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1.
Medical mycology ; 2022.
Article in English | MEDLINE | ID: covidwho-2008595

ABSTRACT

We describe presenting clinical and imaging manifestations of SARS-CoV-19-associated rhino-oculo-cerebral mucormycosis (ROCM) in a hospital setting during the second wave of SARS-CoV-19 pandemic in India. Data on the presenting manifestations was collected from March 01 to May 31, 2021. Associations between clinical and imaging findings were explored, specifically: (1) the presence or absence of orbital pain and infiltration of superior orbital fissure on imaging;(2) the presence of unilateral facial nerve palsy and pterygopalatine fossa infiltration and geniculate ganglion signal on contrast magnetic resonance imaging and (3) vision loss and optic nerve findings on imaging. Orbital pain was reported by six of 36 subjects. A fixed, frozen eye with proptosis and congestion was documented in 26 (72%), complete vision loss in 23 (64%) and a unilateral lower motor neuron facial nerve palsy in 18 (50%). No association was found between the presence of orbital pain and superior orbital fissure infiltration on imaging. The ipsilateral geniculate ganglion was found to enhance more profoundly in seven out of 11 subjects with facial palsy and available MR imaging, and the ipsilateral pterygopalatine fossa was found infiltrated in 14. Among 23 subjects with complete loss of vision, nine (39%) demonstrated long-segment bright signal in posterior optic nerve on diffusion MR images. We conclude that orbital pain might be absent in SARS-CoV-19-associated ROCM. Facial nerve palsy is more common than previously appreciated and ishaemic lesions of the posterior portion of the optic nerve underlie complete vision loss.

2.
Cureus Journal of Medical Science ; 14(8), 2022.
Article in English | Web of Science | ID: covidwho-2006494

ABSTRACT

Introduction COVID-19 and its mutants have significantly impacted the health care system, claiming numerous lives and adding to the morbidity. The data are scarce to describe the effect of disease severity on pregnancy outcomes, the possibility of mother-to-child transmission, and neonatal outcomes of COVID-positive babies. This study aimed to report the maternal and fetal characteristics of pregnant women with severe COVID disease as well as maternal and neonatal characteristics of neonates with early-onset SARS-CoV-2 infection. Materials and methods This is a prospective data analysis of pregnant women with severe COVID disease and neonates with earlyonset SARS-CoV-2 infection. The disease parameters including demographic data, clinical presentation, investigations, management, and maternal and neonatal outcomes were recorded and analyzed. Results India has faced three waves till now. At the study center, a total of 165 (60, 68, and 37 in the first, second, and third waves, respectively) COVID-positive pregnant women were admitted during all three waves. No severe COVID disease with pregnancy was noted in the first and third waves. During the second wave (March to June 2021), 15 pregnant women were found to have severe COVID disease. All of them had COVID-related symptoms, with the majority requiring supplementary oxygen at presentation. Nine of these women had intrauterine fetal demise at admission. Nearly 73% were in their second trimester, and the rest were in the third trimester. There was raised total leukocyte count and alanine transaminase in 73% and raised aspartate transaminase in all cases. All of them were admitted to the intensive care unit. Two women in their third trimester had a termination of pregnancy by cesarean section, and one of the neonates had early neonatal death due to perinatal asphyxia. Both the neonates were COVID-19 positive. Eleven women with critical illness succumbed to the disease. No neonate was found to have early-onset SAR-CoV-2 infection during the first and third waves. Only 11 neonates tested positive for SARS-CoV-2 at the time of birth during the second wave. None of them had any COVID-related symptoms. Preterm birth was reported in four cases. The average Apgar scores at 1 and 5 minutes were 6.9 and 8.09, respectively. The average birth weight was 2,551.81 grams. All neonates were initially kept in the neonatal intensive care unit. Out of 11, four neonates required treatment in the form of positive-pressure ventilation, chest compressions, high-flow nasal oxygen, and non-invasive and invasive ventilation. Neonatal mortality was documented in two cases. Six mothers had one or more positive results in either amniotic fluid, placental membrane, or vaginal or cervical swab, highlighting the possibility of antepartum or intrapartum transmission. Conclusion Severe COVID disease during pregnancy was associated with high rates of intrauterine fetal demise and maternal mortality. Raised liver enzymes might be taken as a predicting factor for severe disease. On the other hand, early-onset neonatal SARS-CoV-2 infection is mostly asymptomatic and has a good prognosis. Additionally, mother-to-child transmission of SARS-CoV-2 is possible in the antepartum and intrapartum periods.

