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1.
Journal of Clinical and Diagnostic Research ; 16(10):LC34-LC39, 2022.
Article in English | EMBASE | ID: covidwho-2114376

ABSTRACT

Introduction: Pandemics and subsequent lockdowns affect mental health of different subgroups of populations. In Coronavirus Disease-2019 (COVID-19), caregivers of those patients who have respiratory complaints is one such subgroup which is more vulnerable to disturbances in mental health, because of the fear that their patient's respiratory symptoms could be because of COVID-19. Aim(s): To assess the psychosocial impact of COVID-19 and subsequent state imposed lockdown on the caregivers of patients presenting with respiratory complaints and also to evaluate the effect of relaxation of lockdown after following-up them over a period of time. Material(s) and Method(s): This prospective observational study was conducted in the Department of Pulmonary Medicine, Government Medical College, Patiala, Punjab, India (tertiary care institute), from April 2020 to June 2020. Baseline assessment was done using socio-demographic performa, lockdown related questionnaire {3 domains, summed as total score (Lockdown)}, COVID-19 related questionnaire {Total score (COVID-19)} and General Health Questionnaire-12-Hindi version (GHQ-12). Reassessment was done twice i.e., at 11-15 days and 41-45 days after relaxation of lockdown. Quality Of Life (QOL) at first and second follow-up versus pre-lockdown times (score A and C) and first follow-up versus un-lockdown (score B) was also noted. Analysis was conducted using Statistical Package for Social Sciences (IBM, SPSS)version 22.0. Result(s): Mean age of the participants was 40.2+/-11.812 years with maximum caregivers 25 (41.7%) aged between 31-40 years. Majority (83.3%) were men. Psychological distress was experienced in 50% of caregivers at baseline and 23.7% caregivers at first follow-up (p-value=0.001). Worry for COVID-19 (p-value=0.035), Domain 1 scores (p-value <0.001), Domain 2 scores (p-value=0.003), Domain 3 scores (p-value=0.001), and Total score Lockdown (p-value <0.001) decreased significantly at first follow-up. Mean C score was significantly better than mean A score (p-value <0.001). Baseline psychological distress was significantly more in those with worry for COVID-19 (p-value=0.018), poorer scores of domains 1 (p-value=0.005), domains 2 (p-value <0.001), domains 3 (p-value <0.001), total score (Lockdown) (p-value <0.001) and total score (COVID-19) (p-value=0.010). Follow-up psychological distress was more in those with "worry for COVID-19" (p-value <0.001), negative thoughts (p-value=0.001), poorer follow-up scores of three domains, total score (Lockdown), mean A, B and C scores (p-value <0.001). Conclusion(s): Caregivers experienced extreme levels of psychological distress, which decreased, but persisted even after relaxation in lockdown. Copyright © 2022 Journal of Clinical and Diagnostic Research. All rights reserved.

2.
Global Healthcare Disasters: Predicting the Unpredictable with Emerging Technologies ; : 19-35, 2022.
Article in English | Scopus | ID: covidwho-2089279

