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1.
2022 International Joint Conference on Neural Networks, IJCNN 2022 ; JOUR, 2022-July.
Article in English | Scopus | ID: covidwho-2097615

ABSTRACT

The worldwide breakout of the novel COVID-19 has resulted in one of the worst epidemics in modern times since World War II. Although various vaccinations are being produced, their efficacy remains a considerable hurdle. This is especially true when new virus strains emerge. The main challenge to combating this pandemic is diagnosing and isolating COVID-19 positive cases as early as possible. As a result, COVID-19 needs to be detected early and accurately to prevent its spread. This paper proposes a computer-aided automated COVID-19 detection tool based on Computed Tomography (CT-scan) images of lungs. The proposed approach applies an ensemble technique based on Sugeno Fuzzy Integrals with convolutional neural networks (CNNs) as the base model. The lack of COVID-19 data makes it challenging to train a standard CNN from scratch, so we use a transfer learning approach instead of training the base classifiers, VGG-16, InceptionResnetV2, and Xception. We apply the gained knowledge in the target domain of small CT-scan data, considering ImageNet dataset as the source domain. We have also adapted image pre-processing techniques to remove noises so that the model can only focus on specific features. Our proposed framework achieves 98.99% accuracy on a publicly available dataset and outperforms the existing state-of-the-art methods. Experimental results and comparative analysis with baselines establish the need and effectiveness of our proposed model. © 2022 IEEE.

2.
Indian Journal of Public Health Research and Development ; 13(4):188-193, 2022.
Article in English | EMBASE | ID: covidwho-2081578

ABSTRACT

Introduction: Worldwide there was a pandemic of novel corona virus infection in which one of the major concern was the risk of thrombosis and the mortality associated with it. Aim(s): In this study our aim was to observe the changes in D-dimer levels during disease progression and its correlations with severity of Pneumonia, duration of hospital stay and mortality of COVID-19 patients. Material(s) and Method(s): In this study we reported the clinical, radiological and pathological laboratory results of 432 cases of confirmed COVID-19 infection. In these patients their clinical presentation, concentration of D-dimer, coagulation parameters, CBC, severity of Pneumonia on HRCT, hospital stay and higher mortality were retrospectively analyzed. Result(s): All the statistical variables were expressed in % and compared withx2 test. Out of the 432 cases in 45 cases (10.41%) the D-dimer values were >2.4microg/ml and in 15 cases the value were very high (3.47%). When correlated these patients found to have severe degree of pneumonia, longer hospital stay and higher mortality rate in comparison to patients with D-dimer level of <2.4 microg/ml. Conclusion(s): D-dimer level could be used as an early marker for the clinical classification, risk stratification and improved management of COVID-19 patients. Copyright © 2022, Institute of Medico-legal Publication. All rights reserved.

3.
Illn Crises Loss ; 2022.
Article in English | PubMed Central | ID: covidwho-2064595

ABSTRACT

In the early months of the COVID-19 pandemic in India, due to strict lockdown, the family members of the victims of COVID-19 had to witness the dying and death of their relatives in solitude, improper funerals, and the absence of death rituals. After in-depth interviews with twelve relatives of seven deceased patients conducted more than a year after experiencing those deaths of loved ones, it was found that most of them had been struggling with long-term complicated grief without a sense of resolution. As funerals and death rituals, following the work of Van Gennep in his ‘Rites of Passage’, ensure the transition of grievers from a preliminal state by preparing for the imminent loss to a postliminal renovated stable state by reabsorbing them into the collective social and cultural conditions, the absence of that compels the mourners to get stuck in a liminal state, or limbo.

