Artificial Intelligence Based Integrated and Distributed System for Preventing Covid-19 Spread Using Deep Learning

The COVID-19 pandemic is causing a worldwide emergency in healthcare. This virus mainly spreads through droplets which emerge from a person infected with coronavirus and poses a risk to others. The risk of transmission is highest in public places. Many measures have been suggested, such as maintaining a social distance, and wearing a face mask to avoid the spread of this virus. There are three modules in this work, in the first module a mask detection system which detects whether a person wears a mask or not using deep learning techniques such as MobileNet V2 architecture along with Facenet and Masknet. Accuracy of 98.6 percentage is achieved in this module with one or two people in the frame. Barricade has been set which does not allow people who does not wear mask and allows people who wears a mask. LED light indicators and LCD displays are used as alerts, and they are programmed to provide information that is both worn and not worn, depending on the output. In the second module, a system has been designed which detects the temperature of the person and detects whose temperature is above normal body temperature and alerts accordingly. In the third module a social distancing system has been designed which detects people who does not follow social distancing protocol and alerts them using deep learning techniques. The YOLOv3 algorithm is used which creates a square box around people that displays green or red color box according to the measurement output. The transfer learning methodology is also implemented to increase the accuracy of this module. The accuracy of 98.2 percentage is achieved for social distance detection module using YOLOv3 detection model with transfer learning. All three modules are integrated so it automatically monitors human body temperature, detects mask and social distancing at the barricade system.

Serial Changes in Troponin I in COVID-19 Vaccine-Associated Myocarditis.

A 63-year-old woman presented with atypical chest pain after a third dose of the coronavirus disease 2019 (COVID-19) messenger ribonucleic acid (mRNA) vaccine. Serial cardiac troponin measurements were performed to evaluate the trajectory of her time-concentration curve which showed a typical myocarditis curve with rapid normalization. The diagnosis of myocarditis was confirmed by cardiac magnetic resonance imaging and follow-up imaging showed resolution. All symptoms resolved with weeks.

A comprehensive review of SARS-CoV-2 vaccines: Pfizer, Moderna & Johnson & Johnson.

The novel coronavirus outbreak was declared a pandemic in March 2020. We are reviewing the COVID-19 vaccines authorized for use in the United States by discussing the mechanisms of action, administration, side effects, and efficacy of vaccines developed by Pfizer, Moderna, and Johnson & Johnson. Pfizer and Moderna developed mRNA vaccines, encoding the spike protein of SARS-CoV-2, whereas Johnson & Johnson developed an adenovirus vector-based vaccine. Safety has been shown in a large cohort of participants in clinical trials as well as the general population since emergency approval of vaccine administration in the US. Clinical trial results showed the Pfizer and Moderna vaccines to be 95.0%, and the Johnson & Johnson vaccine to be 66.0% effective in protecting against moderate and symptomatic SARS-CoV-2 infection. It is important to keep medical literature updated with the ongoing trials of these vaccinations, especially as they are tested among different age groups and upon the emergence of novel variants of the SARS-CoV-2 coronavirus.

Changes in urologic operative practice at the beginning of the COVID-19 pandemic in a large, national cohort

INTRODUCTION AND OBJECTIVE: While subject to frequent speculation, the actual impact of the COVID-19 pandemic on urologic operative practice is unknown. Understanding the consequences of the pandemic will teach invaluable lessons for future preparedness and provide useful context for individual practices attempting to understand changes in operative volume. We analyzed populationlevel changes in operative practice since the onset of the COVID-19 pandemic to contextualize observations made by individual practices and optimize future responses. METHODS: We used Premier Perspectives Database to investigate changes in operative volume through March 2020. Baseline operative volume for urologic surgery was calculated using data from the preceding 12 months and compared on a total and by procedure basis. Multivariable linear regression was used to identify hospital-level predictors of change in response to the pandemic. Our primary outcome of interest was the change in operative volume in March 2020 relative to baseline. Total operative volume, and volume by procedure and procedure-based groupings were investigated. RESULTS: At baseline, we captured 23,788 urologic procedural encounters per month as compared with 19,071 during March 2020e a 19.9% decrease. Urologic oncology-related cases were relatively preserved as compared to others (average change in March 2020: =1.1% versus -32.2%). Northeastern (b=-5.66, 95% confidence interval [CI]: -10.2 to -1.18, p=.013) and Midwestern hospitals (b=-4.17, 95% CI: -7.89 to -0.45, p=.027;both with South as reference region), and those with an increasing percentage of patients insured by Medicaid (b= -.17 per percentage point, 95% CI: -.33 to -.01, p=.04) experienced a significantly larger decrease in volume. CONCLUSIONS: There was a 20% decline in urologic operative volume in March 2020, compared with baseline, that preferentially affected hospitals serving Medicaid patients, and those in the Northeast and Midwest. In the face of varying mandates on elective surgery, widespread declines in operative volume may also represent hesitancy on behalf of patients to interface with healthcare during the pandemic. Long-term follow-up will be necessary to determine COVID-19's final toll on urology.

Mechanisms of Hypoxia in COVID-19 Patients: A Pathophysiologic Reflection.

Coronavirus disease-2019 (COVID-19) causes severe hypoxemia which fulfills the criteria of acute respiratory distress syndrome (ARDS) but is not accompanied by typical features of the syndrome. The combination of factors including low P/F ratios, high A-a gradient, relatively preserved lung mechanics, and normal pulmonary pressures may imply a process occurring on the vascular side of the alveolar-capillary unit. The scant but rapidly evolving data available on the pathophysiology are seemingly conflicting, indicating the relative dominance of intrapulmonary shunting or dead space in different studies. In this hypothesis paper, we attempt to gather and explain these observations within a unified conceptual framework by invoking the relative contributions of microvascular thrombosis, along with two proposed vascular mechanisms of capillary flow redistribution and flow through intrapulmonary arteriovenous anastomoses (IPAVA). How to cite this article: Nitsure M, Sarangi B, Shankar GH, Reddy VS, Walimbe A, Sharma V, et al. Mechanisms of Hypoxia in COVID-19 Patients: A Pathophysiologic Reflection. Indian J Crit Care Med 2020;24(10):967-970.