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1.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-332865

ABSTRACT

ABSTRACT SARS-CoV-2, responsible for the COVID-19 pandemic, causes respiratory failure and damage to multiple organ systems. The emergence of viral variants poses a risk of vaccine failures and prolongation of the pandemic. However, our understanding of the molecular basis of SARS-CoV-2 infection and subsequent COVID-19 pathophysiology is limited. In this study, we have uncovered a critical role for the evolutionarily conserved Hippo signaling pathway in COVID-19 pathogenesis. Given the complexity of COVID-19 associated cell injury and immunopathogenesis processes, we investigated Hippo pathway dynamics in SARS-CoV-2 infection by utilizing COVID-19 lung samples, and human cell models based on pluripotent stem cell-derived cardiomyocytes (PSC-CMs) and human primary lung air-liquid interface (ALI) cultures. SARS-CoV-2 infection caused activation of the Hippo signaling pathway in COVID-19 lung and in vitro cultures. Both parental and Delta variant of concern (VOC) strains induced Hippo pathway. The chemical inhibition and gene knockdown of upstream kinases MST1/2 and LATS1 resulted in significantly enhanced SARS-CoV-2 replication, indicating antiviral roles. Verteporfin a pharmacological inhibitor of the Hippo pathway downstream transactivator, YAP, significantly reduced virus replication. These results delineate a direct antiviral role for Hippo signaling in SARS-CoV-2 infection and the potential for this pathway to be pharmacologically targeted to treat COVID-19.

2.
Journal of family medicine and primary care ; 10(12):4483-4488, 2021.
Article in English | EuropePMC | ID: covidwho-1733309

ABSTRACT

Introduction: The COVID-19 Pandemic has caused anxiety and stress among people. Nursing students, being an important link in the delivery of health care services, are always exposed to stressful situations which in turn put a great toll on their mental health. Moreover, the perceived risk of pandemics motivates people to embrace different protective measures so as to reduce any potential threats of an emerging health concern. Objective: The aim of this study was to assess the COVID-induced anxiety and protective behaviors among nursing students. Methods: Nursing students studying at 02 nursing institutes of Jodhpur, Rajasthan, India were enrolled for the study. The data were collected using COVID-induced anxiety scale and protective behaviors towards COVID-19 Scale. These scales were converted to online google forms, and the link was circulated among 370 nursing students through emails and WhatsApp. A total of 229 students submitted their responses within stipulated time and were included in the final data analysis. Results: The response rate of the survey was 62%. Evidently, nursing students had a moderate level of anxiety (mean score 31.28 ± 5.29) due to the COVID-19 outbreak. Overall protective behavior mean score was 56.63 ± 6.4 which reflects that students were following higher quality of protective behaviors. There is a negative linear correlation between anxiety score and protective behavior score. Conclusion: The nursing students exhibited a moderate level of anxiety, and routing protective behaviors were frequently performed by these students. There is a timely need to plan and implement interventions for nursing students so as to make them self-capable to resolve psychosocial issues, especially during disease outbreaks.

3.
J Family Med Prim Care ; 11(1): 118-122, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1726355

ABSTRACT

Background: Asymptomatic carriers are responsible for the consistent spread of coronavirus disease 2019 (COVID-19) in the community. The Government of India has deputed house-to-house survey teams to aid in identifying asymptomatic individuals and their susceptible contacts. We selected door-to-door survey teams of a COVID-19 red zone in western India and determined their infectioncontrol practices and anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoglobin G (IgG) status. Materials and Methods: This single-day prospective cross-sectional study was conducted by the Department of Microbiology of a tertiary care hospital of Jodhpur, in collaboration with the Rajasthan State Health Services. Participants were asked to fill out a questionnaire regarding personal protective equipment (PPE) use after written informed consent. Venous blood samples were collected and Kavach enzyme-linked immunosorbent assay (ELISA) (J Mitra and Co.) was performed to determine anti-SARS-CoV-2 IgG status. Results: Out of the total 39 participants, IgG antibody was detected in four. Of them, three reported mild symptoms in the past. Out of two previously real-time polymerase chain reaction (RT-PCR) SARS-CoV-2-positive participants, only one had detectable IgG antibodies (Ab) in serum. Cloth mask was used by 24, N95 mask by 11, and surgical masks by four. Conclusion: Anti-SARS-CoV-2 IgG Abs were detected among four members of house-to-house COVID-19 survey teams in Jodhpur. Most of the team members used cloth masks, whereas the Government of India guidelines has recommended triple-layered surgical masks as minimum essential PPE for healthcare workers in India. More such studies should be conducted to ascertain infection prevention and control practices among such vulnerable frontline workers in our country.