ABSTRACT

Across the world, researchers are busy developing analytics/procedures/ methods of forecasting to identify the likelihood of getting affected by coronavirus at the individual level as well as for the macro level to formulate national/state policies. The present study is an attempt to forecast the total number of COVID-19 cases across Indian states individually and cumulative for the country so that the resources could be sourced well advance in time to prevent healthcare failure and/or mismanagement of existing resources to minimize the impacts of the pandemic as well as to identify the need of mobilization of required healthcare support to appropriate places vis-à-vis to develop new facilities like isolation, quarantine centers, and medical facilities, etc. Key points are the surge of pandemic across India and to prevent the healthcare disaster. There is a strong need for forecasting number of possible cases which is vital to restrict subsequent spread and fatality. The main objective is to develop a methodology for forecasting the number of possible cases so that future healthcare requirements shall be generated at the state level for the development of a better healthcare system. Employing autoregressive moving-average models for each state in India based on daily frequency. The impact of the epidemic is not uniform across the nation and estimating one model may generate erogenous results. 20ARIMA model has been estimated, for India and major states of India. It is based on the Cumulative Active Cases (CAC) from April 01, 2020 to September 07, 2020 in a machine learning environment where short-term forecasting was the target to understand and determine new requirements, of the healthcare system and related measures, on daily basis. Although the rate of change in daily active cases is a small fraction of the rate of new cases confirmed daily, most of the states including India are showing stationarity on second order which is a clear sign of a nonlinear sharp upward trend. In such a situation, it seems that India is about to enter the third stage of the epidemic where spread will be maximum, and so the catastrophic conditions. In such circumstances, predictions may be the only way to procure the desired amount of facilities to avoid forthcoming health-related hazards. To avoid healthcare hazards, it is recommended to opt for a system to understand the futuristic need for requisite health and medical infrastructure, both for the short and long run. © 2023 by Apple Academic Press, Inc.

3.
2nd IEEE International Conference on Intelligent Technologies, CONIT 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2029223

ABSTRACT

It's been over two years since the novel Coronavirus first appeared and with the constantly evolving new variants found around the world, the havoc of n-Coronavirus seems to be unstoppable. With more than 264 million people being affected by the n-coronavirus as of 2nd December 2021 and 5.2 million deaths around the world, there is a dire need to increase the COVID-19 testing to stop the virus from spreading further. With COVID - 19 devastating the economic situation of various countries across the globe, it has become necessary to come up with a fast, efficient, and inexpensive way to test the presence of the n-Coronavirus in people. However, the methods currently being used to test COVID 19 are rather very expensive and unavailable to a large section of society. One of the most feasible solutions to this problem is through radiological detection i.e., with Chest X - ray images. Contrary to the prevalent testing methods, Chest X - ray scans are much lesser in cost and are readily available. One major problem that arises is that COVID and pneumonia have very similar X-RAY results, so having a binary classification (COVID and NOT COVID) isn't enough. In this paper, we have put forward a model based on Convolutional NN for detection of Pneumonia, COVID - 19, and Normal patients using X - ray photos of Chest. We achieved an AUC score of 90% in our results while classifying the X-Ray Images. Besides Accuracy, we have also made the ROC Curve, confusion matrix, and classification report for our model. To keep our model lightweight, we have used a Genetic Algorithm to get the best hyperparameters possible for the model. © 2022 IEEE.

4.
Indian Journal of Radiology and Imaging ; 2022.
Article in English | EMBASE | ID: covidwho-1915320

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic in 2020 was paralleled by an equally overwhelming publication of scientific literature. This scientometric analysis was performed to evaluate the 100 most cited articles on COVID-19 imaging to highlight research trends and identify common characteristics of the most cited works. A search of the Web of Science database was performed using the keywords COVID CT, COVID Radiograph, and COVID Imaging on June 29, 2021. The 100 top cited articles found were arranged in descending order on the basis of citation counts and citations per year and relevant data were recorded. Our search revealed a total of 4,862 articles on COVID-19 imaging published in the years 2020 to 2021. The journal with maximum number of publications (n = 22), citation count (n = 8,788), and impact was Radiology. Citations for the top 100 articles ranged from 70 to 1,742 with the most cited article authored by A.I. Tao and published in Radiology. Two authors tied at first spot, having maximum impact, with both having 5 publications and a total of 3,638 citations among them. China was the leading country with both the maximum number of publications (n = 49) and total citations (n = 13,892), the United States coming second in both. This study evaluates publication and citation trends in literature and shows that the countries most affected by the pandemic early on have contributed to the majority of the literature. Furthermore, it will help radiologists to refer to the most popular and important article texts on which to base their unbiased and confident diagnoses.