4.
Diabetes ; 71, 2022.
Article in English | ProQuest Central | ID: covidwho-1952109

ABSTRACT

Background: Recent evidence suggests a bidirectional relationship between COVID-infection and new-onset diabetes (NOD) presenting with DKA. Methodology: This one-year prospective study comprised of 29 COVID-negative DKA (controls) and 52 COVID-positive-DKA patients (18 NOD, 15 T1DM ,T2DM) . NOD were previously normoglycemic and negative for GAD/IA-2/ZnT8 autoantibodies. After 75g- OGTT with estimation of glucose, C-peptide, FFA and insulin at 0,15, 30,45, 60,90 ,120, 150 and 180minutes, Insulin secretion rate (ISR) [C-peptide-deconvolution] , Hepatic insulin sensitivity [AUC-glucose × AUC-insulin during first 30-minutes of OGTT ], Peripheral insulin sensitivity [ dG/dt ÷ mean plasma insulin concentration;dG/dt rate of decline in plasma glucose concentration]were calculated alongwith Metabolomics and Adipose tissue gene expression. All tests were performed at admission and 4, 8, and 12-months of followup. Results: At baseline, ISR in NOD was significantly reduced than controls (p=0.001) but similar to T1DM (p=0.15) . Nearly 83% (n=17) of NOD with DKA had near-complete recovery of ISR on follow-up compared to T1DM (all p<0.01) ,with non-remitters (n=3) having significantly worse admission Hba1c and IL-6 (all p<0.01) . NOD had significantly increased hepatic and peripheral insulin resistance compared to T1DM (all p<0.05) ,but similar to T2DM (all p>0.05) . Their Metabolomics revealed increased inflammatory phosphatidylcholines, that correlated with peripheral glucose uptake (p<0.01) ,while RNA sequencing showed significantly enhanced WNT5A , TLR4 (Toll-like Receptor-4) and RETN (resistin) than T1DM and T2DM (both p=0.001) . Conclusion: Our study provides novel insights into COVID-associated NOD with DKA. Majority have near-complete recovery of insulin secretion while simultaneous multi-tissue insulin resistance and inflammatory adipose tissue profiles persist as drivers of hyperglycemia.

5.
Indian Journal of Rheumatology ; 17(2):153-156, 2022.
Article in English | EMBASE | ID: covidwho-1928755

ABSTRACT

Background: The coronavirus disease or COVID-19 pandemic is the major global health crisis of the present time. Various rheumatological manifestations have been reported during or after COVID-19 infection, but data are scarce. In this observational study, we have tried to analyze the clinical characteristics of COVID-19 associated arthralgia/arthritis. Methods: We have collected the clinical data of 14 patients over the past 6 months who have developed arthralgia or arthritis during or after symptomatic COVID-19 infection, proven by a positive reverse transcription-polymerase chain reaction test from nasopharyngeal swab. Results: The most common symptoms during COVID-19 infection in the 14 patients were fever and myalgia, being present in 92.8% and 64.3% patients, respectively. Arthralgia/arthritis occurred at a mean interval of 20 days (range: 0-60 days). Knee was the most commonly involved joint (78.6%), followed by the wrist and metacarpophalangeal joints (each in 57.1%). Enthesitis was documented in 21.4% patients. The mean duration of COVID-19 associated arthralgia or arthritis was 53.9 days (range: 7-210 days). In 85.7% patients, joint pains improved within 2 months;in only a small proportion of patients (14.3%), joint pains persisted after 6 months. Nonsteroidal anti-inflammatory drugs (NSAIDs) (given in 64.3% patients) and corticosteroids (in 50%) were the most commonly prescribed and effective treatment options. Conclusion: COVID-19 infections mostly caused reactive arthritis, though acute and chronic arthritis is also seen. In the majority of cases, arthritis started about 3 weeks after COVID-19 infection and subsided within 2 months. NSAIDs and corticosteroids are the most effective treatment options.

6.
Management of Environmental Quality ; : 20, 2022.
Article in English | Web of Science | ID: covidwho-1868505

ABSTRACT

Purpose Taking a retrospective view, the present study aims to investigate the resilience of shared facilities (accommodation) across India in the post-pandemic period. More specifically, it explores the issues and challenges in implementing sustainable practices in the long run taking a dual perspective of both consumers and service providers. Design/methodology/approach A mixed-method study was pursued in exploring the future resilience of the shared facilities in the post-pandemic period. A multi-method triangulation approach was adopted involving both data collection and data analysis. Primary data was collected through focus group sessions and analysed through a grounded theory study. Whereas, secondary data was extracted from Twitter and processed through textual data mining using the NVivo (12 Pro) software. Critical themes and sentiments were explored through the dual study and a corroboration process was followed thereon to support the findings. Findings The dual study extracted major themes pertaining to the present pandemic scenario wherein recovery strategies are at the top priority for all tourism service providers. Among the major themes tourists 2019 passiveness towards the environment existing misconceptions with shared facilities and situational perspective emerged as critical issues worrying service providers in the post-pandemic period. Furthermore the sentiment analysis indicated a positive start to the recovery measures wherein both tourist and tour operators are confident to embrace and restore the shared facilities/business respectively with additional care and responsibilities. Originality/value The novelty of the study lies in the identification of critical themes and sentiments concerning the future resilience of the shared economy businesses post-pandemic period in Indian tourism which can have a generalized effect across the world. Moreover, the study corroborated the findings of the dual study where similarities among the themes were observed.

