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The recent disruption of the respiratory disease known as COVID-19 infection in December 2019 has deeply affected health organizations all over the world. The most common symptoms of COVID-19 infection include fever, cough, muscle aches, and shortness of breath. The clinical and epidemiological data reveal that COVID-19 patients with a history of chronic obstructive pulmonary disease (COPD), diabetes, hypertension, cardiovascular diseases, and other comorbidities have the chance of a high rate of infection and life-threatening situations. The present healthcare emergency is having special concern for the oncology community, as COVID-19 disease causes negative consequences in cancer patients because of the immunosuppressed status of cancer patients. Although cancer communities all over the world are committed to providing safe care and treatment for cancer inmates, the present pandemic has resulted in a major shift in the approaches to cancer management. In this study, a systematic analysis of the impact of COVID-19 infection on various types of cancers has been presented. Then, the study focused on the case studies representing the scenarios of cancer patients in various countries. Finally, the study delineates the major challenges and future directions for the efficient management of the cancer community during the COVID-19 pandemic. © 2023 Elsevier Inc. All rights reserved.
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Objective: Due to the COVID 19 pandemic healthcare providers all over the world had brought some changes in the management of surgical patients. This study is aimed to estimate the impact of pandemic on surgical practices. Material(s) and Method(s): We conducted a retrospective review of the medical records of all patients admitted to the department of general surgery (both elective & emergency), SCB Medical College and Hospital, Odisha, India from April 1 to July 31, 2020, and 2021 and the records were those of patients who were admitted in the same period in 2019. Data collection includes the number of admissions, the reason for admission, the age & gender of the patients admitted patients and type of management. Result(s): There was a 57.5% reduction in total admission during first COVID in pandemic 2020 and 58.7% reduction during second wave of pandemic in 2021. The proportion of patient presenting to emergency department was more in 2020 and 2021 than 2019. Number of emergency admission decreased by 46.54% in 2020 and 46% in 2021. There was a 79.5% drop in the number of out-patients admission in 2020 and 84% in 2021. Furthermore a 79.8% reduction in elective surgical intervention noticed in 2020 and 80% in 2021. Conservative management was preferred over surgical management during the COVID era. Conclusion(s): COVID-19 has led to a drastic reduction in outpatient and elective surgical practices. Hence creating a major concern for all surgeons about the critical situation.Copyright © 2023, Dr Yashwant Research Labs Pvt Ltd. All rights reserved.
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Introduction: Acute lymphoblastic leukemia (ALL) is the commonest childhood cancer. With the evolution of minimal residual disease (MRD)-adapted intensive pediatric treatment regimens in children and Adolescent & young Adult (AYA) ALL, survival rates have improved significantly. Multiple randomized studies compared the efficacy of dexamethasone & prednisolone in childhood ALL and showed dexamethasone had a superior response in high-risk ALL and decreased cumulative incidence of relapse, but at the cost of increased toxicity. Aims & Objectives: To compare the adverse events (AE) in the two treatment groups (dexamethasone vs prednisolone) in induction therapy phase IA of ALL BFM 2009 protocol. Material(s) and Method(s): The present randomized controlled study enrolled newly diagnosed ALL patients in age group of 1-25 years at AIIMS Rishikesh between April 2021 & July 2022 after obtaining informed consent & ethical approval. Patients were randomized to receive either Dexamethasone 10 mg/m2/day administered intravenously on days 1-14 or Prednisolone 60 mg/m2/day per orally on days 1-28 during Induction Phase IA of modified ALL BFM 2009 regimen. Steroid dose was tapered off over next 7 days in both groups. Patients of infantile ALL (age<1 year), lymphoblastic lymphoma (LBL), & patients who had already received steroid or any chemotherapy prior to enrollment in the study were excluded. The adverse events of all grade, and grade 3-4 as per CTCAE version-5 were compared in the two treatment groups. Result(s): The differences in incidence of common steroid related AE's namely gastritis, proximal myopathy, hypokalemia, febrile neutropenia/ sepsis, enterocolitis/typhlitis, hyperglycemia, hypertension, invasive fungal infection and septic shock were not statistically significant in the two steroid groups. There were seven deaths in induction [Pred: 2/7;Dexa: 5/7], three were not in remission, two had MDR-bacterial infection, two had invasive fungal infection (pulmonary aspergillosis & mucormycosis), and one had COVID-19 and was not statistically significant in the treatment groups. Conclusion(s): In the present single-center experience, the toxicity profile of dexamethasone & prednisolone used in induction phase IA of ALL BFM 2009 protocol in pediatric& adolescent ALL were comparable, with no statistically significant increase in steroid-related adverse events in the dexamethasone group.