3.
Gastroenterology ; 162(7):S-1280, 2022.
Article in English | EMBASE | ID: covidwho-1967446

ABSTRACT

Background & Aims: Prior studies have indicated the presence of hepatic inflammation (as signified by elevated liver function test (LFT) values), as conferring an escalated risk toward adverse outcomes in patients admitted with COVID-19. In line with this hypothesis, we study the various thresholds of LFTs and its associated prognostic risks toward COVID- 19 related hospital deaths Method: This was a single-center retrospective study involving patients admitted with COVID-19. Univariate Cox regression analysis identified the LFT variables significantly associated with our primary endpoint, in-hospital death. Subsequently, 500 iterations of thresholds were generated for each biomarker to estimate the prognostic relationship between biomarker and endpoint. Multivariate Cox regression and event-analyses were performed for each threshold to identify the minimal cutoffs at which the prognostic relationship was significant. Event curves were drawn for each significant relationship. Results: A total of 858 patients with COVID-19 were included with a median follow-up time of 5 days from admission. From the total, 90 patients passed away during admission (10.5%). The deceased cases were more likely to be older (66.2 vs 55.3y p<0.001);however, there was no difference in gender (male: 66 vs 56.2% p=0.11). Between the cases and controls (no-death), deceased cases had higher incidence of nonalcoholic fatty liver disease (7.78 vs 2.99% p=0.042), COPD (18.9 vs 7.80% p=0.001), lung cancer (4.44 vs 0.65% p= 0.009), ICU admissions (81.1 vs 26% p<0.001), and intubation events (84.4 vs 19.5% p<0.001), however there was no difference in alcohol use (21.1 vs 30.6% p=0.083) and alcoholic liver disease (5.56 vs 2.08% p=0.097). Upon univariate Cox analysis, the following LFT parameters were associated with in-hospital death: Bilirubin (p<0.001), AST (p<0.001), ALT (p<0.001). However, alkaline phosphatase (p=0.449) was not associated with the primary endpoint. The iterations of event regression analyses using 500 sequences of LFT thresholds showed the following cutoffs to be significantly associated with in-hospital death (minimally significant values): ALT (281.71 IU/L), AST (120.94 IU/L), bilirubin (2.615 mg/ dL). On the multivariate analysis, while controlling for demographics and cardiopulmonary/ medical comorbidities, the following adjusted hazard ratios were derived for each cutoff: ALT (aHR: 6.43 95%CI 1.85-22.40), AST (aHR: 3.35 95%CI 1.84-6.11), and bilirubin (aHR: 2.77 95%CI 1.15-6.65). Conclusion: The delineated cutoffs for AST, ALT, and bilirubin levels can serve as clinical benchmarks to help determine when a COVID-19 infection poses significant risk. Given this finding, the cutoffs can be used as part of a risk assessment for patients to support early preventative therapies and medical management. (Table Presented)