7.
IEEE International Conference on Recent Advances in Systems Science and Engineering (RASSE) ; 2021.
Article in English | Web of Science | ID: covidwho-1822039

ABSTRACT

Over the past year, COVID-19 has become a global pandemic and people across the globe have suffered a lot from this pandemic. The rate of transmitting the coronavirus in people is very quick. A rapid diagnosis can potentially help governments in identifying the pattern of transmission. There are some tests available but those tests take a long time to give the report. So, in this work, we have proposed a model that will distinguish between normal people, COVID affected people, and pneumonia affected people with the help of an X-ray. X-ray images are considered because taking an X-ray image is very little time-consuming. In this work, we have trained the X-ray images with a novel Deep Learning approach with SpinalNet architecture, and that distinguishes normal people, COVID affected people, and pneumonia affected people. After training the model we have achieved a very good accuracy for the SpinalNet architecture that is 96.12% while the traditional model provides 95.50% accuracy. We present precision, recall, and Fl scores of COVID and Pneumonia classes. We also present our results and codes with execution details. This paper contains the link to Kaggle notebooks with execution details. The applied Spinalnet transfer learning code is available in our GitHub repository: https://github.com/dipuk0506/SpinalNet

8.
Journal of the Indian Medical Association ; 118(7):28-33, 2020.
Article in English | Scopus | ID: covidwho-1787055

ABSTRACT

COVID 19 pandemic has a significant impact on global public health and economies. Scientists and researchers all over the world are endeavouring in search of specific drug against COVID19 virus. For a novel emerging virus, specific antiviral drug takes time before its approval for clinical use as RCTs are expensive and time consuming. In Indian perspective, many drugs which are currently under clinical trial are unavailable. Reviewing available published and unpublished papers, we intend to throw light on the drugs that can be used in the interim in India till further evidence come. Pending sufficient evidence remdesivir, favipirvair,tocilizumab,lopinavir-ritonavir with or without ribavirin;hydroxychloroquine or convalescent plasma can be considered. © 2020 Indian Medical Association. All rights reserved.

9.
National Journal of Medical Research ; 12(3):97-99, 2021.
Article in English | GIM | ID: covidwho-1717278

ABSTRACT

"Introduction: The novel coronavirus, SARS-CoV-2 presented with a wide array of clinical, inflammatory and radiological manifestations. Currently, a very few data is available about the relationship in between pattern of fever and biochemical parameters in patients affected by COVID-19. Our objective is to find out the clinical and inflammatory status of COVID-19 patients and whether there is a relationship in between pattern of fever and biochemical parameters of severe acute respiratory syndrome coronavirus disease 2. Methodology: A retrospective study conducted on 60 COVID-19 positive patients, who were clinically/radiologically evaluated and screened for inflammatory markers. Result: 39 men and 21 women had Fever and elevated inflammatory markers like CRP, D-dimer, ferritin, ESR. Altered neutrophil lymphocyte ratio was also found. Patients with moderate and severe grade fever had more significant rise in CRP (60%), D-dimer (50%).patients with mild and moderate fever had more rise of ferritin (65%). ESR and NLR were not significantly increased. Patients with intermittent fever had high rise in CRP (80%), D-dimer (75%), and ferritin (72%). Again, ESR was not significantly raised. NLR was moderately raised in patients with continuous fever (66%). Sub acute and chronic rise of temperature shows more significant rise in CRP (60%), D-dimer (82%), ferritin (80%), NLR and ESR.

