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1.
PLoS ONE [Electronic Resource] ; 17(12):e0278825, 2022.
Article in English | MEDLINE | ID: covidwho-2197057

ABSTRACT

BACKGROUND: Long COVID or long-term symptoms after COVID-19 has the ability to affect health and quality of life. Knowledge about the burden and predictors could aid in their prevention and management. Most of the studies are from high-income countries and focus on severe acute COVID-19 cases. We did this study to estimate the incidence and identify the characteristics and predictors of Long COVID among our patients.

2.
De Simone, B.; Abu-Zidan, F. M.; Chouillard, E.; Di Saverio, S.; Sartelli, M.; Podda, M.; Gomes, C. A.; Moore, E. E.; Moug, S. J.; Ansaloni, L.; Kluger, Y.; Coccolini, F.; Landaluce-Olavarria, A.; Estraviz-Mateos, B.; Uriguen-Etxeberria, A.; Giordano, A.; Luna, A. P.; Amin, L. A. H.; Hernandez, A. M. P.; Shabana, A.; Dzulkarnaen, Z. A.; Othman, M. A.; Sani, M. I.; Balla, A.; Scaramuzzo, R.; Lepiane, P.; Bottari, A.; Staderini, F.; Cianchi, F.; Cavallaro, A.; Zanghi, A.; Cappellani, A.; Campagnacci, R.; Maurizi, A.; Martinotti, M.; Ruggieri, A.; Jusoh, A. C.; Rahman, K. A.; Zulkifli, A. S. M.; Petronio, B.; Matias-Garcia, B.; Quiroga-Valcarcel, A.; Mendoza-Moreno, F.; Atanasov, B.; Campanile, F. C.; Vecchioni, I.; Cardinali, L.; Travaglini, G.; Sebastiani, E.; Chooklin, S.; Chuklin, S.; Cianci, P.; Restini, E.; Capuzzolo, S.; Curro, G.; Filippo, R.; Rispoli, M.; Aparicio-Sanchez, D.; Munoz-Cruzado, V. D.; Barbeito, S. D.; Delibegovic, S.; Kesetovic, A.; Sasia, D.; Borghi, F.; Giraudo, G.; Visconti, D.; Doria, E.; Santarelli, M.; Luppi, D.; Bonilauri, S.; Grossi, U.; Zanus, G.; Sartori, A.; Piatto, G.; De Luca, M.; Vita, D.; Conti, L.; Capelli, P.; Cattaneo, G. M.; Marinis, A.; Vederaki, S. A.; Bayrak, M.; Altintas, Y.; Uzunoglu, M. Y.; Demirbas, I. E.; Altinel, Y.; Meric, S.; Aktimur, Y. E.; Uymaz, D. S.; Omarov, N.; Azamat, I.; Lostoridis, E.; Nagorni, E. A.; Pujante, A.; Anania, G.; Bombardini, C.; Bagolini, F.; Gonullu, E.; Mantoglu, B.; Capoglu, R.; Cappato, S.; Muzio, E.; Colak, E.; Polat, S.; Koylu, Z. A.; Altintoprak, F.; Bayhan, Z.; Akin, E.; Andolfi, E.; Rezart, S.; Kim, J. I.; Jung, S. W.; Shin, Y. C.; Enciu, O.; Toma, E. A.; Medas, F.; Canu, G. L.; Cappellacci, F.; D'Acapito, F.; Ercolani, G.; Solaini, L.; Roscio, F.; Clerici, F.; Gelmini, R.; Serra, F.; Rossi, E. G.; Fleres, F.; Clarizia, G.; Spolini, A.; Ferrara, F.; Nita, G.; Sarnari, J.; Gachabayov, M.; Abdullaev, A.; Poillucci, G.; Palini, G. M.; Veneroni, S.; Garulli, G.; Piccoli, M.; Pattacini, G. C.; Pecchini, F.; Argenio, G.; Armellino, M. F.; Brisinda, G.; Tedesco, S.; Fransvea, P.; Ietto, G.; Franchi, C.; Carcano, G.; Martines, G.; Trigiante, G.; Negro, G.; Vega, G. M.; Gonzalez, A. R.; Ojeda, L.; Piccolo, G.; Bondurri, A.; Maffioli, A.; Guerci, C.; Sin, B. H.; Zuhdi, Z.; Azman, A.; Mousa, H.; Al Bahri, S.; Augustin, G.; Romic, I.; Moric, T.; Nikolopoulos, I.; Andreuccetti, J.; Pignata, G.; D'Alessio, R.; Kenig, J.; Skorus, U.; Fraga, G. P.; Hirano, E. S.; de