4.
Gastroenterology ; 162(7):S-1279-S-1280, 2022.
Article in English | EMBASE | ID: covidwho-1967445

ABSTRACT

Background and Aims: While the relationship between elevated liver enzymes and COVID- 19 related adverse events is well-established, a liver-dependent prognostic model that predicts the risk of death is helpful to accurately stratify admitted patients. In this study, we use a bootstrapping-enhanced method of regression modeling to predict COVID-19 related deaths in admitted patients. Method: This was a single-center, retrospective study. Univariate and multivariate Cox regression analyses were performed using 30-day mortality as the primary endpoint to establish associated hepatic risk factors. Regression-based prediction models were constructed using a series of modeling iterations with an escalating number of categorical terms. Model performance was evaluated using receiver operating characteristic (ROC) curves. Model accuracy was internally validated using bootstrapping-enhanced iterations. Results: 858 patients admitted to hospital with COVID-19 were included. 78 were deceased by 30 days (9.09%). Cox regression (greater than 20 variables) showed the following core variables to be significant: INR (aHR 1.26 95%CI 1.06-1.49), AST (aHR 1.00 95%CI 1.00- 1.00), age (aHR 1.05 95%CI 1.02-1.08), WBC (aHR 1.07 95%CI 1.03-1.11), lung cancer (aHR 3.38 95%CI 1.15-9.90), COPD (aHR 2.26 95%CI 1.21-4.22). Using these core variables and additional categorical terms, the following model iterations were constructed with their respective AUC;model 1 (core only): 0.82 95%CI 0.776-0.82, model 2 (core + demographics): 0.828 95%CI 0.785-0.828, model 3 (prior terms + additional biomarkers): 0.842 95%CI 0.799-0.842, model 4 (prior terms + comorbidities): 0.851 95%CI 0.809-0.851, model 5 (prior terms + life-sustaining therapies): 0.933 95%CI 0.91-0.933, model 6 (prior terms + COVID-19 medications): 0.934 95%CI 0.91-0.934. Model 1 demonstrated the following parameters at 0.91 TPR: 0.54 specificity, 0.17 PPV, 0.98 NPV. Bootstrapped iterations showed the following AUC for the respective models: model 1: 0.82 95%CI 0.765-0.882, model 2 0.828 95%CI 0.764-0.885, model 3 0.842 95%CI 0.779-0.883, model 4: 0.851 95%CI 0.808-0.914, model 5: 0.933 95%CI 0.901-0.957, model 6: 0.934 95%CI 0.901- 0.961. Conclusion: Model 1 displays high prediction performance (AUC >0.8) in both regression-based and bootstrapping-enhanced modeling iterations. Therefore, this model can be adopted for clinical use as a calculator to evaluate the risk of 30-day mortality in patients admitted with COVID-19. (Table Presented)

5.
4th International Conference on Recent Trends in Computer Science and Technology, ICRTCST 2021 ; : 302-308, 2022.
Article in English | Scopus | ID: covidwho-1909221

ABSTRACT

chronic health risks have risen among young individuals due to several factors such as sedentary lifestyle, poor eating habits, sleep irregularities, environmental pollution, workplace stress etc. The problem seems to be more menacing in the near future, with the exacerbation of lifestyle conditions and unforeseen breakout of pandemics such as COVID-19. One possible solution is thus to design health risk prediction systems which can evaluated some critical features of parameters of the individual and then be able to predict possible health risks. As the data shows large divergences in nature with non-correlated patterns, hence choice of machine learning based methods becomes inevitable to design systems which can analyze the critical factors or features of the data and predict possible risks. This paper presents an ensemble approach for health risk prediction based on the steepest descent algorithm and decision trees. It is observed that the proposed work attains a classification accuracy of 93.72%. A simple graphic user interface has also been created for the ease of use and interaction and for prototype testing. © 2022 IEEE.

6.
1st International Conference on Computing, Communication and Green Engineering, CCGE 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1901432

ABSTRACT

Indian m-health app Aarogya Setu has made a significant contribution in terms of contactability tracing and disease management during the initial days of the COVID-19 pandemic, with its contact tracking approach to infectious individuals and its health tips for eliminating new coronaviruses. The goal of this study is to forecast whether or not Indian consumers will continue to use this app. According to previous studies, the context or setting has a substantial impact on the customer's perceived value. The current study's unique setting is to investigate the parameters impacting Indians' ongoing use of the mobile mHealth app AarogyaSetu. An extended technology adoption model (TAM) has been proposed and tested to achieve this wide goal, with the addition of three additional constructs: social influence, health consciousness, and trust in the app developer. © 2021 IEEE.

7.
Benchmarking ; 2022.
Article in English | Scopus | ID: covidwho-1891297

ABSTRACT

Purpose: This study aims to identify how ICT appeared as an emergent business strategy and to investigate the impact of ICT adoption factors on the perceived benefits of micro, small and medium enterprises (MSMEs). Design/methodology/approach: A total of 393 responses from Indian small and mid-size enterprises (SMEs) were collected for the final analysis. The study presents the partial least-squares structural equation modeling with the Chi-square test and descriptive analysis as a methodology based on numerous independent variables and one dependent variable. Findings: The findings indicate that ICT adoption during and following the COVID-19 pandemic is constant in nature of the enterprise. Moreover, the results indicate that different adoption of ICT factors influence on perceived benefits of organizational performance of Indian MSMEs that lent good support except for the regulatory framework. Research limitations/implications: The implications of the current research help Indian MSMEs to take investment decisions in various technologies that help the organization. Furthermore, managers and practitioners help the organization in deciding which technology adoption factors are more critical to the betterment of the organization. Originality/value: The study found certain ICT adoption factors that have a significant role in organizational performance in Indian MSMEs. Moreover, during COVID-19, investigate ICTs' role as a business strategy. © 2022, Emerald Publishing Limited.