5.
Lung India ; 39(SUPPL 1):S155, 2022.
Article in English | EMBASE | ID: covidwho-1857234

ABSTRACT

Background: COVID-19 and dengue infection both are caused by single-stranded RNA viruses of the families' coronaviridae and flaviviridae respectively. Both diseases share various clinical and laboratory parameters, making them difficult to distinguish from one another. In these times of covid-19 where dengue is already a public health concern, this co-infection poses great threat to already burdened healthcare system. Case Study: So, here we report a case of 76 year old male with complaints of high grade fever and dyspnea for 2 days diagnosed with COVID-19 who was simultaneously diagnosed with dengue infection and later died of ARDS and sepsis delineating the rarity and severity of this coinfection. Discussion: In the tropical counties, there is an emerging threat of dengue-covid co-infection. They have overlapping clinical presentations, also share several laboratory parameters like elevated liver enzymes, leukopenia and thrombocytopenia. Aggressive fluid resuscitation has a key role in dengue which may worsen oxygenation in COVID-19 patients. Also, the use of LMWH in COVID-19 settings can have a devastating effect in the setting of thrombocytopenia in case of dual infection. Conclusion: As we wait for more data, it is emphasized the need for early detection of the dual infection by testing all covid 19 patients for dengue in endemic areas as the disease can be more severe or one pathology can be misdiagnosed for the other.

6.
British Journal of Surgery ; 109:1, 2022.
Article in English | Web of Science | ID: covidwho-1799471
7.
Journal of Clinical and Diagnostic Research ; 16(3):LC26-LC32, 2022.
Article in English | EMBASE | ID: covidwho-1780260

ABSTRACT

Introduction: Coronavirus Disease 2019 (COVID-19) appropriate behaviour and vaccination are two critical defenses in the fight against this pandemic. As these need to be followed religiously, this preventive behaviour should be thoroughly investigated. Aim: To examine the COVID-19 vaccine behaviour amongst people attending tertiary care centre at Patiala, Punjab, India. Materials and Methods: A cross-sectional study was conducted on 200 individuals attending the Outpatient Department of Government Medical College at Patiala, Punjab, India, from 15th July to 22nd July 2021. Individuals were administered socio-demographic questionnaire, General Health Questionnaire-12Hindi version (GHQ-12), and COVID-19 vaccine related and COVID-19 appropriate behavior related questionnaire. Actual observation by the clinician regarding proper use of face masks, hand hygiene and social distancing was done and objectively scored on 0-10 for each item with a scale interval of 2. Analysis was conducted using IBM Statistical Package for the Social Sciences (SPSS) version 22.0. Results: Only 40% individuals were vaccinated. After eligibility, there was a mean delay of 4.20±3.51 weeks (median: 4 weeks) and 13.40±3.33 weeks (median: 12 weeks) in the vaccinated and unvaccinated individuals. Out of 120, 86 unvaccinated participants planned to get vaccinated in future. Significantly lower scores were obtained for actually observed COVID-19 appropriate behaviour (proper mask usage, hand hygiene and social distancing) as noted by the clinician vs the scores as reported by the participants. Conclusion: There were few takers for the COVID-19 vaccine, even weeks after eligibility. The COVID-19 appropriate behaviour was largely not being followed properly and the false sense of following the same complicated issues further. With multiple waves of the pandemic one after the other, and booster doses of vaccination, there is still an urgent need to sensitise the population at the grass root level regarding the COVID-19 vaccine behaviour to fight this pandemic.

8.
Biomedical and Biotechnology Research Journal ; 6(1):50-53, 2022.
Article in English | Scopus | ID: covidwho-1780160

ABSTRACT

The year 2019 witnessed a pandemic named COVID-19 caused by infection severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). It emerged in Wuhan, China, in December 2019 and has affected millions since then. It led to a global cry for vaccine development. Scientists arrayed the SARS-CoV-2 genome within a month of the outbreak. They used the parallels between SARS-CoV-1 and SARS-CoV-2 to speed up the vaccine preparation. As of now, different types of COVID-19 vaccines are prevailing. © 2022 Biomedical and Biotechnology Research Journal (BBRJ).