Lima Bertuol, J. V.; Isik, A.; Kurnaz, E.; Asghar, M. S.; Afzal, A.; Akbar, A.; Nikolouzakis, T. K.; Lasithiotakis, K.; Chrysos, E.; Das, K.; Ozer, N.; Seker, A.; Ibrahim, M.; Hamid, H. K. S.; Babiker, A.; Bouliaris, K.; Koukoulis, G.; Kolla, C. C.; Lucchi, A.; Agostinelli, L.; Taddei, A.; Fortuna, L.; Agostini, C.; Licari, L.; Viola, S.; Callari, C.; Laface, L.; Abate, E.; Casati, M.; Anastasi, A.; Canonico, G.; Gabellini, L.; Tosi, L.; Guariniello, A.; Zanzi, F.; Bains, L.; Sydorchuk, L.; Iftoda, O.; Sydorchuk, A.; Malerba, M.; Costanzo, F.; Galleano, R.; Monteleone, M.; Costanzi, A.; Riva, C.; Waledziak, M.; Kwiatkowski, A.; Czyzykowski, L.; Major, P.; Strzalka, M.; Matyja, M.; Natkaniec, M.; Valenti, M. R.; Di Vita, M. D. P.; Sotiropoulou, M.; Kapiris, S.; Massalou, D.; Veroux, M.; Volpicelli, A.; Gioco, R.; Uccelli, M.; Bonaldi, M.; Olmi, S.; Nardi, M.; Livadoti, G.; Mesina, C.; Dumitrescu, T. V.; Ciorbagiu, M. C.; Ammendola, M.; Ammerata, G.; Romano, R.; Slavchev, M.; Misiakos, E. P.; Pikoulis, E.; Papaconstantinou, D.; Elbahnasawy, M.; Abdel-Elsalam, S.; Felsenreich, D. M.; Jedamzik, J.; Michalopoulos, N. V.; Sidiropoulos, T. A.; Papadoliopoulou, M.; Cillara, N.; Deserra, A.; Cannavera, A.; Negoi, I.; Schizas, D.; Syllaios, A.; Vagios, I.; Gourgiotis, S.; Dai, N.; Gurung, R.; Norrey, M.; Pesce, A.; Feo, C. V.; Fabbri, N.; Machairas, N.; Dorovinis, P.; Keramida, M. D.; Mulita, F.; Verras, G. I.; Vailas, M.; Yalkin, O.; Iflazoglu, N.; Yigit, D.; Baraket, O.; Ayed, K.; Ghalloussi, M. H.; Patias, P.; Ntokos, G.; Rahim, R.; Bala, M.; Kedar, A.; Sawyer, R. G.; Trinh, A.; Miller, K.; Sydorchuk, R.; Knut, R.; Plehutsa, O.; Liman, R. K.; Ozkan, Z.; Kader, S. A.; Gupta, S.; Gureh, M.; Saeidi, S.; Aliakbarian, M.; Dalili, A.; Shoko, T.; Kojima, M.; Nakamoto, R.; Atici, S. D.; Tuncer, G. K.; Kaya, T.; Delis, S. G.; Rossi, S.; Picardi, B.; Del Monte, S. R.; Triantafyllou, T.; Theodorou, D.; Pintar, T.; Salobir, J.; Manatakis, D. K.; Tasis, N.; Acheimastos, V.; Ioannidis, O.; Loutzidou, L.; Symeonidis, S.; de Sa, T. C.; Rocha, M.; Guagni, T.; Pantalone, D.; Maltinti, G.; Khokha, V.; Abdel-Elsalam, W.; Ghoneim, B.; Lopez-Ruiz, J. A.; Kara, Y.; Zainudin, S.; Hayati, F.; Azizan, N.; Khei, V. T. P.; Yi, R. C. X.; Sellappan, H.; Demetrashvili, Z.; Lekiashvili, N.; Tvaladze, A.; Froiio, C.; Bernardi, D.; Bonavina, L.; Gil-Olarte, A.; Grassia, S.; Romero-Vargas, E.; Bianco, F.; Gumbs, A. A.; Dogjani, A.; Agresta, F.; Litvin, A.; Balogh, Z. J.; Gendrikson, G.; Martino, C.; Damaskos, D.; Pararas, N.; Kirkpatrick, A.; Kurtenkov, M.; Gomes, F. C.; Pisanu, A.; Nardello, O.; Gambarini, F.; Aref, H.; Angelis, N. D.; Agnoletti, V.; Biondi, A.; Vacante, M.; Griggio, G.; Tutino, R.; Massani, M.; Bisetto, G.; Occhionorelli, S.; Andreotti, D.; Lacavalla, D.; Biffl, W. L.; Catena, F..
World Journal Of Emergency Surgery ; 17(1):61, 2022.
Article in English | MEDLINE | ID: covidwho-2196368