10.
National Journal of Medical Research ; 11(4):121-124, 2021.
Article in English | GIM | ID: covidwho-1717277

ABSTRACT

Introduction: Since the end of 2019, the world is witnessing the emergence of the coronavirus disease 2019 (COVID-19) outbreak and pandemic caused by a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This disease presented with a wide array of clinical, inflammatory and possible autoimmune manifestations. Currently, a very few data is available about the involvement of autoimmunity in patients affected by coronavirus disease 2019 (COVID-19). Aim: To find out the clinical and inflammatory status of COVID-19 patients and whether this disease (SARS-CoV-2) stimulates autoantibody production and contributes to autoimmunity activation. Methodology: A hospital based retrospective study conducted on 60 COVID-19 patients. All patients were clinically and radiologically evaluated and screened for common inflammatory markers and auto antibodies. Result: Patients included were 39 men (65%) and 21 women (35%). 33 patients were mild cases, 15 were moderate and 12 were severe cases with a mean age of 44.27. Fever and shortness of breath were the dominant symptoms;most patients had at least one coexisting disorder on admission;the most common characteristic on chest CT was groundglass opacity;the most common findings on laboratory measurements of inflammatory markers were elevated levels of CRP, LDH, ferritin and altered neutrophil lymphocyte ratio;and prevalence of autoantibodies, anti SSA/Ro antibody, anti SSB/La antibody, and antinuclear antibody was 20%, 10%, and 15%, respectively and Anti-TPO antibody was positive in 33.3% patients.

11.
Biomedical and Biotechnology Research Journal ; 5(4):366-373, 2021.
Article in English | Web of Science | ID: covidwho-1580219

ABSTRACT

The pandemic of novel coronavirus disease-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has stimulated scientists from different backgrounds to gear up on developing vaccines against the virus. Several antigenic epitopes of the virus have the potential to induce an immunogenic response, among which viral spike protein ("S" protein) is considered to be the most suitable vaccine candidate. In this review, the latest progress in the field of plant molecular pharming (PMF), its application, limitations, and commercial initiatives toward the production of the SARS-CoV-2 vaccine have been discussed. Vaccine production by PMF has gained considerable attention these days and can be used for large-scale commercial production of antigenic proteins, antibodies, and other biopharmaceuticals. New age plant breeding techniques facilitated by CRISPR-Cas-based genome editing technology and next-generation sequencing methods also help to achieve greater precision and rapidity. Several unique advantages are offered by plant-based vaccine production techniques over that of the microbial or mammalian cell culture system. Virus-like particles and Agrobacterium-mediated transient somatic expression systems have a high potential for the large scale, cost-effective, and robust production of plant-derived vaccines against SARS-CoV-2.

12.
Journal of Clinical and Diagnostic Research ; 15(11):LC46-LC49, 2021.
Article in English | EMBASE | ID: covidwho-1527011

ABSTRACT

Introduction: Telemedicine counselling service for Coronavirus Disease 2019 (COVID-19) has an immense importance in India. Hard to reach rural areas have more skewed ratio and due to mandatory quarantine during COVID-19, availing physical consultation from doctors has become more difficult. Aim: To find out the queries of the callers in COVID-19 support cell and their satisfaction of this service. Materials and Methods: This cross-sectional study was conducted at Institute of Post Graduate Medical Education and Research (IPGMER), Kolkata in May 2021. Total 152 participants were included in the study. Data were collected by telephonic interview using a pre designed pretested interview guide. Queries of the callers to the telemedicine centre were recorded along with their demographics. Satisfaction was measured in a scale of 0-10. Results: Mean age of the patients were 44.5±17.05 years;114 (75%) callers were male and 93 (61.2%) were from rural areas of West Bengal. There were 78 (51.3%) callers who were repeat callers. The most common query {90 (59.21%)} was “when positive patients would undertake next Rapid Antigen Test (RAT)/ Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) test to find out whether they were negative.” The mean satisfaction score was 6.29. Conclusions: Telemedicine services were availed by many callers from rural area. The support cell responded to queries like what drugs to be taken and home isolation duration. Majority of the callers felt satisfied after consultation, thus, indicating effective role of teleconsultation.