4.
Budhiraja, Sandeep, Tarai, Bansidhar, Jain, Dinesh, Aggarwal, Mona, Indrayan, Abhaya, Das, Poonam, Mishra, R. S.; Bali, Supriya, Mahajan, Monica, Kirtani, Jay, Tickoo, Rommel, Soni, Pankaj, Nangia, Vivek, Lall, Ajay, Kishore, Nevin, Jain, Ashish, Singh, Omender, Singh, Namrita, Kumar, Ashok, Saxena, Prashant, Dewan, Arun, Aggarwal, Ritesh, Mehra, Mukesh, Jain, Meenakshi, Nakra, Vimal, Sharma, B. D.; Pandey, Praveen Kumar, Singh, Y. P.; Arora, Vijay, Jain, Suchitra, Chhabra, Ranjana, Tuli, Preeti, Boobna, Vandana, Joshi, Alok, Aggarwal, Manoj, Gupta, Rajiv, Aneja, Pankaj, Dhall, Sanjay, Arora, Vineet, Chugh, Inder Mohan, Garg, Sandeep, Mittal, Vikas, Gupta, Ajay, Jyoti, Bikram, Sharma, Puneet, Bhasin, Pooja, Jain, Shakti, Singhal, R. K.; Bhasin, Atul, Vardani, Anil, Pal, Vivek, Pande, Deepak Gargi, Gulati, Tribhuvan, Nayar, Sandeep, Kalra, Sunny, Garg, Manish, Pande, Rajesh, Bag, Pradyut, Gupta, Arpit, Sharma, Jitin, Handoo, Anil, Burman, Purabi, Gupta, Ajay Kumar, Choudhary, Pankaj Nand, Gupta, Ashish, Gupta, Puneet, Joshi, Sharad, Tayal, Nitesh, Gupta, Manish, Khanna, Anita, Kishore, Sachin, Sahay, Shailesh, Dang, Rajiv, Mishra, Neelima, Sekhri, Sunil, Srivastava, Dr Rajneesh Chandra, Agrawal, Dr Mitali Bharat, Mathur, Mohit, Banwari, Akash, Khetarpal, Sumit, Pandove, Sachin, Bhasin, Deepak, Singh, Harpal, Midha, Devender, Bhutani, Anjali, Kaur, Manpreet, Singh, Amarjit, Sharma, Shalini, Singla, Komal, Gupta, Pooja, Sagar, Vinay, Dixit, Ambrish, Bajpai, Rashmi, Chachra, Vaibhav, Tyagi, Puneet, Saxena, Sanjay, Uniyal, Bhupesh, Belwal, Shantanu, Aier, Imliwati, Singhal, Mini, Khaduri, Ankit.
IJID Regions ; 2022.
Article in English | ScienceDirect | ID: covidwho-1708321