9.
British Journal of Surgery ; 109(SUPPL 1):i14, 2022.
Article in English | EMBASE | ID: covidwho-1769154

ABSTRACT

Aim: During the COVID-19 pandemic, many surveys have analysed the impact of the virus spreading on everyday medical practice, including neurosurgery. However, no one has examined the perceptions of neurosurgeons towards the pandemic, their life changes, and the strategies they implemented to deal with their patients in such a difficult time. Method: From April 2021 to May 2021, a modified Delphi method was used to construct, pilot, and refine the questionnaire. The first part focused on the evolution of global neurosurgical practice during the pandemic. This survey was distributed worldwide among 1000 neurosurgeons. The responses were then collected and critically analysed. Results: Outpatient department practices changed with a rapid rise in teleservices. 63.9% of respondents reported that they had changed their OT practices to emergency cases with occasional elective cases. 40.0% of respondents and 47.9% of their family members reported having suffered from COVID-19 at some time. 56.2% of the respondents reported having felt depressed in the last 1 year. 80.6% of the respondents found online webinars to be a good source of learning. 47.8% of respondents tried to improve their neurosurgical knowledge, while 31.6% spent extra time in research activities during the COVID-19 pandemic. Conclusions: Progressive increase in operative waiting lists, preferential use of telemedicine, reduction in the tendency to complete stoppage of physical clinic services and reduction in the administration and application of PPE kits were evident across the world. Respondents' age impacted how the clinical services and impacted mental health across the global neurosurgical fraternity.

10.
Smart Healthcare Monitoring Using IoT with 5G: Challenges, Directions, and Future Predictions ; : 229-245, 2021.
Article in English | Scopus | ID: covidwho-1765495
11.
Journal of Acute Disease ; 10(6):252-257, 2021.
Article in English | Web of Science | ID: covidwho-1572741

ABSTRACT

Objectives: To determine COVID-19 mortality and its risk factors in hospitalized patients at of a tertiary care center in north India.<br>Methods: A retrospective observational study was conducted of patients who were hospitalized from May 2020 to January 2021. The in-hospital mortality was assessed, and demographic variables and comorbidities between COVID-19 deaths and survivors were compared.<br>Results: A total of 24 000 patients were admitted during the study period, among which 17 000 had shown positive results of the RT-PCR test for COVID-19. The total mortality was 329 patients (1.37%), among which 232 (70.52%) succumbed due to COVID-19, and 97 (29.48%) died due to other illnesses. The mean age of the patients was (64.09 & PLUSMN;16.99) years. The mean age was significantly higher in COVID-19 related deaths [(67.63 & PLUSMN;13.78) years] as compared to that of the survivors [(60.52 & PLUSMN;19.5) years] (P < 0.001). Compared to COVID-19 survivors, there were more males (72.41% v.s. 61.5%) and less females (27.59% v.s. 38.5%) in COVID-19 related deaths (P=0.001). Comorbidities such as hypertension, diabetes mellitus, and chronic kidney disease showed a significant correlation with COVID-19 mortality with an adjusted odds ratio of 2.389 (95% CI: 1.465-2.982), 3.891 (95% CI: 2.059-5.392), and 6.358 (95% CI: 5.675-10.564), respectively.<br>Conclusions: Elderly males with comorbidities have higher risk for mortality related to COVID-19. Ongoing vaccination drive is rightfully prioritised to serve the high-risk category first.

12.
Journal of Neuroanaesthesiology and Critical Care ; 7(3):170-171, 2020.
Article in English | EMBASE | ID: covidwho-1260972
13.
Studies in Systems, Decision and Control ; 324:139-156, 2021.
Article in English | Scopus | ID: covidwho-1130688