8.
American Journal of Respiratory and Critical Care Medicine ; 205:1, 2022.
Article in English | English Web of Science | ID: covidwho-1880968
9.
1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021 ; 107:7703-7711, 2022.
Article in English | Scopus | ID: covidwho-1874814

ABSTRACT

Covid-19 has thrown a lot of challenges to address the gaps in our existing healthcare ecosystem, especially in the remote areas, where providing quality healthcare services is a challenge. Digital healthcare or the internet of medical things(IOMD) is viewed as a new age weapon to provide healthcare services to the masses at an affordable price. One such way is by connecting the end-user with physicians through mobile applications or devices, however, this demands thorough research and validation to understand the underlying needs of the users and physicians interacting in this connected eco-system Through this study, we intend to probe and analyze the role of user interaction and user experience (UI/UX) in discovering the features and services provided through connected devices and mobile applications and their subsequent usage over a prolonged period of time. This study aims to present a theoretical framework utilizing the UTAUT-2 framework to hypnotize the identified problem statement. © The Electrochemical Society

10.
Journal of Global Operations and Strategic Sourcing ; : 27, 2022.
Article in English | Web of Science | ID: covidwho-1822014

ABSTRACT

Purpose COVID-19 pandemic has exposed that even the best of the developed nations have surrendered to the devastations imposed on the global supply chains. The purpose of this study is to explore how COVID-19 has exaggerated the supply chain of production and distribution of Taiwan-based face masks and also investigate the conscientious factors and subfactors for it. Design/methodology/approach In this study, an analytical hierarchy processes (AHP)-based approach has been used to assign the criterion weights and to prioritize the responsible factors. Initially, based on 26 decision-makers, successful factors were categorized into five main categories, and then main categories and their subcategories factors were prioritized through individual and group decision-maker's contexts by using the AHP approach. Findings The results of this AHP model suggest that "Safety" is the most important and top-ranked factor, followed by production, price, work environment and distribution. The key informers in this study are stakeholders which consist of managers, volunteers, associations and non-governmental organizations. The results showed that good behavior of the employees under the "Safety" category is the top positioned responsible factor for successful production and distribution of face masks to the other countries with the highest global percentage of 15.7% and using sanitizers to protect health is the second most successful factor with the global percentage of 11.7%. Research limitations/implications The limitations faced in this study were limited to only Taiwan-based mask manufacturing companies, and it was dependent on the decisions of the limited company's decision-makers. Originality/value The novelty of this study is that the empirical analysis of this study has been based on a successful Taiwan masks manufacturing company and evaluates the responsible factors for the production and distribution of Taiwan masks to other countries during COVID-19.

11.
European Urology ; 79:S1388, 2021.
Article in English | EMBASE | ID: covidwho-1747409

ABSTRACT

Introduction & Objectives: The current coronavirus disease 2019 (COVID-19) pandemic is creating huge pressure on our health care systems and has led to dramatic changes in our daily lives. Many countries have enforced strict controls on movement and socializing in an effort to manage the pandemic. Both, in-patient and out-patient care has been affected. There is big gap between health care service providers and patients and because of that many people are suffering. But telemedicine appears to be only bridge between them so that patients can get maximum benefit from the experts. This study is being conducted to know the worth of telemedicine in urology during ongoing COVID pandemic and for future prospect. Materials & Methods: All the patients who made a call on telemedicine contact number of department of urology of our tertiary care hospital and took advice for their treatment or follow up from April 2020 to December 2020, were included in this prospective observational study. Patients contacted us through various modalities like Voice/video call, WhatsApp chat, messages. Patients who contacted us for non-urological problem were excluded. All calls were answered by Professional Urologist and advice was given verbally as well as sent them in written on a prescription slip through WhatsApp. Data collection included age, sex, place, symptoms and advice given. Results: During the study period, we received 1102 calls from the patients of North India, 124 patients were excluded for being non-urological and 978 patients were included. 94% patients contacted us through voice call, 4% through video call and 2% through chat only. Average duration of call was 16 minutes and 25 seconds. 68% patients were males, while 32% females. 54% patients were younger than 40 years and only 15% were elder than 60 years. Common reasons for calling us were- urinary tract infection (23%), lower urinary tracts symptoms (21%), renal stone disease (17%), haematuria (11%), post-operated cases (11%) and sexual problems (7%). Approximately 16% patients had some urological malignancy. Only 18% patients contacted us for acute illness of duration <1 week, while 47% patients were sick for >4 weeks. 18% patients needed only counselling for their disease, 65% required prescription and conservative management. 17% patients were requiring in-hospital management so referred to nearby urological center for urgent intervention or care. None of the patients had any problem in getting medications from pharmacy. Conclusions: Telemedicine provides specialized clinical support for urologists and patients just by using mobile phones, as a logistically feasible alternative to face-to-face consultation. 83% of cases were successfully managed just by telemedicine and very useful for reducing the risk of transmission of COVID-19 infection. This novel way of urological practice should be continued in future to reduce unnecessary visits to medical facilities even after this pandemic.