ABSTRACT

BACKGROUND: The incidence of the highly morbid and potentially lethal gangrenous cholecystitis was reportedly increased during the COVID-19 pandemic. The aim of the ChoCO-W study was to compare the clinical findings and outcomes of acute cholecystitis in patients who had COVID-19 disease with those who did not.

3.
International Journal of Software Science and Computational Intelligence-Ijssci ; 14(1), 2022.
Article in English | Web of Science | ID: covidwho-2201332

ABSTRACT

Global public health will be severely impacted by the successive waves of emerging COVID-19 disease. Since 2019 people get sick and die in our daily lives placing a massive burden on our health system. One of the crucial factors that has led to the virus's fast spread is a protracted clinical testing gap before discovering of a positive or negative result. A detection system based on deep learning was developed by using chest X-ray(CXR) images of Covid19 patient and healthy people. In this regard the Convolution Neural Network along with other DNNs have been proved to produce good results. To improve the COVID-19 detection accuracy, we developed model using the deep learning(CNN) approach where we observed an accuracy of 96%. We validated the accuracy by using same dataset through a pretrained VGG16 model and an LSTM model which produced excellent reliable results. Our aim of this research is to implement a reliable Deep Learning model to detect presence of Covid-19 in case of limited availability of chest-Xray images.

4.
Am J Otolaryngol ; 44(2):103702, 2022.
Article in English | PubMed | ID: covidwho-2158378

ABSTRACT

PURPOSE: To compare the efficacy of 0.1 % w/w Liposomal Amphotericin-B gel with 10 % w/w Povidone-Iodine and saline nasal douching in preventing revision surgery in patients with CAM. STUDY DESIGN: Multi-arm, parallel randomized control trial. STUDY SETTING: The trial was conducted in the Department of ENT, All India Institute of Medical Sciences (AIIMS) Bhubaneswar. METHODS: Participants: Microbiologically and histologically proven cases of mucormycosis who underwent surgical debridement were included in the study. INTERVENTIONS: Postoperatively, patients were randomized into three groups based on the type of topical intervention received, in the form of Lipid-based Amphotericin B gel, povidone‑iodine ointment or saline nasal douching. OUTCOME: Requirement of revision surgery in postoperative cases of CAM. RANDOMIZATION: Participants were allotted to one of the three arms by block randomization. BLINDING: Single-blinded trial. RESULTS: Numbers randomized: 15 participants were randomized to each group. Recruitment: Completed recruiting. Numbers analyzed: 15 participants were analyzed in each group. OUTCOMES: Control arm's risk of revision surgery was 4.50 (95 % CI: 1.16-17.44) times than Lipid-based Amphotericin B gel arm and 1.50 (95 % CI: 0.71-3.16) times that of the Povidone- Iodine arm. The difference was statistically significant (p = 0.02) for Amphotericin but not for Povidone-Iodine. CONCLUSIONS: Topical Amphotericin-B gel application in the postoperative cavity can decrease the need for revision surgery and help in early recovery. TRIAL REGISTRATION: CTRI/2021/10/037257. Clinical Trials Registry of India.

