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Introduction: COVID-19 is an infectious disease caused by the SARS-CoV-2 virus that commonly involved the respiratory system. However, the virus can affect any organ in the body including the liver. Hepatic involvement in COVID-19 could be related to the direct cytopathic effect of the virus, an uncontrolled immune reaction, sepsis, or drug-induced liver injury. Background: The current study aims to evaluate the relevance of liver enzyme derangement in COVID-19. Methods: The sample size of 165 patients, tested positive for covid 19 and underwent liver enzyme testing. These patients were categorized into mild, severe, and critical diseases based on clinical evaluation, radiological findings, and biochemical parameters. Results: Of 165 patients selected 103 (62.4%) have mild disease, 40(24.2%) have severe and 12(7.2%) suffered from the critical disease. 48(29.1%) patients show deranged liver function. 83.3% of critical patients and 45% of severe patients show deranged liver function.9.09%of patients died due to severe COVID-19 infections showing moderately to severe liver function derangement. Conclusions: This study concludes that the severity of COVID-19 disease may increase due to chronic liver disease, particularly fatty liver. Atypical ALT and AST levels during hospitalization were indicative of liver injury and correlated with the severity of patients.
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Aims and objectives: The aim of this study was to compare the immediate adverse effects of the coronavirus disease 2019 (COVID-19) vaccine (COVAXIN) in a pregnant woman with that of a nonpregnant woman. Material(s) and Method(s): It is a prospective observational study done at Vanivilas Hospital, Bangalore Medical College & Research Institute (BMCRI) for 2 months. The sample size was 100 pregnant and 100 nonpregnant women. Telephonically, patients were followed-up, and details of the side/adverse effects were collected in a proforma after 2 and 14 days. Data collected from both groups were analyzed using the Chi-square test or Fisher's exact test. Result(s): The majority of women were in the age group of <=25 years (64.0% and 36.0%, respectively) with a mean age of 25.01 +/- 3.71 years among the pregnant and 28.52 +/- 6.00 years among nonpregnant women. About 25.0% of pregnant women and 38.0% of nonpregnant women reported side effects. About 15.0% and 22.0% had taken treatment for side effects among pregnant women and nonpregnant women, respectively. Among the pregnant women, the common side effects reported were injection site pain (17) followed by fever (5), fatigue (4), and myalgia (03). Whereas among the nonpregnant women, the common side effects reported were injection site pain (28) followed by fever (6), myalgia (3), headache (2), and fatigue (1). Conclusion(s): Side effects reported following the administration of Covaxin in pregnant and nonpregnant women are fever, fatigue, injection site pain, myalgia, and headache. The proportion of side effects was not significantly different in the pregnant and nonpregnant women following Covaxin administration. Clinical significance: Covaxin is an inactivated killed vaccine against COVID-19 by Bharat Biotech. The vaccine has been recommended for pregnant women by the Government of India during corona pandemic. Studies are lacking regarding the difference in adverse events in pregnant versus nonpregnant women, after vaccine administration.Copyright © The Author(s).
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The COVID-19 diagnosis using Chest X-ray image processing algorithms can offer a significant influence on medical diagnosing. The sparseness in the progression of COVID-19 and its respective diagnosis limitation shows the main challenge involved in the algorithm for detection from X-ray images. For processing such images require more robust approach and deep neural networks can provide the better solution in terms of accuracy along with less complexity in processing for faster detection. This paper contributes in terms of Convolutional Neural Network (CNN) model with 4 channel (4-CH) for COVID-19 identification with less processing requirements and less effects of neighboring pixels during convolution operations. These convolution operations are the main processes that improve the accuracy of the network. The performance evaluation shows better results in terms of accuracy, specificity and sensitivity. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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BACKGROUND & AIMS: Nowadays, the whole World is under threat of Coronavirus disease (COVID-19). The ongoing COVID-19 pandemic has resulted in many fatalities and forced scientific communities to foster their Research and Development (R&D) activities. As a result, there is an enormous growth of scholarly literature on the subject. We here in this study have assessed the Indian publications contributions on COVID-19. METHODS: WHO is curating global scientific literature on coronavirus since it declared COVID-19 a global pandemic through Global Research Database on COVID-19. The present study analyzed Indian publications on SARS-CoV-2 as found in WHO COVID-19 database. The research data was restricted for the period of March 2, 2020 to May 12, 2020. RESULTS: The study found that there is a considerable and constant growth of Indian publications on COVID-19 from mid-April. It is interesting to note that, the most prolific authors belong to either AIIMS or ICMR institutes. Delhi state contributed highest number of publications on COVID-19. The AIIMS, New Delhi was the most productive institution in terms of publications. The Indian Journal of Medical Research has emerged as the productive journal contributing highest number of the publications. In terms of research area, the majority of the publications were related to Epidemiology. CONCLUSIONS: The highly cited publications were of evidenced based studies. It is observed that the studies pertaining to virology, diagnosis and treatment, clinical features etc. have received highest citations than general studies on epidemiology or pandemic.