12.
European Urology ; 81:S135-S136, 2022.
Article in English | EMBASE | ID: covidwho-1747406

ABSTRACT

Introduction & Objectives: Patients are often given printed information leaflets as part of informed consent for a procedure or explanation of their condition. Challenges of the COVID-19 pandemic and restrictions on face-to-face (F2F) consultations have required alternative methods ofdistributing information. We evaluated frequency of patient information leaflet use;preliminary cost benefit of electronic methods;and effectivenessof using QR codes to access digital leaflets.Materials & Methods: An international online survey of Urologists was distributed, and leaflet costs were estimated. QR codes were generated forcommonly used British Association of Urological Surgeons (BAUS) patient information leaflets and were incorporated into a poster for display in theoutpatient department. Evaluation of poster use was sought from patients through a questionnaire.(Figure Presented)Results: 108 Urologists responded to the initial survey, 44% of whom were Consultant grade. 54% provided >50% of patients with an information leaflet during F2F clinics. During transition to telephone clinics, this fell to 33% during the COVID-19 pandemic. Instead, 47% patients were provided with an internet link or directed to search engine terms in the clinical letter, instead of a printed leaflet. In a F2F clinic, each leaflet costs 40p to print, using a departmental model of 25 clinics/week, each clinician seeing 12 patients, if 53% receive a leaflet, the cost saving could be £3,307per year. In response to the QR codes poster for digital provision of patient leaflets, in a patient population mostly male (82%) and older (60%between 60-80 years), 40% were familiar with QR codes and 73% could access the internet on a personal smartphone. 53% reporting using theirsmartphone to find information, 46% found the poster easy to use or follow, and 61% found it informative.Conclusions: Patient information leaflets are important for a Urologists’ practice, frequently distributed, and printed forms can be costly. Providingpaperless digital leaflets via a QR code offers many benefits including being cost-effective, touch-free, was well received by patients and haspotential to increase patient engagement and education. Patient perception varies with age group and smartphone usage, therefore may not besuitable for all patient groups. This use of QR codes to provide direct access to digital patient information can be easily applied to other societiesand specialties

13.
5th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2021 ; : 12-16, 2021.
Article in English | Scopus | ID: covidwho-1728828

ABSTRACT

Pneumonia is life-threatening. It's critical for infants, young children, elders, and people with health problems or enfeebles immune systems. However, someone who has been infected with coronavirus can get intense Pneumonia in each lung. The best way to stumble on Pneumonia is via chest X-ray. Radiotherapist is required for an examination of chest X-Ray. An automated pneumonia detection device would be helpful for early detection in far-off places. The proposed method makes it possible to train ViT models with enhanced performance. Nowadays, ViT is an alternative method of CNN in the field of computer vision. In this research, three models have been proposed, namely convolutional neural network (CNN), VGG16, and Visual Transformer were constructed. Statistical results are obtained after the comparison of all three models. Results indicate that ViT can identify Pneumonia with an accuracy of 96.45%. And also can be used to recognize other lung-related diseases. All the models were trained and tested on a dataset that contains standard chest X-Rays and pneumonia chest X-Rays. © 2021 IEEE.