5.
Ieee Access ; 10:120901-120921, 2022.
Article in English | Web of Science | ID: covidwho-2152416

ABSTRACT

Background: Radiomical data are redundant but they might serve as a tool for lung quantitative assessment reflecting disease severity and actual physiological status of COVID-19 patients. Objective: Test the effectiveness of machine learning in eliminating data redundancy of radiomics and reflecting pathophysiologic changes in patients with COVID-19 pneumonia. Methods: We analyzed 605 cases admitted to Al Ain Hospital from 24 February to 1 July, 2020. They met the following inclusion criteria: age $\geq 18$ years;inpatient admission;PCR positive for SARS-CoV-2;lung CT available at PACS. We categorized cases into 4 classes: mild < 5% of pulmonary parenchymal involvement, moderate - 5-24%, severe - 25-49%, and critical $\geq50$ %. We used CT scans to build regression models predicting the oxygenation level, respiratory and cardiovascular functioning. Results: Radiomical findings are a reliable source of information to assess the functional status of patients with COVID-19. Machine learning models can predict the oxygenation level, respiratory and cardiovascular functioning from a set of demographics and radiomics data regardless of the settings of reconstructionkernels. The regression models can be used for scoring lung impairment and comparing disease severity in followup studies. The most accurate prediction we achieved was 6.454 +/- 3.715% of mean absolute error/range for all thefeatures and 7.069 +/- 4.17% for radiomics.Conclusion:The models may contribute to the proper risk evaluation anddisease management especially when the oxygen therapy impacts the actual values of the functional findings. Still,the structural assessment of an acute lung injury reflects the severity of the disease.

6.
6th International Conference on Advanced Computing and Intelligent Engineering, ICACIE 2021 ; 428:31-47, 2023.
Article in English | Scopus | ID: covidwho-2094488

ABSTRACT

COVID-19, the virus that has affected current living standards, has undergone mutation, and the second wave has caused a much more devastating situation in India. In such a scenario, the alert of a third wave by the authorities has alarmingly increased concern in the nation. After being declared as an international emergency, the development of its vaccine has been conducted by different countries. India among other countries is also pursuing to develop much more efficient variants of the vaccine. The situation still persists to be hostile and maintaining the current precaution measures and maximizing the distribution of the vaccines is the only solution in hand. A necessity arises for a user-friendly app to reduce social interaction while assisting in medical support. In this paper, we have proposed an android application named YUDH, which focuses on the overall service that an individual requires from booking test centers, vaccine slot notification to home sanitization. The user can book COVID-19 testing centers and can arrange sanitization service after recovery with the provision of place, date, and time. In addition to booking test centers, swab testing at the doorstep is also available. The user also gets regular notifications on COVID vaccine slot availability in accordance with CoWIN portal and users’ preferences. This deployment is aimed at the safety of the user and their privacy safeguard. The application also assists the government to maintain a database more efficiently. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

7.
IEEE Access ; : 1-1, 2022.
Article in English | Scopus | ID: covidwho-2078163

ABSTRACT

Background: Radiomical data are redundant but they might serve as a tool for lung quantitative assessment reflecting disease severity and actual physiological status of COVID-19 patients. Objective: Test the effectiveness of machine learning in eliminating data redundancy of radiomics and reflecting pathophysiologic changes in patients with COVID-19 pneumonia. Methods: We analyzed 605 cases admitted to Al Ain Hospital from 24 February to 1 July, 2020. They met the following inclusion criteria: age≥18 years;inpatient admission;PCR positive for SARS-CoV-2;lung CT available at PACS. We categorized cases into 4 classes: mild ≤25% of pulmonary parenchymal involvement, moderate - 25-50%, severe - 50-75%, and critical –over 75%. We used CT scans to build regression models predicting the oxygenation level, respiratory and cardiovascular functioning. Results: Radiomical findings are a reliable source of information to assess the functional status of patients with COVID-19. Machine learning models can predict the oxygenation level, respiratory and cardiovascular functioning from a set of demographics and radiomics data regardless of the settings of reconstruction kernels. The regression models can be used for scoring lung impairment and comparing disease severity in follow up studies. The most accurate prediction we achieved was 6.454±3.715% of mean absolute error/range for all the features and 7.069±4.17% for radiomics. Conclusion: The models may contribute to the proper risk evaluation and disease management especially when the oxygen therapy impacts the actual values of the functional findings. Still, the structural assessment of an acute lung injury reflects the severity of the disease. Author

8.
J Laryngol Otol ; 136(12): 1309-1313, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2076940

ABSTRACT

OBJECTIVE: Rhino-orbito-cerebral mucormycosis is a rapidly progressive disease with high mortality rates of about 60 per cent. The increasing incidence of rhino-orbito-cerebral mucormycosis in coronavirus disease 2019 patients in India and worldwide has become a matter of concern owing to the case fatality rate. This study explored the use of low dose aspirin in decreasing the mortality rate of coronavirus disease 2019 associated mucormycosis. METHOD: This was a retrospective observational study. Patients suffering from post-coronavirus disease 2019 mucormycosis were included in the study. Each patient was treated with surgical debridement and systemic amphotericin B. Low dose aspirin was added, and mortality rates were compared with the patients who did not receive aspirin. RESULTS: The demographic data and rhino-orbito-cerebral mucormycosis staging between the two groups were not significantly different. There was a statistically significant difference in mortality outcomes between the two groups (p = 0.029) and a 1.77 times higher risk of dying for patients not receiving aspirin. Kaplan-Meier survival indicated that patients receiving aspirin had better survival rates (p = 0.04). CONCLUSION: Low dose aspirin improves survival rates in coronavirus disease 2019 associated mucormycosis.