13.
3rd International Conference on Computational Advancement in Communication Circuits and Systems, ICCACCS 2020 ; 786:355-366, 2022.
Article in English | Scopus | ID: covidwho-1499394

ABSTRACT

Human history is observing a very strange time fighting an invisible enemy;the novel COVID-19 is the greatest challenge to humankind since the Second World War. The current outbreak of COVID-19 coronavirus infection among humans in Wuhan (China) and its spreading around the globe is heavily impacting global health and mental health. Novel coronavirus (n-CoV) is a generic name given to severe acute respiratory syndrome coronavirus 2(SARs-CoV-2). It has rapidly spread around the world posing enormous mental, social, economic, and environmental challenges to the entire human population. This paper evolved from an overview of the coronavirus and its effect on public health and economics. The main focus of this paper is to survey the various species and types of COVs. The overall statistics of the count around the world and an inclusive survey of its impact on society is being discussed in this paper. In this paper, the linear regression analysis of different vaccines commissioned around the world in COVID-19 and manifold updated information across India has been analyzed in a statistical approach. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

14.
Journal of the Indian Medical Association ; 119(5):21-27, 2021.
Article in English | EMBASE | ID: covidwho-1471427

ABSTRACT

Background: The declining trend of COVID-19 infection in India has made healthcare personnel (HCP) and general public lenient about personal-protective-measures. Serosurveys to estimate the prevalence of SARS-CoV2 IgG antibodies, particularly in high-risk-zones like hospitals can give the real scenario and risk-factors can help prioritise the target population for urgent, effective vacccination. Methods: 1470 consecutive HCP from 4 tertiary-care-hospitals in Kolkata filled a questionnaire and were tested for serum SARS-CoV2-IgG by Enzyme-linked Immunosorbent Assay (ELISA). The prevalence of SARS-CoV2-IgG among asymptomatic HCPs was studied and the work environment, clinical comorbidities, personal habits and protective measures and pharmacologic prophylaxes were compared between those with and without SARS-CoV2-IgG. Parameters of asymptomatic seroconverters were also compared to those with personal history of COVID-19-Infection. Logistic regression was done to identify independent risk-factors. Results: Prevalence of asymptomatic seroconversion was 15.8%. Asymptomatic seroconverters (n=208) were mostly working in mixed hospitals (having both COVID-19 and non-COVID-19 wards, 57.7%), were non-doctors by profession (nurses-25.1%, others–51.4%). Among asymptomatic HCP, indepedendent positive risk factors for SARS-CoV2 IgG-positivity were Diabetes Mellitus (DM) and multiple comorbidities (pboth <0.001) and prophylactic use of Hydroxychloroquine and Famotidine (pboth < 0.03). However, for symptomatic COVID-19 infection, working in COVID-19 dedicated hospitals, and personal h/o COPD were positive risk-factors and Ivermectin prophylaxis a negative risk-factor (pall < 0.03). Conclusion:In our study conducted i n the i mmedi ate pre-i mmuni sati on peri od, rate of asymptomati c seroconversion among HCPs is too low to presume herd immunity. Those working in mixed hospitals and DM, multiple comorbidities are at particularly high risk.

15.
EAI/Springer Innovations in Communication and Computing ; : 31-65, 2022.
Article in English | Scopus | ID: covidwho-1404619

ABSTRACT

The rapid spread of the coronavirus disease 2019 (COVID-19) epidemic poses a threat to human civilization. This infectious outbreak induced a global menace, resulting in day-to-day community and social services standstill. Countries like China and Italy are positioned at an alarming stage of this pandemic, and India is also testifying a rapid outbreak of the COVID-19.This unprecedented scenario warrants the formulation of a robust mechanism to estimate the misfortunes of this pandemic in these three countries to assist governments in countermeasuring the COVID-19 catastrophe. In the light of fast varying fatality data rendered by the World Health Organization (WHO), a spectrum of case-based fatality assessments for the COVID-19 is presented that differs considerably in measurements. This publication elucidates the scope of the curve-fitting methods in terms of the goodness-of-fit statistics and support vector machine-based regression (SVR) in estimating the misfortunes of COVID-19 in China, Italy, and India in a given time frame. Consequently, we achieved a reasonably small root mean squared error (RMSE) for the SVR method in predicting the adversities induced by this global pandemic in China and India. In contrast, conventional regression offers a better estimate to sketch the outbreak pattern in Italy. © 2022, Springer Nature Switzerland AG.