ABSTRACT

Objective : To get better insights into the extent of secondary bacterial and fungal infections in Indian hospitalized patients and to assess how these alter the course of COVID-19 so that the control measures can be suggested. Methods : This is a retrospective, multicentre study where data of all RT-PCR positive COVID-19 patients was accessed from Electronic Health Records (EHR) of a network of 10 hospitals across 5 North Indian states, admitted during the period from March 2020 to July 2021. Results : Of 19852 RT-PCR positive SARS-CO2 patients admitted during the study period, 1940 (9.8%) patients developed SIs. Patients with SIs were 8 years older on average (median age 62.6 years versus 54.3 years;P<0.001) than those without SIs. The risk of SIs was significantly (p < 0.001) associated with age, severity of disease at admission, diabetes, ICU admission, and ventilator use. The most common site of infection was urinary tract infection (UTI) (41.7%), followed by blood stream infection (BSI) (30.8%), sputum/BAL/ET fluid (24.8%), and the least was pus/wound discharge (2.6%). Gram negative bacilli (GNB) were the commonest organisms (63.2%), followed by Gram positive cocci (GPC) (19.6%) and fungus (17.3%). Most of the patients with SIs were on multiple antimicrobials – the most used were the BL-BLI for GNBs (76.9%) followed by carbapenems (57.7%), cephalosporins (53.9%) and antibiotics carbapenem resistant Enterobacteriaceae (47.1%). The usage of empirical antibiotics for GPCs was in 58.9% and of antifungals in 56.9% of cases, and substantially more than the results obtained by culture. The average stay in hospital for patients with SIs was almost twice than those without SIs (median 13 days versus 7 days). The overall mortality in the group with SIs (40.3%) was more than 8 times of that in those without SIs (4.6%). Only 1.2% of SI patients with mild COVID-19 at presentation died, while 17.5% of those with moderate disease and 58.5% of those with severe COVID-19 died (P< 0.001). The mortality was the highest in those with BSI (49.8%), closely followed by those with HAP (47.9%), and then UTI and SSTI (29.4% each). The mortality in diabetic patients with SIs was 45.2% while in non-diabetics it was 34.3% (p < 0.001). Conclusions : Secondary bacterial and fungal infections complicate the course of COVID-19 hospitalised patients. These patients tend to have a much longer stay in hospital, higher requirement for oxygen and ICU care, and significantly high mortality. The group most vulnerable to this complication are those with more severe COVID-19 illness, elderly, and diabetic patients. Judicious empiric use of combination antimicrobials in this set of vulnerable COVID-19 patients can save lives. It is desirable to have a region or country specific guidelines for appropriate use of antibiotics and antifungals to prevent their overuse.

5.
Adv Respir Med ; 2022 Feb 24.
Article in English | MEDLINE | ID: covidwho-1705404

ABSTRACT

INTRODUCTION: Health care workers (HCWs) are directly involved in processes linked with diagnosis, management, and assistance of coronavirus disease-19 (COVID-19) patients which could have direct implications on their physical and emotional health. Emotional aspects of working in an infectious pandemic situation is often neglected in favour of the more obvious physical ramifications. This single point assessment study aimed to explore the factors related to stress, anxiety and depression among HCWs consequent to working in a pandemic. MATERIAL AND METHODS: This was a cross-sectional study involving healthcare workers who were working in COVID-19 inpatient ward, COVID-19 screening area, suspect ward, suspect intensive care unit (ICU) and COVID-19 ICU across four hospitals in India. A web-based survey questionnaire was designed to elicit responses to daily challenges faced by HCWs. The questionnaire was regressed using machine-learning algorithm (Cat Boost) against the standardized Depression, Anxiety and Stress Scale - 21 (DASS 21) which was used to quantify emotional distress experienced by them. RESULTS: A total of 156 participants were included in this study. As per DASS-21 scoring, severe stress was seen in ∼17% of respondents. We could achieve an R² of 0.28 using our machine-learning model. The major factors responsible for stress were decreased time available for personal needs, increasing age, being posted out of core area of expertise, setting of COVID-19 care, increasing duty hours, increasing duty days, marital status and being a resident physician. CONCLUSIONS: Factors elicited in this study that are associated with stress in HCWs need to be addressed to provide wholesome emotional support to HCWs battling the pandemic. Targeted interventions may result in increased emotional resilience of the health-care system.