Subject(s)
COVID-19 , Mucormycosis , Orbital Diseases , Humans , Mucormycosis/drug therapy , Retrospective Studies , Aspirin/therapeutic use , Antifungal Agents/therapeutic use , Debridement
10.
International Journal of Health Sciences ; 6:3535-3554, 2022.
Article in English | Scopus | ID: covidwho-1995087

ABSTRACT

The deadly COVID-19 outbreak emerged in the city of Wuhan, China at the end of 2019 and developed into a global pandemic during March 2020. According to Ministry of Health and Family Welfare, Govt. of India report of 2021, recovery rate of the state capital of Mizoram is very low while the positivity rate is high during the second wave compared to the national average. Therefore this present study aimed to analyze the spatial pattern of Covid Care Centers, infrastructural details and different Covid Care Service area with the help of GIS using Nearest Neighbour Analysis (NNA) and Weighted Linear Combined Model (WLCM) in Aizawl district of Mizoram. The result shows that Covid Care Centers are mainly clustered in city areas and infrastructure is not adequate. There is dearth of COVID care facilities in the district and the major chunk of facilities are located only in the capital city of Aizawl leaving the rest of the district in a weak zone facility wise. Only city and its surrounding areas have very high and high Covid Care Service. The overall scenario is indicating a poor condition towards the village areas. So, this present study will help the policymakers of health authorities to take some remedial measures in inaccessible and underdeveloped Covid healthcare service areas to improve Covid Care services of the district. © 2022 International Journal of Health Sciences. All rights reserved.

11.
2022 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2022 ; 2022.
Article in English | Scopus | ID: covidwho-1948802

ABSTRACT

In today's world of medical science, remote patient monitoring devices are becoming more important and a future need particularly in the present COVID-19 situation as individuals are preferred to be kept isolated. Patients would be benefited from a suitable monitoring system that measures their important medical parameters such as pulse rate, oxygen saturation or SpO2, body temperature, blood pressure, and Galvanized Skin Response (GSR). This system can increase the medical staff efficiency by drastically decreasing their duties in hospitals and the need to attend to them individually. Patients in their home isolation may utilize the device as well, and their vital indicators may be checked by doctors remotely. In this work, we are prototyping a powerefficient, wearable medical kit and a resource-aware fog network set up to handle the Internet of Things (IoT) data traffic. The idea behind the design is to process the critical medical sensors' data in the fog nodes which are deployed at the edge of the network. The data thus received, is used for a machine learning-based solution for personal health anomalies and COVID-19 infection risk analysis. © 2022 IEEE.

12.
Egyptian Journal of Radiology and Nuclear Medicine ; 53(1), 2022.
Article in English | EMBASE | ID: covidwho-1938375

ABSTRACT

Background: Chest radiographs are frequently used to evaluate pediatric patients with COVID-19 infection during the current pandemic. Despite the minimal radiation dose associated with chest radiography, children are far more sensitive to ionizing radiation's carcinogenic effects than adults. This study aimed to examine whether serum biochemical markers could be potentially used as a surrogate for imaging findings to reduce radiation exposure. Methods: The retrospective posthoc analysis of 187 pediatric patients who underwent initial chest radiographs and serum biochemical parameters on the first day of emergency department admission. The cohort was separated into two groups according to whether or not the initial chest radiograph revealed evidence of pneumonia. Spearman's rank correlation was used to connect serum biochemical markers with observations on chest radiographs. The Student's t-test was employed for normally distributed data, and for non-normally distributed data, the Mann–Whitney U test was used. A simple binary logistic regression was used to determine the importance of LDH in predicting chest radiographs. The discriminating ability of LDH in predicting chest radiographs was determined using receiver operating characteristics (ROC) analysis. The cut-off value was determined using Youden's test. Interobserver agreement was quantified using the Cohen k coefficient. Results: 187 chest radiographs from 187 individual pediatric patients (95 boys and 92 girls;mean age ± SD, 10.1 ± 6.0 years;range, nine months–18 years) were evaluated. The first group has 103 patients who did not have pneumonia on chest radiographs, while the second group contains 84 patients who had evidence of pneumonia on chest radiographs. GGO, GGO with consolidation, consolidation, and peri-bronchial thickening were deemed radiographic evidence of pneumonia in group 2 patients. Individuals in group 2 with radiological indications of pneumonia had significantly higher LDH levels (p = 0.001) than patients in group 1. The Spearman's rank correlation coefficient between LDH and chest radiography score is 0.425, showing a significant link. With a p-value of < 0.001, the simple binary logistic regression analysis result validated the relevance of LDH in predicting chest radiography. An abnormal chest radiograph was related to LDH > 200.50 U/L (AUC = 0.75), according to the ROC method. Interobserver agreement between the two reviewers was almost perfect for chest radiography results in both groups (k = 0.96, p = 0.001). Conclusion: This study results show that, compared to other biochemical indicators, LDH has an 80.6% sensitivity and a 62% specificity for predicting abnormal chest radiographs in a pediatric patient with confirmed COVID-19 infection. It also emphasizes that biochemical measures, rather than chest radiological imaging, can detect the pathogenic response to COVID-19 infection in the chest earlier. As a result, we hypothesized LDH levels might be potentially used instead of chest radiography in children with COVID-19, reducing radiation exposure.

