceptible population immediately. This is not a new concept, rather this has been utilized for over 100 years, even predating the discovery of antibiotics. Once it is confirmed that the proposed donor is no longer contagious, the next step would be to see if the donor has adequate levels of antibodies to donate. This can be done by measuring SARS-CoV-2 antibody levels to ensure adequate titers in the donor's circulation. The FDA recommends a SARS-CoV-2 neutralising antibody titer of at least 1:160 as an inclusion criterion for donor selection. If a compatible unit is not available, the FDA suggests that a titer of 1:80 may be considered acceptable. While waiting for an effective vaccine and / or antiviral agent against COVID-19, experimental therapies are currently being tested in clinical trials. So far, plasma therapy has provided encouraging results with no serious events. It is expected that an increasing use of convalescent plasma for the treatment of seriously ill patients and possibly earlier in the course of the disease and/or for prophylaxis in the coming months. The American Red Cross, the United States government, researchers at the Mayo Clinic, and many others across the country are now working hard to identify suitable donors and establish tests to confirm neutralizing antibodies in such a way that they timely. Since the antibody test is validated, it should help support the most effective use of convalescent plasma. Additionally, efforts are being made to continue the production of a COVID-19 immunoglobulin that could provide a more reliable, effective, and more available plasma-based therapy for this formidable virus.
ABSTRACT
COVID-19 is a pandemic outbreak that has slaughtered millions worldwide and infected millions more. RT-PCR examination, CT (Computed Tomography) scans, and Chest X-ray (CXR) images are used to diagnose it. Most medical centers lack CT scanners and RT-PCR (Reverse Transcription Polymerase Chain Reaction) testing, as a result, in many circumstances, X-rays of the chest have become the most time and cost-effective technique for supporting clinicians in decision-making. Any technological process that aids in the fast diagnosis of COVID-19 infection can be highly beneficial to health care providers. A diagnosis recommender device that will aid the doctor in examining the patient's lung scans would reduce the doctor's medical workload. When compared to machine learning techniques, deep learning approaches have shown unbeatable results in categorizing the realm of medical imaging. However, currently available databases do not create such schemes because they are extremely diverse and skewed against extreme cases. This research paper used a VGG-16 architecture which was already pre-trained on the ImageNet dataset to predict COVID-19, non COVID-19 and pneumonia patients from chest X-ray images. The employed VGG-16 architecture, is one of the CNN architectures, used for image classification. Classical data augmentation techniques were used to increase the size of dataset. VGG-16 model has predicted COVID-19, non COVID-19 and Pneumonia patients from chest X-ray images with a 92.5% accuracy using the transfer learning. © 2021 IEEE.
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Background: Limited data is available about knowledge, anxiety and use of HCQ prophylaxis among health care personnels in India related to COVID-19 pandemic Methods: A cross-sectional study was done in May 2020, using a validated questionnaire comprised of 28 questions at a tertairy care health-care center in India Results: A total 957 respondents were included (10.2% nurses, 45.2% medical students, 24.3% paramedical students, 11.7% residents and 8.6% faculty). Overall knowledge score was 9.3/15;highest for preventive practices (4/5), followed by clinical knowledge (2.7/5) and use of Personal Protective Equipment (2.6/5). Overall score was higher in faculty (10.8), least in nurses (8.5) & paramedical students (8.4) [p <.001]. Less than 50% had knowledge about correct sequence of doffing PPE and use of N95 mask. Using GAD-7 scale, 21.8% experienced anxiety, highest among nurses (38%), followed by paramedical students (29.3%), residents (21.3%), faculty (18.3%), medical students (14.8%);and anxiety was higher when knowledge score was low (27.6% vs 14.7%);both factor significant on multivariate analysis (p <.001). Most common reasons for anxiety was no definite cure, fear of getting infection & lot of misinformation in media. HCQ prophylaxis was taken by 18.1% respondents which was significantly higher among older age group(p<.001), faculty(p<.001) and having family member <5/>65 years age at home on multivariate analysis (p<.001) Conclusions: The lower COVID-19 knowledge scores were significantly associated with a higher likelihood of anxiety and potentially dangerous practices towards COVID-19 epidemic.