6.
Ocular Surgery News ; 40(3):17-17, 2022.
Article in English | CINAHL | ID: covidwho-1695797
7.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-325790

ABSTRACT

Background and Objective: Artificial intelligence (AI) methods coupled with biomedical analysis has a critical role during pandemics as it helps to release the overwhelming pressure from healthcare systems and physicians. As the ongoing COVID-19 crisis worsens in countries having dense populations and inadequate testing kits like Brazil and India, radiological imaging can act as an important diagnostic tool to accurately classify covid-19 patients and prescribe the necessary treatment in due time. With this motivation, we present our study based on deep learning architecture for detecting covid-19 infected lungs using chest X-rays. Dataset: We collected a total of 2470 images for three different class labels, namely, healthy lungs, ordinary pneumonia, and covid-19 infected pneumonia, out of which 470 X-ray images belong to the covid-19 category. Methods: We first pre-process all the images using histogram equalization techniques and segment them using U-net architecture. VGG-16 network is then used for feature extraction from the pre-processed images which is further sampled by SMOTE oversampling technique to achieve a balanced dataset. Finally, the class-balanced features are classified using a support vector machine (SVM) classifier with 10-fold cross-validation and the accuracy is evaluated. Result and Conclusion: Our novel approach combining well-known pre-processing techniques, feature extraction methods, and dataset balancing method, lead us to an outstanding rate of recognition of 98% for COVID-19 images over a dataset of 2470 X-ray images. Our model is therefore fit to be utilized in healthcare facilities for screening purposes.

8.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-322332

ABSTRACT

Background: Time-series forecasting has a critical role during pandemics as it provides essential information that can lead to abstaining from the spread of the disease. The novel coronavirus disease, COVID-19, is spreading rapidly all over the world. The countries with dense populations, in particular, such as India, await imminent risk in tackling the epidemic. Different forecasting models are being used to predict future cases of COVID-19. The predicament for most of them is that they are not able to capture both the linear and nonlinear features of the data solely. Methods: : We propose an ensemble model integrating an autoregressive integrated moving average model (ARIMA) and a nonlinear autoregressive neural network (NAR). ARIMA models are used to extract the linear correlations and the NAR neural network for modeling the residuals of ARIMA containing nonlinear components of the data. Comparison : Single ARIMA model, ARIMA-NAR model and few other existing models which have been applied on the COVID-19 data in different countries are compared based on performance evaluation parameters. Result: The hybrid combination displayed significant reduction in RMSE(16.23%), MAE(37.89%) and MAPE (39.53%) values when compared with single ARIMA model for daily observed cases. Similar results with reduced error percentages were found for daily reported deaths and cases of recovery as well. RMSE value of our hybrid model was lesser in comparison to other models used for forecasting COVID-19 in different countries. Conclusion: Results suggested the effectiveness of the new hybrid model over a single ARIMA model in capturing the linear as well as nonlinear patterns of the COVID-19 data.

9.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-319310

ABSTRACT

Time series forecasting methods play critical role in estimating the spread of an epidemic. The coronavirus outbreak of December 2019 has already infected millions all over the world and continues to spread on. Just when the curve of the outbreak had started to flatten, many countries have again started to witness a rise in cases which is now being referred as the 2nd wave of the pandemic. A thorough analysis of time-series forecasting models is therefore required to equip state authorities and health officials with immediate strategies for future times. This aims of the study are three-fold: (a) To model the overall trend of the spread;(b) To generate a short-term forecast of 10 days in countries with the highest incidence of confirmed cases (USA, India and Brazil);(c) To quantitatively determine the algorithm that is best suited for precise modelling of the linear and non-linear features of the time series. The comparison of forecasting models for the total cumulative cases of each country is carried out by comparing the reported data and the predicted value, and then ranking the algorithms (Prophet, Holt-Winters, LSTM, ARIMA, and ARIMA-NARNN) based on their RMSE, MAE and MAPE values. The hybrid combination of ARIMA and NARNN (Nonlinear Auto-Regression Neural Network) gave the best result among the selected models with a reduced RMSE, which proved to be almost 35.3% better than one of the most prevalent method of time-series prediction (ARIMA). The results demonstrated the efficacy of the hybrid implementation of the ARIMA-NARNN model over other forecasting methods such as Prophet, Holt Winters, LSTM, and the ARIMA model in encapsulating the linear as well as non-linear patterns of the epidemical datasets.