ABSTRACT

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. The disease causes a respiratory illness with symptoms like cough and fever and, in more severe cases, causes difficulty while breathing. COVID-19 spreads primarily through contact with an infected person when they sneeze or cough or by touching a surface that has that virus on it and then touching our mouth, nose, or eyes. The disease was first observed in the central Chinese city of Wuhan at the end of 2019. The outbreak has been declared a global pandemic. The novel coronavirus is already reorienting our lives, but the crisis moments also present an opportunity for more sophisticated and flexible use of technology. The epidemic is impacting the global population as the number of cases is increasing rapidly, and there is an urgent need to stop the virus from spreading. The outbreak has triggered massive demand for digital health solutions, and for this, the drones and robots present an excellent method for automation of manual activities. Drones and robots can be used to provide services to the patients and those who are quarantined and are the most desirable and safe way to fight against the outbreak and limit contamination and spread of the virus. The following chapter will discuss the various solutions based on drones and robots in the field of AI and IoT, such as drones being used for social distancing and robots for sanitization. Further, analysis has been made about the total number of cases and deaths around the world and also how it has affected humanity and what measures have been taken to control this deadly disease. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

14.
IOP Conference Series: Materials Science and Engineering ; 1022, 2021.
Article in English | Scopus | ID: covidwho-1096471

ABSTRACT

The outbreak of the Corona Virus (COVID-19) that has begun in December 2019 drastically affected the world. Endemic Coronavirus (COVID-19) is rapidly growing across the globe. SARS-CoV-2 is the virus name that causes a highly contagious and deadly disease COVID-19. It also entered India by the end of January 2020 and has significantly influenced India. More than two million people worldwide have been confirmed to have been contaminated with this virus as of the date (29 July 2020), and more than 7, 24,000 have died of this disease. The governments of most countries, including India, have already taken several measures to reduce the spread of COVID-19, such as lockdown, social distancing, closure of shopping malls, gyms, schools, universities, religious gatherings, etc. This lockdown has affected every Indian sector, such as the Economy, Retail Sector, Tourism Industry, etc. This paper aims to explore to what extent a 2020 epidemic like Covid-19 had impacted the Indian economy using a machine learning approach. The statistical data from esteemed and trustworthy information sources were gathered to realize the impact of the Corona Virus on the Indian economy. Based on this trusted data, analysis has been performed using the various regression models. © 2021 Institute of Physics Publishing. All rights reserved.

15.
European Journal of Gastroenterology & Hepatology. Publish Ahead of Print ; 22:22, 2020.
Article in English | MEDLINE | ID: covidwho-998551

ABSTRACT

BACKGROUND: Coronavirus disease 2019 (COVID-19) has caused a global pandemic unprecedented in over a century, with =35 million cases, and more than 1 million deaths globally. Though predominantly a lower respiratory illness, other organ injuries are well-recognized. Among these, liver injury is of major interest. OBJECTIVE: To define prevalence, pattern, predictors, and impact of liver injury among patients hospitalized with COVID-19. METHODS: Demographic, clinical, and biochemical data were collected retrospectively among patients admitted to St. Luke's University Hospital with COVID-19 between 1 March and 18 April 2020. Association of liver tests (LTs) with mortality and need for mechanical ventilation, adjusted for demographic, clinical and biochemical predictors, was examined. RESULTS: Data were available on 551 patients. Prevalence of any or >=3 x upper limit of normal transaminase elevation on was 61.2 and 9.4% on admission, and 72.1 and 22.4% at peak. Bilirubin and alkaline phosphatase elevations were less common on admission (11.4 and 12.6%, respectively), and at peak (17.7 and 22%, respectively). All liver test (LT) elevations were consistently predicted by inflammatory markers. Hyperbilirubinemia predicted mortality on admission and at peak. Aspartate aminotransferase (AST) and alanine aminotransferase (ALT) had opposite impact on mortality with AST positively, and ALT negatively associated with mortality. Hence, besides hyperbilirubinemia, AST:ALT ratio emerged as the best marker for mortality among the LTs. CONCLUSION: LT elevations among patients presenting with COVID-19 are very common, though majority are mild. Admission and peak bilirubin >=1 mg/dl, as well as admission and peak AST:ALT ratio were significant predictors of mortality, along with age, myocardial injury, and chronic medical illness.

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