16.
Journal of the Scientific Society ; 48(2):93-97, 2021.
Article in English | Web of Science | ID: covidwho-1380024

ABSTRACT

Background: A significant portion of the global population seeks health-related information on the Internet. The world is searching for an effective vaccine to control the coronavirus disease-19. Knowing the information-seeking behavior of the population helps in designing an awareness program. Aim: This study aimed to explore the information-seeking behavior of the global and Indian population by analyzing Internet search trends. Materials and Methods: This cross-sectional study was conducted from April to November 2020. We used fully anonymous data available in the public domain (https://trends.google.com/trends). The phrase "COVID vaccine" was searched with "schedule," "when," "cost," "where," and "side effect" to compare the trends. The global and Indian data were categorized month-wise and statistically tested by the Chi-square test. Results: Global Internet users seek information on "when" the COVID vaccine would be available followed by "where" to get the vaccine. The "schedule," "cost," and "side effect" come later. Indian search trend is similar for "when" and "where." However, the third query was the "cost" followed by "schedule" and "side effect." Conclusion: The Internet search trend showed that people around the world want to know when they would get a vaccine and where to get it. The least search volume was about the side effects of the vaccine. Primary care physicians, government, and nongovernment stakeholders may use this finding for optimum dissemination of information both online and offline.

17.
Journal of Nature and Science of Medicine ; 4(3):288-295, 2021.
Article in English | Scopus | ID: covidwho-1355836

ABSTRACT

Background: During the coronavirus disease-2019 pandemic, learning activity via the digital medium has suddenly increased. Medical teachers quickly adapted with synchronous (i.e., online classes), and asynchronous (i.e., video-and other materials-based learning) method of delivering the content to the students. Aim: We aimed to explore the comparative preference of face-to-face lecture, synchronous, and asynchronous learning among Indian undergraduate medical students. Materials and Methods: We conducted a cross-sectional nation-wide online survey in July–August 2020 with a snowball sampling technique. We collected response from undergraduate medical students who had attended both online classes and video-and other materials-based learning. Preference on the three modes of learning (namely, face-to-face lecture, online synchronous, and asynchronous) was recorded in a 10 point Likert-type scale. Obtained responses were statistically compared by analysis of variance with a P < 0.05 to be statistically significant. Results: A total of 695 (female = 304 (43.74%), male = 391 (56.26%)) entries were analyzed. Overall, traditional face-to-face lecture class was the most preferred method (8.68 ±1.49) followed by asynchronous (6.33 ± 2.22) learning and then online classes (5.22 ± 2.55, P < 0.0001). Perceived attention, interest, scope of learning, and possibility of interaction with the teachers were highest in face-to-face lecture. The scope of taking notes from all three modes was equal but the scope of formative assessment was highest with synchronous learning. The distraction was highest with asynchronous learning. Conclusion: Undergraduate medical students in India prefer to learn by face-to-face lecture while compared with distance delivery via the digital media. Postpandemic blended learning may be planned with the following sequence of importance: Face-to-face lecture >asynchronous >synchronous learning. © 2021 Journal of Nature and Science of Medicine ;Published by Wolters Kluwer-Medknow.

18.
Journal of Clinical and Diagnostic Research ; 15(8):LC01-LC04, 2021.
Article in English | EMBASE | ID: covidwho-1355188