10.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-309836

ABSTRACT

Background: Health care personnel (HCP) are at an increased risk of acquiring COVID infection during this pandemic especially in developing countries like India, where they work in resource restricted healthcare settings and return to homes, unfit for safe self-isolation. Thus, many HCP were reluctant to accept COVID-19 duty as they were apprehensive about their safety and concerned about carrying the infection home to their families.Methods: We describe a novel multidimensional HCP-centric evidence-based, dynamic policy to address the expressed concerns of HCPs. The hospital was divided into three zones: high, medium, and low risk zones. In the high risk and medium risk zones, we organized pre-duty holistic training, provided on-duty support, ensured post duty HCP welfare, and send them all home after they tested negative for COVID-19. To minimize transmission, we provided appropriate PPE, ensured its proper use, kept all communication paperless. To reduce morbidity, we recruited only willing low risk HCP, aged <50 years, with no co-morbidities to perform duty in high risk zones. Social distancing, hand hygiene and universal masking were advocated in the low risk zone.Findings: Between 31st March-20th July 2020, we clinically screened 5553 outpatients, of whom 3012 (54.2%) were COVID suspects and they were kept in the medium risk zone. Among them, 346(11.4%) were COVID+ve (57.2% male) and managed in the high-risk zone of whom 19(5.4%) died. One ( 0.08%) of the 1224 HCP in high-risk zone tested positive;6(0.62%) of the 960 HCP in medium risk zone and 23(0.18%) of the 12600 HCP in the low risk zone. All the 30 COVID +ve HCP have since recovered and none were critically ill.This multidimensional HCP centric policy resulted in very low transmission rates <1%, low morbidity, high satisfaction rates with training (92%), the PPE provided(90.8%), medical and psychosocial support received (79%) and with improved acceptance of COVID duty with over 54.7% now volunteering for re-deployment.Interpretation: A multidimensional HCP centric policy was effective in ensuring safety, satisfaction, and welfare of HCP in a resource poor setting and resulted in a willing workforce to fight the pandemic.Funding Statement: None.Declaration of Interests: None of the authors has any conflict of interest to declare.Ethics Approval Statement: Ethical clearance for reporting the results of our HCP protocol and feedback was taken from the Institutional Ethics Committee (Letter No INT/IEC/2020/SPL997;Dated 25.07.2020) and the need for individual informed consent was waived. This retrospective study was conducted in accordance with the Declaration of Helsinki and ICMR guidelines.

11.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-309161

ABSTRACT

COVID-19 is an infectious disease, growth of which depends upon the linked stages of the epidemic, the average number of people one person can infect and the time it takes for those people to become infectious themselves. We have studied the COVID-19 time series to understand the growth behaviour of COVID-19 cases series. A structural break occurs in the COVID-19 series at the change time form one stage to another. We have performed the structural break analysis of data available for 207 countries till April 20, 2020. There are 42 countries which have recorded five breaks in COVID cases series. This means that these countries are in the sixth stage of growth transmission and show a downward pattern in reporting in the daily cases, whereas countries with two and three breaks, record the rapid growth pattern in the daily cases. From this study, we conclude that the more the breaks in the series, there is more possibility to determine the constant or decreasing rate of daily cases. It is well fitted using lognormal distribution as this distribution is archived at its highest peak after some period and then suddenly it decreases at a longer time period. This can be seen in various countries like China, Australia, New Zealand and so on.

12.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-305835

ABSTRACT

The Randomized Embedded Multifactorial Adaptive Platform (REMAP-CAP) adapted for COVID-19) trial is a global adaptive platform trial of hospitalised patients with COVID-19. We describe implementation in three countries under the umbrella of the Wellcome supported Low and Middle Income Country (LMIC) critical  care network: Collaboration for Research, Implementation and Training in Asia (CCA). The collaboration sought to overcome known barriers to multi centre-clinical trials in resource-limited settings. Methods described focused on six aspects of implementation: i, Strengthening an existing community of practice;ii, Remote study site recruitment, training and support;iii, Harmonising the REMAP CAP- COVID trial with existing care processes;iv, Embedding REMAP CAP- COVID case report form into the existing CCA registry platform, v, Context specific adaptation and data management;vi, Alignment with existing pandemic and critical care research in the CCA. Methods described here may enable other LMIC sites to participate as equal partners in international critical care trials of urgent public health importance, both during this pandemic and beyond.