13.
5th International Conference on Smart Computing and Informatics, SCI 2021 ; 283:139-149, 2022.
Article in English | Scopus | ID: covidwho-1899057

ABSTRACT

In December 2019, the COVID-19 broke out. From that point, the situation has become much dire. The number of cases kept spiking and a cure is still unknown for COVID-19. For this reason, we must be more cautious and take all possible precautions. We know a few things about this disease. Fever happens to be one of the early symptoms of COVID-19. Hence, we do thermal scanning in public places. Our paper proposes a way to make this process more efficient. We can scan body temperature using various sensors and store it in the cloud. Doing so, it gives us more flexibility to monitor the data and predict if someone might suffer from fever in the future. In our analysis, we have found that among the different machine learning algorithms, moving averages smoothing was able to predict the data better. Now, in order to run this machine learning model automatically, we used AWS. Also, due to GUI, it is much easier to use the system. Overall, the main purpose of our work is to collect daily thermal scan reports and use that data for our benefit. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

14.
2021 International Conference on Control, Automation, Power and Signal Processing, CAPS 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1784479

ABSTRACT

The COVID-19 pandemic has hit the world at large claiming large number of lives till date leaving us with no solution except maintaining social distancing or washing hands regularly, wearing masks and staying at homes. Social distancing is one of the key aspects to prevent spreading of this virus. It means more of maintaining suitable distance between each other. Artificial intelligence has been used widely for a large number of purposes and as such is one of the key tools used here for implementing this project. The proposed system identifies people who are not suitable distance apart by using object detection and calculating the Euclidian distance between two people. This system would be beneficial to the authorities for alerting people if the situation is serious. © 2021 IEEE.

15.
12th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2021 ; : 702-707, 2021.
Article in English | Scopus | ID: covidwho-1672777

ABSTRACT

Novel Corona Virus (COVID-19) was declared as a global pandemic on March 11, 2020 by World Health Organization (WHO). All countries around the globe have implemented the lockdown and maintaining of safe distance to minimize the spread of COVID-19. India had implemented the lockdown at an early stage of virus outbreak while maintaining strict social distancing protocol in all states including Karnataka. Karnataka state has taken various measures to contain the spread which includes regulated lockdown, creating containment zones, initiating social distancing protocol, and so on. Karnataka implemented lockdown in phases during wave-1 wave-2. All countries across the world had implemented lockdowns and quarantine as a counter measure to address the rapid increase in the infected cases and death toll numbers. Having said, the effects of lockdown on disease cannot-and should not-be looked at in isolation. They are entwined with its political and humanitarian effects, including unemployment, hunger, an unprecedented migrant worker crisis, and widespread loss of access to healthcare. These crises could have been averted or lessened with planning, but they are now an essential part of India's lockdown story. However, in this study we are aiming to analyze the effectiveness of lockdown in Karnataka, India. We analyzed the data available at covid19india.org for the confirmed cases during wave-1 wave-2 of the pandemic in Karnataka state. As part of Exploratory data analysis (EDA), we conducted hypothesis testing, p-value, t-statistics as a statistical technique to determine the impact of the lockdown. Based on our statistical analysis in this study, we can say that lockdown in Karnataka state during the wave-1 and wave-2 was effective. It has helped control the speed of spreading the virus and breaking the chain during the lockdown. © 2021 IEEE.