ABSTRACT

Introduction: The dominant respiratory feature of Coronavirus Disease 2019 (COVID-19) is arterial hypoxaemia, greatly exceeding abnormalities in pulmonary mechanics. Arterial Blood Gas (ABG) analysis helps to find out respiratory, metabolic acidosis and alkalosis. Aim: To evaluate the blood gas levels among critically ill COVID-19 positive patients admitted in Intensive Care Unit (ICU). Materials and Methods: A retrospective, observational study was conducted. Data of ABG analysis {pH, PaO2 (partial pressure of oxygen in arterial blood), PaCO2 (partial pressure of carbon dioxide in arterial blood) and bicarbonate (HCO3)} in 314 adult COVID-19 positive cases were obtained from ICU records. All critically ill COVID-19 patients those who were admitted in ICU and age more than 15 years of age were included in this study. Data were analysed and Pearson correlation test was applied for statistical significance. Results: Among the study subjects, 234 (74.5%) were male. Most affected age group was 51-60 years among males and above 60 years among females. Most common ABG finding was high pH indicating alkalosis, found among 183 (58.3%) patients. Acidosis was rare and seen in only 19 (6.0%) patients. A total of 174 (55.4%) patients developed respiratory alkalosis with low PaCo2. Hypoxaemia was found in 144 (45.9%) patients. High HCO3, indicating metabolic alkalosis, was seen in 144 (45.9%) patients. Statistically significant correlation was found between PaCO2 and pH (person correlation coefficient (r) =-0.153, p=0.007) and PaCO2 and HCO3 standard (r=0.185, p=0.001). Conclusion: ABG should be done in all COVID-19 patients during admission. A regular interval monitoring of ABG can help in early identification of respiratory damage, silent hypoxia and cytokine storm and with early detection many lives can be saved with early initiation of management.

19.
Frontiers in Education ; 6, 2021.
Article in English | Scopus | ID: covidwho-1304588

ABSTRACT

Several studies have been conducted to understand the predictors of academic performance of various levels of high school and undergraduate students as quantified by the grade point average. This study focuses specifically on engineering students as they differ from other undergraduate students in their background and expectations. We focus on quantifying essential predictors of the performance of engineering students in an advanced mathematics course. We collected data from 72 participants recruited from engineering students enrolled in the advanced engineering mathematics (AEM) course in a research university. We chose this course to represent a standard engineering mathematics course covering several essential topics. We consider several factors in our analysis, such as cellphone usage and the academic background, e.g., the academic year, number of minors, and majors, performance in prerequisite courses. We perform several regression analyses to understand the effects of cellphone usage, course schedule, and academic background on performance in the AEM course and its prerequisites. In particular, we use the stepwise regression technique using forward selection and backward elimination procedures. We discovered a few interesting findings in this case study. Firstly, for the participants in this study, we find that the daily average “screen time” on their cellphones is not a statistically significant predictor of student performance. This finding contradicts some prior studies on this participant and may indicate adaption and integration of the technology by the new generation of students in recent years. We also found that the lecturing schedule was not an influential factor for their academic performance. These findings are especially relevant during the COVID-19 pandemic, as they suggest that advanced engineering students have adapted to the use of technology and are flexible concerning lecture schedules. Another unexpected finding is that this study brings new evidence that the number of minors taken by the participants is a negative predictor of their grade in the AEM course. This observation may indicate that course-work from non-major classes may adversely impact their performance in mathematical engineering courses. © Copyright © 2021 Athavale, Mondal and Rivera.

20.
Journal of the Indian Chemical Society ; 97(8):1287-1294, 2020.
Article in English | Web of Science | ID: covidwho-1292451

ABSTRACT

Both, zinc and copper play important roles in human metabolic processes. In humans, zinc (Zn) is required directly for the chemical catalysis and/or maintaining the structure of nearly 10% of total body proteins. It plays a significant role not only in immune defence but also takes part in DNA and protein synthesis, growth and development throughout the life span as well as in tissue repair. On the other hand, copper (Cu) is crucial to strengthen the skin, epithelial tissue, connective tissue and blood vessels. Cu helps to increase the level of haemoglobin, melanin and myelin in our body. Both of these trace metals possess antioxidant like properties. However, it is necessary to balance the optimal concentration of Zn or Cu in blood serum to avoid the associated organ damage. Excess zinc intake increases the incidence of chronic kidney disease (CKD) which is harmful to normal renal function and thus elevated the risk of prostate cancer. Similarly, the one and only reason for heart, kidney and liver failure including Wilson disease is the excess amount of copper. Both of these trace metals are responsible to deal with brain diseases. Thus, there are many "faces" of Zn and Cu in the maintenance of cellular network including immunomodulatory regulation and infection prevention. Zinc appears to inhibit the enzymatic processes of viral protease and polymerase, as well as different physical processes for instance virus attachment, inflammation, and viral uncoating. Ideally, the clinicians should monitor zinc status of the individuals and advice for the supplements when necessary, otherwise deficiency of these micronutrients could lead to the onset of severe secondary diseases.

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