ABSTRACT
In severe Covid-19 pneumonia, acute respiratory distress syndrome (ARDS) associated with cytokine storm is the leading cause of death. Tocilizumab was approved for chimeric antigen receptor T-cell therapy induced cytokine release syndrome and it may provide clinical benefit in these severe covid-19 pneumonia. In this retrospective cohort study, we evaluated patients with severe COVID-19 pneumonia admitted between May 2021 and June, 2021. Patients who were received tocilizumab during treatment, were enrolled for the study. Systemic steroids, hydroxychloroquine, and azithromycin were concomitantly used for the patients. The outcome was measured as an improvement in peripheral oxygen saturation by change in mode of oxygen therapy and improvement in laboratory parameters after tocilizumab administration. Out of 23 treated patients (18 Male, 5 Females), 19 patients received a single dose of tocilizumab and another four patients received two doses of it. Of these 23 patients, 3/3 with NRBM (non-rebreather mask) showed improvement and shifted to nasal cannula for oxygenation. 11/12 patients with NIV(non-invasive) showed improvement. 5/8 patients with invasive ventilation showed gradual improvement and shifted to NIV. A total of 4/23 (17%) patients didn’t show any improvement and died. Inflammatory markers like CRP, percentage of lymphocytes, and ferritin also showed significant improvement after administration of tocilizumab. Our study showed that in patients with severe COVID-19, tocilizumab was associated with significant improvement in clinical and laboratory parameters. These findings require further validation from ongoing clinical trials of Tocilizumab in COVID-19 patients.
ABSTRACT
Most of the hospitals store their patient's data locally and some even do not have any backup storage. This poses a real threat of data loss or data corruption. Although many hospitals are migrating to cloud storage, the clouds have their own threat vectors. Recently, various health care providers were hit by ransomware and Distributed Denial of Service attacks during the COVID-19 outbreak. Due to these attacks, many emergency services were halted, affecting hundreds of thousands without any healthcare. Another problem with these traditional database practices is that they often misplace or mix the patient's data, which, needless to say, have severe complications. Many researchers are working on IPFS and Blockchain technology to improve the storage of medical records. This article presents a detailed study of the IPFS and Blockchain based healthcare secure storage solutions. It analyzes the existing solutions and their architecture, which will further facilitate the future research and development of emerging IPFS and Blockchain technologies.
ABSTRACT
To control the spread of the coronavirus (COVID-19) pandemic, the Government of India imposed various phases of lockdown starting from the third week of March 2020. Improvement in city air quality has emerged as a benefit of this lockdown in India. The objective of this paper is to quantify the health benefits due to this lockdown. PM2.5 concentrations in nonattainment cities (NACs) in Uttar Pradesh and the Delhi-National Capital Region (NCR) in North India were studied. Data from prelockdown and the various lockdown phases were compared, with 2019 as a benchmark. Compared with those in 2019, the PM2.5 concentrations during lockdown Phase 1 were approximately 44.6% lower for cities in Uttar Pradesh and approximately 58.5% lower for the Delhi-NCR. The health impacts of particle inhalation were quantified using the multiple-path particle dosimetry and AirQ+ models, which revealed that the most considerable improvement was during lockdown Phase 1. Among the prelockdown and lockdown phases, Phase 1 exhibited the minimum PM2.5 concentration and thus the greatest health benefits. For the selected cities, the concentration of particle deposition in the tracheobronchial region of human lungs showed its maximum reduction during lockdown Phase 1(30.14%). Furthermore, the results highlighted a decrease of 29.85 deaths per 100,000 persons during lockdown Phase 1, primarily due to the reduction in PM2.5 concentrations. This quantification of the health benefits due to a decrease in PM2.5 may help policymakers implement suitable control measures, especially for NACs, where the respirable particulate matter concentrations remain very high. © 2021, AAGR Aerosol and Air Quality Research. All rights reserved.
ABSTRACT
In December 2019, a novel coronavirus, called COVID-19 was discovered in the city of Wuhan China, which spread to various cities as well as other countries. At present novel coronavirus has become the most important health hazard, causing severe issues about a concern to the human being and has become a pandemic. Due to the prone of this deadly virus, uncertainty is significantly the facility for a health condition. There are solutions to handle insecurity about health from coronavirus for assessing the condition through FIS (Fuzzy Inference System). Therefore, for this particular reason we study and develop the fuzzy system to help assess the safety of health-related issues of the patient's condition according to the changes of environment. The FIS is permitted to assess the patient's history like temperature of the body, travel history, disinfection frequency, breathing problem, suffering cough and cold and ventilation rate. A fuzzy system consists of several steps like fuzzification, fuzzy database rule and also defuzzification. Furthermore, a study of FIS identifies the risk of health status according to the patient's condition. In this paper, we proposed a fuzzy rule system which is implemented with MATLAB fuzzy tools for simulation to assess the health conditions of the patient and prevention from COVID-19 disease. © 2021 IEEE.