16.
5th International Conference on Information and Communication Technology for Intelligent Systems, ICTIS 2021 ; 251:145-155, 2022.
Article in English | Scopus | ID: covidwho-1653368

ABSTRACT

The spread of COVID-19 contagion has to lead the world on a pause, because of its alarming rate. The only immediate solution was to practice social distancing and enforce lockdown. COVID-19 has declared an international emergency because it has been labeled pandemic, and different countries are still developing their vaccine. As far as now various countries with various governments have undertaken active plans and emergency measures to protect the public. The government and various health organizations are in charge of the survey. In fear of being affected, people tend to avoid hospital visits and circumvent the COVID-19 test. As of now, many Web applications are developed to avoid social interaction and community gathering. The COVID-19 test booking Web app provides the user to choose what, when, and where to take the COVID-19 test, it also helps the government health officials to maintain a safe database. This ensures the increase of COVID-19 test being taken and provides the individual proper safety and assurance. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

17.
Indian Journal of Hematology and Blood Transfusion ; 37(SUPPL 1):S76, 2021.
Article in English | EMBASE | ID: covidwho-1633556

ABSTRACT

Introduction: Since its origin in December 2019, Novel Corona virusinfection has behaved in an unprecedented manner. Viral infectionsare characterized by atypical and reactive lymphocytosis as is seen ininfectious mononucleosis and dengue viral infection respectively.Previous studies on influenza like illnesses have demonstrated the roleof Neutrophil-to-lymphocyte as a preferable diagnostic tool to screeninfluenza virus-infected patients. In addition to these, volume conductivity and scatter has revealed significant findings in volumescatter and conductivity of monocytes and neutrophils in the past ininfluenza and influenza like illnesses.Aims &Objectives: To study the hematological parameters ofCOVID-19 positive cases and to compare the hematological parameters in COVID-19 positive cases, patients with influenza andinfluenza like illness.Materials &Methods: 169 Covid positive cases, 113 influenza andinfluenza like illnesses and 140 healthy controls were included in thestudy. All samples were processed on DXH 800 and all parameterswere recorded.Result: There was significant difference between Covid 19 and influenza and influenza like illness in terms of age, percentage ofneutrophils, percentage of lymphocyte, percentage of monocyte, percentage of eosinophil and basophil. Significant difference was alsofound between mean neutrophilic and mean monocytic volume, and inall the scatter parameters of neutrophils. Neutrophil-to-lymphocyteratio (NLR) and platelet-to-lymphocyte ratio (PLR) also showed significant difference in both the conditions. Multivariate analysis wasperformed and a joint probability was calculated which showed a cutoffin differentiating Covid 19 from influenza and influenza like illnesses.Conclusions: Covid 19 and Influenza can cause different changes inperipheral blood parameters and the diagnostic formula developed inthis study will enable the clinicians to differentiate Covid 19 frominfluenza during the early stages.

18.
Journal of the American Society of Nephrology ; 32:59, 2021.
Article in English | EMBASE | ID: covidwho-1489908

ABSTRACT

Background: Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 was first reported in Wuhan in 2019 and reached pandemic proportions. SARS-CoV-2-related respiratory failure and acute kidney injury (AKI) are major complications of infection. Kidney Injury Molecule-1 (KIM-1) is a scavenger receptor expressed by kidney epithelial cells and was previously reported to be a receptor for Hepatitis virus A. We hypothesized that KIM-1 is a receptor for SARS-CoV-2 and may play an important role in COVID-19 lung and kidney injury. Methods: Human lung and kidney autopsy samples were immunostained and analyzed. Liposomal nanoparticles displaying the SARS-CoV-2 spike protein on their surface (virosomes) were generated. Virosome uptake by A549 lung epithelial cells, mouse primary lung epithelial cells and human kidney tubuloids (3D structures of kidney epithelial cells) was evaluated in the presences or absence of anti-KIM-1 antibody or TW-37, a small molecule inhibitor of KIM-1-mediated endocytosis that we discovered. Protein-protein interaction characteristics between purified SARS-CoV-2 spike protein and purified KIM-1 were determined using microscale thermophoresis. HEK293 cells expressing human KIM-1 but not angiotensin-converting enzyme 2 (ACE2) were infected with live SARS-CoV-2 or pseudovirions expressing the SARS-CoV-2 spike protein. Results: KIM-1 was expressed in lung and kidney epithelial cells in COVID-19 patient autopsy samples. Human and mouse lung and kidney epithelial cells expressed KIM-1 and endocytosed spike-virosomes. Both anti-KIM-1 antibodies and TW-37 inhibited uptake. Enhanced KIM-1 expression by human kidney tubuloids increased virosome uptake. KIM-1 positive cells expressed less ACE2. Using microscale thermophoresis, the EC50 for interaction between KIM-1 and SARS-CoV-2 spike protein and the receptor binding domain were 56.2±28.8 nM and 9.95±3.10 nM, respectively. KIM-1-expressing HEK293 cells without ACE2 expression had increased susceptibility to infection by live SARS-CoV-2 and pseudovirions expressing spike when compared with control cells. Conclusions: KIM-1 is a receptor for SARS-CoV-2 in the lung and kidney and thus, KIM-1 inhibitors such as TW-37 can be potential therapeutics and/or prophylactic agents for COVID-19.