14.
Information Discovery and Delivery ; 49(3):193-202, 2021.
Article in English | Web of Science | ID: covidwho-1691709

ABSTRACT

Purpose - Using data from Twitter, the purpose of this paper is to assess the coping behaviour and reactions of social media users in response to the initial days of the COVID-19-related lockdown in different parts of the world. Design/methodology/approach - This study follows the quasi-inductive approach which allows the development of pre-categories from other theories before the sampling and coding processes begin, for use in those processes. Data was extracted using relevant keywords from Twitter, and a sample was drawn from the Twitter data set to ensure the data is more manageable from a qualitative research standpoint and that meaningful interpretations can be drawn from the data analysis results. The data analysis is discussed in two parts: extraction and classification of data from Twitter using automated sentiment analysis;and qualitative data analysis of a smaller Twitter data sample. Findings - This study found that during the lockdown the majority of users on Twitter shared positive opinions towards the lockdown. The results also found that people are keeping themselves engaged and entertained. Governments around the world have also gained support from Twitter users. This is despite the hardships being faced by citizens. The authors also found a number of users expressing negative sentiments. The results also found that several users on Twitter were fence-sitters and their opinions and emotions could swing either way depending on how the pandemic progresses and what action is taken by governments around the world. Research limitations/implications - The authors add to the body of literature that has examined Twitter discussions around H1N1 using in-depth qualitative methods and conspiracy theories around COVID-19. In the long run, the government can help citizens develop routines that help the community adapt to a new dangerous environment - this has very effectively been shown in the context of wildfires in the context of disaster management. In the context of this research, the dominance of the positive themes within tweets is promising for policymakers and governments around the world. However, sentiments may wish to be monitored going forward as large-spikes in negative sentiment may highlight lockdown-fatigue. Social implications - The psychology of humans during a pandemic can have a profound impact on how COVID-19 shapes up, and this shall also include how people behave with other people and with the larger environment. Lockdowns are the opposite of what societies strive to achieve, i.e. socializing. Originality/value - This study is based on original Twitter data collected during the initial days of the COVID-19-induced lockdown. The topic of "lockdowns" and the "COVID-19" pandemic have not been studied together thus far. This study is highly topical.

15.
Indian Journal of Hematology and Blood Transfusion ; 37(SUPPL 1):S107-S108, 2021.
Article in English | EMBASE | ID: covidwho-1635524

ABSTRACT

Introduction: The incidence of COVID-19 is remarkably less in thepaediatric population as compared to the adult population, withchildren accounting for 1-5% of diagnosed cases. Data in childrenregarding the spectrum of haematological manifestations and thecorrelation with prognosis is limited. Aims &Objectives: To describe the haematological manifestationsand peripheral smear findings of SAR-CoV-2 infection in COVID-19positive symptomatic children and to study the association betweendifferent haematological parameters with patient age, disease severity, and patient outcomes.Materials &Methods: A retrospective cum prospective review of thehaematological parameters and peripheral smear findings of thechildren diagnosed with COVID-19 positive status over four monthswas conducted in the Department of Pathology, Maulana AzadMedical College from September 2020 to December 2020. Allsymptomatic paediatric patients less than 18 years of age, with laboratory-confirmed SARS-CoV-2 (severe acute respiratory syndromecoronavirus-2) infection were included. Complete blood count andperipheral smear findings were reviewed and a comparison of theproportion of children with abnormal hematological parametersacross various age groups and different disease severity (mild, moderate, and severe) was done. The data obtained were analyzed usingMS Excel and Statistical Package for the Social Sciences (SPSS)software, version 26. Prior approval of the institutional ethical committee was taken.Result: Seventy-two SARS-CoV-2 proven infection (RT-PCR positive) cases were included ranging in age from 2 days to 18 years.Anaemia was the most common haematological abnormality (62.5%)followed by leucopoenia (21%). Lymphopenia and neutropenia wereseen in 18% of cases respectively. Leucocytosis was seen in 10% ofcases with raised neutrophil to leucocyte ratio (NLR) seen in 30.Conclusions: Children have milder disease outcomes and a lesserdegree of haematological changes than adults. This can be attributedto a better immune response in otherwise healthy children. Howeverlarger studies are required for further understanding of paediatricpopulation outcomes.

16.
2nd Global Conference for Advancement in Technology, GCAT 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1537709

ABSTRACT

As far as, air quality index (AQI) is concerned, the long duration lockdown that was applied in India in year 2020 due to Covid-19 pandemic was very fruitful. The reason being, due to complete ban on the movement of people and automobiles, the air became so pure and clean, and AQI value went much down. The secondary air pollution data of the lockdown duration, for Uttarakhand, is the base of this research work. This work attempts to design unsupervised and supervised classification models to classify the provided data into two classes i.e class 1 ('clean') and class 2 ('hazardous') using MATLAB. The techniques used are FCM clustering and Probabilistic neural network (PNN). Eventually, a comparative study of the performance of both models is performed. © 2021 IEEE.