13.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-314684

ABSTRACT

As the outbreak of coronavirus disease 2019 (COVID-19) is continuously increasing in India, so epidemiological modeling of COVID-19 data is urgently required for administrative strategies. Time series and is capable to predict future observations by modeling the data based on past and present data. Here, we have modeled the epidemiological COVID-19 Indian data using various models. Based on the collected COVID-19 outbreak data, we try to find the propagation rule of this outbreak disease and predict the outbreak situations in India. For India data, the time series model gives the best results in the form of predication as compared to other models for all variables of COVID-19. For new cases, new deaths, total cases and total deaths, the best fitted ARIMA models are as follows: ARIMA(0,2,3), ARIMA(0,1,1), ARIMA(0,2,0) and ARIMA(0,2,1). Based on time series analysis, we predict all variables for next month and conclude that the predictive value of Indian COVID-19 data of total cases is more than 20 lakhs with more than 43 thousand total deaths. The present chapter recommended that a comparison between various predictive models provide the accurate and better forecast value of the COVID-19 outbreak for all study variables.

14.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-314647

ABSTRACT

All transmission disease depends on the transmission opportunity or medium like humans in COVID-19. Due to globalization and regular movement of people from one country to another, spread of COVID 19 reached to 208 countries till May 10, 2020. For any society health is major concern for humanity as well as administration. Any pandemic is declared as and when it reached at a particular severity level and control vice versa. So, we have continued the daily COVID 19 cases analysis and segregated till May 10, 2020. We have included at least 25 countries for the analysis purpose due to limitation of number of observations in the analysis. Maximum number of day’s data available for China is for 100 days, followed by Iran for 81 days, minimum number of days data is for 16 days for Western Sahara and Tajikistan.

15.
Reumatologia ; 59(6): 420-422, 2021.
Article in English | MEDLINE | ID: covidwho-1622752

ABSTRACT

Post-vaccination inflammatory myositis is a rare but known entity in the literature. We encountered a 46-year-old female patient, who presented with complains of fever, arthralgia, and weakness 1 week after taking the second dose of COVID-19 (Oxford-AstraZeneca) vaccine. On workup the patient had raised inflammatory markers, evidence of myositis on magnetic resonance imaging of thighs, and evidence of interstitial lung disease on high-resolution computed tomography of the chest. The patient was further found to be positive for anti-Jo-1 antibody. The initial treatment was glucocorticosteroids and methotrexate initially. The patient briefly developed pneumocystis pneumonia and recovered. The treatment was switched to mycophenolate mofetil with good response. We presented the first case of anti-Jo-1 syndrome reported following COVID-19 vaccination in the literature. Our aim is to sensitise the clinicians to such rare but occasionally life-threatening complications that may arise in the post-vaccination period.

16.
J Educ Health Promot ; 10: 411, 2021.
Article in English | MEDLINE | ID: covidwho-1595072

ABSTRACT

BACKGROUND: The nationwide coronavirus (COVID-19) pandemic and ensuing lockdown has enforced institutions crosswise India to provisionally close to inhibit the spread of the virus and started online learning for students. To measure the level of satisfaction of nursing students with online learning and to identify the barriers which restrict to online learning. MATERIALS AND METHODS: The current study adopted quantitative research approach with an online survey research design and carried out during May-June 2020. Participants were selected through a web-based survey (Google form), in which 219 students enrolled. Self-structured questionnaire with the Likert scale was used to measure the level of satisfaction of nursing students with online learning and identify the barriers which restrict online learning. The descriptive and inferential statistics were used for the analysis in which 219 participants were enrolled in the study of data with IBM SPSS version 20. RESULTS: Majority of student's participants 148 (67.57%) were extremely satisfied with online learning. The findings suggest that the highest barriers which restrict to online learning among nursing students is low voice and language clarity (2.16 ± 0.593), physical health barriers such as eye strain (2.43 ± 0.613), reliability and connectivity problem (2.26 ± 0.534). Among all demographic data, age is significantly associated with the level of satisfaction of online learning. CONCLUSIONS: The study data indicated that maximum students were extremely satisfied the with online learning and among barriers which effect online learning is low voice and language clarity, reliability and connectivity problem, physical health barriers such as eye strain.