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Cyber-Physical Systems: AI and COVID-19 highlights original research which addresses current data challenges in terms of the development of mathematical models, cyber-physical systems-based tools and techniques, and the design and development of algorithmic solutions, etc. It reviews the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS) and reviews tools and techniques that can be used. This book will act as a resource to guide COVID researchers as they move forward with clinical and epidemiological studies on this outbreak, including the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS). The major problem in the identification of COVID-19 is detection and diagnosis due to non-availability of medicine. In this situation, only one method, Reverse Transcription Polymerase Chain Reaction (RT-PCR) has been widely adopted and used for diagnosis. With the evolution of COVID-19, the global research community has implemented many machine learning and deep learning-based approaches with incremental datasets. However, finding more accurate identification and prediction methods are crucial at this juncture. © 2022 Elsevier Inc. All rights reserved.
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Aim: The aim of this study is to evaluate the results of laparoscopic reversal of Hartmann’s procedure assisted by transanal circular stapler as a primary treatment modality. Materials and methods: About 32 patients presenting with an end colostomy due to various elective and emergency surgical, gynecological, and obstetric indications were selected for this study, from April 2010 to March 2016. All the patients were subjected to ultrasonography of the abdomen and pelvis, a colostogram and contrast enema, and colonoscopy. Patients selected for the study were subjected to all routine workup. Pre-anesthetic evaluation was done. Parameters such as operative time, conversion rates, intraoperative blood loss, postoperative complications, return of bowel movements, starting on oral feed, anastomotic leak, port-site infection, and hospital stay were studied. Results: About 32 patients, including both male (12) and female (20), were included in the study. The age ranged between 30 years and 65 years (mean 47.5 years). The mean operative time was 150.6 ± 20.4 minutes. Four cases were converted to open. Oral feeds were started on 2 ± 1 postoperative day. Patients tolerated solid soft diet 96 hours after surgery. Postoperative hospital stay was 7 days (range 6–8 days). No patients had anastomotic leak or required revision surgery. Three patients had port-site infections. Conclusion: We conclude that transanal stapler-assisted laparoscopic Hartmann reversal can be considered as a primary modality of treatment in the hands of an experienced surgeon though having a steeper learning curve and a higher difficulty score compared with other laparoscopic colorectal surgeries with benefits of lesser intraoperative time, early return of bowel movements, faster initiation of oral solid feeds, decreased incidence of anastomosis leak, and lesser hospital stay. © The Author(s). 2022.
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The sport tourism is an interesting area of research where the national revenues could be enhanced through sports tourism marketing and travel planning. The crises of pandemic have destroyed the hopes and aspiration of tourist, as many sports events have cancelled or postponed. Now, it is the time to realize the sustainability of sports tourism through various intelligent solutions. There is a wider scope of research in sports tourism as almost all sports event are organized in open stadium. This paper studies the pandemic effect on sports tourism and its sustainability associated with intelligent solutions and future challenges. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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This present study has used the long-short-term memory (LSTM) network-based deep learning architecture to analyze the influence of the current widespread COVID-19 on the Indian stock market. The major contribution of this work is as follows: (1) Designing LSTM-based deep neural network is used to study the effect of the COVID-19 outbreak and Lockdown on the Indian stock exchange (Nifty 50), and (2) designing a prediction model to capture the effect of various COVID-19 waves in India on Indian Stock exchange. The outcomes of the analysis show that the increase in daily new confirmed cases, recovered cases, and death cases have a significant adverse impact on the trend of the stock market. Moreover, the results of the work have also analyzed the impact of government policy such as ‘lockdown city’ with a reaction to increased Pandemic cases. This work is briefly summarized as follow: (1) LSTM-based deep neural network is used for this study to analyze the effect of the COVID-19 outbreak on the Indian stock exchange. (2) The Indian Stock exchange affected by the COVID-19 pandemic has been studied. Here, the analysis is based on the impact of COVID-19 including the effect of lockdown. (3) A prediction model has been proposed for the study of the behavior of the Indian stock index (Nifty 50) during the COVID-19 pandemic. (4) Comparison of the efficacy of the suggested approach with other existing baseline regression models. © 2022, The Institution of Engineers (India).
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Novel COVID-19 (SARS-COV-2) has emerged as one of the most hazardous pandemics across the globe. Due to the spread of this virus, there was a forcible postponement of physical education. This moved the whole education system into a fringe condition for a certain period with hopeless progress shortly. Though few countries have opted for online education, a country like India has partially succeeded. In this paper, a detailed study has been executed on the impact of COVID-19 at all levels of education with their pros and cons. The article is four-folded: Firstly, the impact of COVID-19 on the global education system is thoroughly studied with a special focus on Indian education. Second, a brief study on acceptance and adaptation of the online education process to fill the gap of schedules is done. Thirdly, an impactful analysis on the growth of development of online educational apps to fulfil the absence of offline education is emphasized. Fourthly, an insightful study on the role of intelligent computing approaches for analysing such a study is deeply investigated. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.