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Arab Gulf Journal of Scientific Research ; 39(Special Issue (2):48-59, 2021.
Article in English | GIM | ID: covidwho-1929360

ABSTRACT

Background: Coronavirus disease 2019 (COVID-19) associated inflammatory cytokine storm that worsens COVID-19, relies heavily on the inflammatory response. IL-6, a TH1 cytokine, PCT and CRP have been linked to serious illness and a higher mortality rate. We further tried to evaluate the role of these indicators and their association with clinical severity in COVID-19 patients. Material and Methods: Eighty-three consecutive patients with age 18 years with RT-PCR test positive for SARS-CoV-2 were included in the study. Demographic characteristics (age and sex), underlying co-morbidities, symptoms, physical findings, and laboratory tests of the patients were recorded. All patients were categorized as having mild, moderate, and severe COVID-19 disease, according to the Indian Council of Medical Research (ICMR). The levels of IL-6 and PCT were estimated by electrochemiluminescence immunoassay (ECLIA) using Cobas-e411 Immunoassay System, and Quantitative CRP was done by Unicorn-230 automated biochemistry analyzer to find out their correlation with disease severity and outcome. Multiple Regression was performed to find out factors associated with the adverse outcome of the disease. Result: Mean age of patients was 51 years. IL-6, CRP, and PCT levels increased in 73%, 68.0%, and 8.2% patients on admission, respectively. The most common co-morbidity associated with the disease was hypertension (25%), followed by diabetes (24%) and respiratory disease (15%). Increased IL-6, CRP, and PCT levels were found in 77 percent, 79 percent, and 20 percent of patients, respectively. We found that IL-6 (P0.05), CRP (P0.05), and PCT (P0.05) were significantly raised in COVID-19 patients with increasing severity of the disease. The Area under the receiver operating characteristic (AUROC) of these parameters ranged between 0.65 and 0.8 (IL-6, 0.828;CRP, 0.809;and PCT, 0.658), indicating a reliable biomarker to assess clinical severity.

2.
Natural Volatiles & Essential Oils ; 8(5):4517-4521, 2021.
Article in English | CAB Abstracts | ID: covidwho-1904995

ABSTRACT

Corona Virus or COVID-19 Disease is an infectious disease caused by newly discovered coronavirus. It caused a lot of damage to the Mankind around the world. It is also parallelly called as SARS-CoV-2 and was first reported in Wuhan City, China by the officials in December 2019. On 30 January 2020, the Director-General Tedros Adhanom of World Health Organization declared the outbreak of the coronavirus. Currently, many Pharma Companies aiming to develop vaccine to the COVID-19. To avoid being exposed to coronavirus, we must cover our nose and mouth with a mask, wash our hands frequently and avoid direct contact with the people who are already affected. This Paper aims to detect whether a person who is facing the camera is wearing a face mask or not in real time. Deep Learning is the best Technology present in the current Industry for its effectiveness in reorganization and classification using image processing. It proposes a retina face mask which a one stage detector and with further developments and modifications, this model can be used in Airports, Railway Stations and other highly crowed public areas.

3.
Arab Gulf Journal of Scientific Research ; 39(1):19-30, 2021.
Article in English | Scopus | ID: covidwho-1824568

ABSTRACT

Purpose: COVID-19, a pandemic declared on March 11th, 2020, makes it crucial for the whole world to control and ensure safety measures to control such infections in the future. Fear, worry, and panic remain widespread, especially among healthcare workers. We aimed to compare the knowledge, attitude, anxiety, and behaviours of medical and non-medical students towards vaccination against COVID-19. Material and Methods: We conducted a cross-sectional study for one month on the MBBS/BDS and undergraduate nonmedical students through an online questionnaire which consisted of a multiple choice KAP questionnaire consisting of four sections (i.e., socio-demographic details, knowledge, attitudes, and behavior). Multiple linear regression was performed to determine the variables predicting knowledge and attitudes towards COVID-19 vaccination. Results: Vaccine hesitancy was detected in 17% of Undergraduate Medical Students, while the same was noted in 45% of non-medical students. 48.7% of medical students knew about different vaccines available in India for COVID-19 viz a viz the same in non-medical students was 49.5%. The majority of the students (35.8% medical and 48.6% non-medical) considered Covishield the best currently available vaccine in India. The majority of the students (Medical 86.5% and non-medical 75.2%) thought that the COVID-19 vaccine could reduce the spread of the disease in the community. In the multiple regression model, better socioeconomic status, holding nuclear families, and having a history of essential vaccinations uptake were linked with knowledge, while attitudes were substantially associated with being female and having previous history of vital vaccines uptake.Conclusion: The results showed that medical students had sufficient knowledge, an optimistic attitude, and moderate levels of concern towards COVID-19. Vaccine hesitancy was much less among medical when compared to non¬medical students. Expanding knowledge and regulatory oversight of vaccine research and the public release of safety data may lessen vaccine reluctance among students. © 2021, Arabian Gulf University. All rights reserved.

4.
Indian Journal of Medical Microbiology ; 39:S75, 2021.
Article in English | EMBASE | ID: covidwho-1734522

ABSTRACT

Background:This ongoing coronavirus disease 2019 (Covid-19) pandemic is a great challenge for our health-care systems and their infrastructure. Diagnostic confirmation of infected individuals based on RT-PCR is important for the contain- ment of viral spread because despite high viral loads, infection can be asymptomatic. To come up with the limited sup- plies in low socio economic countries like ours, pooling of specimens was proposed as a method to screen large number of patients. To analyse the effect of pooling of samples on the sensitivity of RT-PCR, we compared Cycle threshold (Ct) values of pools with those of the deconvulated (individual) samples. Methods:From March 2020 to October 2020, we performed Covid-19 testing by RT-PCR from areas with varying preva- lence of population referred to VRDL, JNMCH, Aligarh. To circumvent the limited availability of RNA extraction and PCR reagents, pool testing was started. 5 samples were pooled together and these pools were tested by RT-PCR. Negative pools were reported as negative whereas positive pools were deconvoluted and each sample was tested individually. In this study, 408 pools i.e 2040 samples were analysed. Results:In our study, a ΔCt value of 0.96 (i.e. an increase in Ct value in the pooled sample as compared to individual sample) was found that shows a slight loss of PCR sensitivity in pooled samples which is relatively small compared to the inherent clinical sensitivity of the standard assay. But the gains in cost effectivity and savings of resources are considera- bly high. Conclusions: As pooling of samples is a cost effective way for Covid-19 testing, the slight loss in the sensitivity of PCR can be overcomed by considering the Ct cut-off value for positive pools slightly above the kit cut off value to circumvent the dilution effect.

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