19.
Egyptian Journal of Radiology and Nuclear Medicine ; 52(1), 2021.
Article in English | EMBASE | ID: covidwho-1457699

ABSTRACT

Background: Despite the dominance of Covid-19 in the current situation, MERS-CoV is found infrequently in the Middle East. When coupled with the chest radiographic score, serum biochemical parameters may be utilized to assess serum biochemical changes in individuals with different degrees of MERS-CoV infection and to predict death. The purpose of this study was to examine the association between increased LDH levels and severe MERS-CoV outcomes utilizing ventilation days and an elevated chest radiographic score. Results: Fifty-seven patients were included in the retrospective cohort. The mean age was 44.9 ± 13.5 years, while the range was between 12 and 73 years. With an average age of 53.3 ± 16.5 years, 18 of 57 (31.6%) patients were classified as deceased. The deceased group showed a substantially greater amount of LDH than the recovery group (280.18 ± 150.79 vs. 1241.72 ± 1327.77, p = 0.007). A cut-off value of > 512 LDH was established with a C-statistic of 0.96 (95% CI 0.92–1.00) and was 94% sensitive and 93% specific for mortality. Multivariate cox regression analysis revealed that loge (LDH) (adjusted HR: 9.91, 95% CI: 2.44–40.3, p = 0.001) and chest radiographic score (adjusted HR: 1.24, 95% CI: 1.05–1.47, p = 0.01) were risk factors for mortality, whereas ventilation days were a protective factor (adjusted HR: 0.84, 95% CI: 0.76–0.93, p = 0.001). Conclusion: According to our results, blood LDH levels of > 512 had a 94% sensitivity and 93% specificity for predicting in-hospital mortality in patients infected with MERS-CoV. The chest radiographic score of 11.34 ± 5.4 was the risk factor for the mortality (adjusted Hazard ratio HR: 1.24, 95% CI: 1.05–1.47, p = 0.01). Thus, threshold may aid in the identification of individuals with MERS-CoV infection who die in hospital.

20.
Annals of Phytomedicine-an International Journal ; 10(1):S130-S145, 2021.
Article in English | Web of Science | ID: covidwho-1389934

ABSTRACT

Dry fruits and few edible seeds are very common consumableitems with the rich source of polyphenolic compounds. Many other phytochemicals are also present in dry fruits and shows significant antioxidant activity that further correlated to get rid of many health complications. These fruits are commonly known as dry fruits or super foods with the rich content of proteins, vitamins, minerals and dietary fibre. They are well known for their immuno modulatory activities with various medicinal applications, especially as antiviral activity. The ongoing COVID outbreak has posed a serious threat to global health sector. At present, the second wave of coronavirus is already has started and gradually increasing day by day in worldwide which arestronger and much more detrimental for the people including in India. In connection with the previous history, it is obvious to increase immunity to fight against the pandemic virus. In the present manuscript, some important dry fruits and seeds are selected which have dual characters, i.e., potent immune boosting property along with antiviral efficacy. Various phytochemicals like flavonoids, alkaloids, glycosides, sesquiterpenes, benzoic compounds were reportedly isolated from these plant extracts those are having strong antiviral as well as immune boosting properties. Therefore, the detail study of these dry fruits and seeds with their sources, chemicals responsible for the therapeutic efficacy, their structural nature, and potent uses along with their combined preparations as home as remedies in boosting immunity and also to resist the viral infection are discussed. The article will focus to the researchers for detailed ethnopharmacological and phytochemical studies on these dry fruit and seed plants used to treat as immuno modulators as well as in the development of novel antiviral drugs.

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