17.
Indian J Ophthalmol ; 69(12): 3761-3764, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1538664

ABSTRACT

Coronavirus disease 19 (COVID-19) and its ophthalmic manifestations have been variably portrayed. We report a case of a 56-year-old female presenting with sudden-onset vision loss associated with painful extraocular muscle movements in both eyes following COVID-19. Visual acuity was counting fingers close to face. Color perception tested was inaccurate. Ocular examination revealed sluggishly reacting pupils and an otherwise unremarkable fundus picture in both eyes, giving us an impression of bilateral retrobulbar neuritis. Magnetic resonance imaging of the brain and orbit were unremarkable, while blood investigations revealed nothing suggestive. The patient dramatically improved with steroid therapy with full visual recovery and a color vision defect. This presentation of bilateral retrobulbar neuritis as a sequela of COVID-19 is presented for its rarity.


Subject(s)
COVID-19 , Optic Neuritis , Female , Humans , Magnetic Resonance Imaging , Middle Aged , Optic Neuritis/diagnosis , Optic Neuritis/drug therapy , Optic Neuritis/etiology , SARS-CoV-2 , Visual Acuity
18.
Indian J Ophthalmol ; 69(12): 3704-3708, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1538659

ABSTRACT

PURPOSE: This study aimed to determine the various innovative surgical training techniques prevalent among ophthalmology residents in India during the COVID-19 pandemic. METHODS: This was a prospective cross-sectional study. An online survey questionnaire was completed by ophthalmology residents from different parts of the country. The survey consisted of questions related to the impact of the pandemic on training, innovative training techniques adapted during the pandemic and their effectiveness, and COVID-19 duty-related information. RESULTS: A total of 147 responses were obtained. The mean age was 29.3 years (range: 24-40 years, SD: ±3.82). Of which, 87 (59.2%) respondents were females. A total of 61 (41.5%) respondents reported practicing steps of ocular surgeries on goat eye, 69 (46.9%) on model eye/vegetables/fruits, 30 (20.4%) on surgical simulators, and 26 (17.7%) utilized 3-D virtual images and videos. In addition, 22 (15%) respondents reported never using any such techniques. Furthermore, 130 (88.4%) respondents reported practicing steps of cataract surgery, 52 (35.4%) practiced steps of open globe repair, and steps of trabeculectomy were reported by 24 (16.3%). The steps that were reported to be practiced most are incision or tunnel construction by 108 (73.5%), suturing by 92 (62.6%), capsulorrhexis by 91 (61.9%), primary wound repair by 82 (55.8%), and conjunctival peritomy by 75 (51%). CONCLUSION: The present study demonstrates that residents across the country are adapting to the present scenario by utilizing several innovative methods to sharpen their surgical acumen. The current pandemic situation can serve as an impetus to emphasize upon the institutes and medical regulatory bodies to appropriately remodel the residency curriculum.


Subject(s)
COVID-19 , Cataract Extraction , Internship and Residency , Cross-Sectional Studies , Female , Humans , Pandemics , Prevalence , Prospective Studies , SARS-CoV-2 , Surveys and Questionnaires
19.
J Clin Exp Hepatol ; 11(6): 720-726, 2021.
Article in English | MEDLINE | ID: covidwho-1525840

ABSTRACT

The COVID-19 pandemic has caused mayhem globally since the beginning of 2020. Owing to the immune dysfunction inherent to cirrhosis and the poor general condition, patients with chronic liver disease (CLD) are at higher risk of mortality and morbidity due to COVID-19. Recently, a number of vaccines against SARS-Cov-2 have been approved for emergency use around the globe. Although the phase 2/3 trials of these vaccines show them to be safe and effective in the general population, data in patients with CLD are scarce. The number of patients with CLD enrolled on these trials is small, and no liver-related adverse effects have been reported yet. Various liver societies have come up with guidelines on vaccination in this population and recommend vaccination on a priority basis. Trials to assess the safety and efficacy of the COVID vaccines are underway and are likely to provide valuable insight into this matter.

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