17.
Engineering, Construction and Architectural Management ; 2021.
Article in English | Scopus | ID: covidwho-1470231

ABSTRACT

Purpose: This study identifies the facilitators and inhibitors for the adoption of e-learning for the undergraduate students of architecture. Nine constructs are identified as facilitators and five constructs are identified as inhibitors to the adoption of online learning systems in the context of the study. These constructs were used to propose a research model. Design/methodology/approach: 596 architecture undergraduates responded to a structured questionnaire. The questionnaire was finalized after a pilot study and included standard scale items drawn from previous studies. An exploratory factor analysis was followed by structural equation modeling (SEM) to test the proposed model. Findings: All the identified facilitators emerged significant except social influence and price value. Furthermore, technology risk emerged insignificant while all other inhibitors had significant impact on Behavioral Intention to adopt e-learning. Research limitations/implications: The study has strong implications in academia as HEIs in developing countries need to make their students computer proficient, boost the implications of e-learning services by mitigating risks and motivating students to acquire knowledge through flexible e-learning modules. Originality/value: The COVID-19 pandemic forced educational institutions to switch to online modes of learning. For students of architectural programs in a developing country like India, this has been unprecedented and has brought in a new set of challenges and opportunities. With the extension of the pandemic induced lockdown in educational institutions, students – and other stakeholders – have no choice but to adapt to this new normal of dependence on remote learning. © 2021, Emerald Publishing Limited.

18.
Journal of Cardiovascular Disease Research ; 12(5):61-68, 2021.
Article in English | EMBASE | ID: covidwho-1417511

ABSTRACT

Background: The ongoing pandemic has highlighted the need for an effective treatment of COVID-19 patients and prevention of SARS-CoV-2 community transmission.Methods: We conducted a prospective observational study on a cohort of 85 COVID-19 patients (80% males, median age 46 years, range 18–80 years). Patients were treated with a triple drug therapy: ivermectin 12 mg once a week, hydroxychloroquine 400 mg twice a day on the first day and 200 mg twice a day for the next 4 days, and azithromycin 500 mg once a day for 5 days. Endpoints were assessed by clinical outcomes, death, negative SARS-CoV-2 RNA-PCR test on the tenth day, and length of the hospital stay.Results: All patients improved except one 70-year-old female, who died on the third day of admission. The clinical outcome was considered good as 95.24% (80/84) of patients presented a negative SARS-CoV-2 RNA-PCR test on the tenth day of admission and 90.48% (76/84) were discharged in stable condition.Conclusions: The response must focus on immediate isolation of COVID-19 patients and their early treatment to prevent irreversible severe respiratory injury. Our study shows the beneficial effect of triple drug therapy in terms of clinical recovery, shorter duration of viral carriage, community spread prevention, and minimal cost of therapy.

19.
6th IEEE International Conference on Communication and Electronics Systems, ICCES 2021 ; : 255-261, 2021.
Article in English | Scopus | ID: covidwho-1393703

ABSTRACT

The lockdown duration of COVID-19 gave rise to a significant betterment in AQI (Air Quality Index) worldwide. In the present research paper, binary classification problem of the air pollutants data of Uttarakhand, India, for year 2019 and 2020 (lockdown period), has been addressed. This problem is challenging to solve as it is non-linearly separable. Using this data, a neural network has been trained, to perform classification, using competitive learning technique (unsupervised learning). Then, for achieving better classification results, a supervised learning technique, learning vector quantization algorithm (LVQ), is used. Finally, the performance of both the networks is compared. All results are obtained in MATLAB. © 2021 IEEE.

20.
Journal of the Indian Medical Association ; 119(5):86, 2021.
Article in English | EMBASE | ID: covidwho-1357939

ABSTRACT

Wound Care is very important in this COVID-19 pandemic. The factors associated with poor prognosis from COVID-19 which increase the risk for chronic wounds are older age, hypertension, chronic lung disease, diabetes and obesity. Patient prioritization is a key aspect while treating wounds in patients with COVID-19 infection. Telemedicine is a supportive alternative for clinic visits and need to create awareness about use of telemedicine among the patients. The patients should be encouraged and educated about the basics of hygiene and wound care prevention.

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