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1.
Journal of Pharmaceutical Negative Results ; 13:5890-5899, 2022.
Article in English | EMBASE | ID: covidwho-2206801

ABSTRACT

Entrepreneurship is proven as a medium in lifting an economic state of an individual or a community. It is also can be considered as an alternative area to be explored especially in the current situation where the world is affected by the pandemic of COVID-19 globally. It justifies the need to research this topic to leverage its benefits to various perspectives including the asnaf community. Unfortunately, despite its importance, limited studies have been found were conducted on entrepreneurship among asnaf community. Therefore, this research is initiating research on this topic by conducting a systematic literature review on the published works on entrepreneurship among asnaf community to explore the trend of the existing research works. A PRISMA approach is adapted to collect the relevant literature that is scoped only to the Scopus and Web of Science (WoS) databases. The result obtained from this research is expected will provide an overview of the trend of previously conducted research works on the entrepreneurship among asnaf community. Finally, it can be referred by a potential researcher in this topic to plan their future research. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

2.
Egyptian Liver Journal ; 12(1), 2022.
Article in English | ProQuest Central | ID: covidwho-2139802

ABSTRACT

BackgroundPortal hypertension is considered as a major complication of liver cirrhosis. Endoscopy plays a main role in managing of gastrointestinal complications of portal hypertension. Endoscopists are at increased risk for COVID-19 infection because upper gastrointestinal (GI) endoscopy is a high-risk aerosol-generating procedure and may be a potential route for COVID-19.ObjectivesTo compare the outcome between cirrhotic patients who underwent classic regular endoscopic variceal ligation after primary bleeding episode every 2–4 weeks, and those presented during the era of COVID-19 and their follow-up were postponed 2 months later.MethodsThis retrospective study included cross-matched 238 cirrhotic patients with portal hypertension presented with upper GI bleeding, 112 cirrhotic patients presented during the era of COVID19 (group A) underwent endoscopic variceal ligation, another session after 2 weeks and their subsequent follow-up was postponed 2 months later, and 126 cirrhotic patients as control (group B) underwent regular endoscopic variceal band ligation after primary bleeding episode every 2–4 weeks.ResultsEradication of varices was achieved in 32% of cases in group A, and 46% in group was not any statistically significant (p > 0.05);also, there was no any statistical significant difference between both groups regarding occurrence of rebleeding, post endoscopic symptoms, and mortality rate (p > 0.05).ConclusionBand ligation and injection of esophageal and gastric vary every 2 months were as effective and safe as doing it every 2 to 4 weeks after primary bleeding episode for further studies and validation.

3.
Lancet Digital Health ; 4(8):E573-E583, 2022.
Article in English | Web of Science | ID: covidwho-2092794

ABSTRACT

Background Real-time prediction is key to prevention and control of infections associated with health-care settings. Contacts enable spread of many infections, yet most risk prediction frameworks fail to account for their dynamics. We developed, tested, and internationally validated a real-time machine-learning framework, incorporating dynamic patient-contact networks to predict hospital-onset COVID-19 infections (HOCIs) at the individual level. Methods We report an international retrospective cohort study of our framework, which extracted patient-contact networks from routine hospital data and combined network-derived variables with clinical and contextual information to predict individual infection risk. We trained and tested the framework on HOCIs using the data from 51 157 hospital inpatients admitted to a UK National Health Service hospital group (Imperial College Healthcare NHS Trust) between April 1, 2020, and April 1, 2021, intersecting the first two COVID-19 surges. We validated the framework using data from a Swiss hospital group (Department of Rehabilitation, Geneva University Hospitals) during a COVID-19 surge (from March 1 to May 31, 2020;40 057 inpatients) and from the same UK group after COVID-19 surges (from April 2 to Aug 13, 2021;43 375 inpatients). All inpatients with a bed allocation during the study periods were included in the computation of network-derived and contextual variables. In predicting patient-level HOCI risk, only inpatients spending 3 or more days in hospital during the study period were examined for HOCI acquisition risk. Findings The framework was highly predictive across test data with all variable types (area under the curve [AUC]-receiver operating characteristic curve [ROC] 0.89 [95% CI 0.88-0.90]) and similarly predictive using only contact-network variables (0.88 [0.86-0.90]). Prediction was reduced when using only hospital contextual (AUC-ROC 0.82 [95% CI 0.80-0.84]) or patient clinical (0.64 [0.62-0.66]) variables. A model with only three variables (ie, network closeness, direct contacts with infectious patients [network derived], and hospital COVID-19 prevalence [hospital contextual]) achieved AUC-ROC 0.85 (95% CI 0.82-0.88). Incorporating contact-network variables improved performance across both validation datasets (AUC-ROC in the Geneva dataset increased from 0.84 [95% CI 0.82-0.86] to 0.88 [0.86-0.90];AUC-ROC in the UK post-surge dataset increased from 0.49 [0.46-0.52] to 0.68 [0.64-0.70]). Interpretation Dynamic contact networks are robust predictors of individual patient risk of HOCIs. Their integration in clinical care could enhance individualised infection prevention and early diagnosis of COVID-19 and other nosocomial infections. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.

4.
An Interdisciplinary Approach in the Post-COVID-19 Pandemic Era ; : 263-278, 2022.
Article in English | Scopus | ID: covidwho-2092128

ABSTRACT

Unlocking after lockdown in the current COVID-19 pandemic has apparently resulted in a new normal way of living, but its impact on mental health is still unexplored. The present study tried to explore the mental health status of the general population in India during the current unlocking phase of the COVID-19 outbreak. Furthermore, it aimed at examining the mental health burden in different age groups and finally to find out the association between psychological distress and education loss, financial loss, exposure and acquaintance of COVID 19. The study was conducted from Unlock phase 3.0 to Unlock phase 8.0 on 200 participants. A Google form was created and circulated on different online and social media platforms. The measures used were: the Impact of Event Scale (IES), Depression, Anxiety, and Stress Scale (DASS-21). The data was analyzed with the help of SPSS v21. Results clearly show that the mental health burden of the majority of the population fell into the normal category and a few into the mild category. As far as stress, anxiety, depression, and IES in the unlock phase are concerned, they still exist but in lower figures as compared to lockdown phases. Without a doubt, the burden on mental health has been greatly reduced, but it still exists among the general population. © 2022 Nova Science Publishers, Inc..

6.
Evol Intell ; : 1-12, 2022 Sep 10.
Article in English | MEDLINE | ID: covidwho-2027689

ABSTRACT

The first COVID-19 confirmed case was reported in Wuhan, China, and spread across the globe with an unprecedented impact on humanity. Since this pandemic requires pervasive diagnosis, developing smart, fast, and efficient detection techniques is significant. To this end, we have developed an Artificial Intelligence engine to classify the lung inflammation level (mild, progressive, severe stage) of the COVID-19 confirmed patient. In particular, the developed model consists of two phases; in the first phase, we calculate the volume and density of lesions and opacities of the CT scan images of the confirmed COVID-19 patient using Morphological approaches. The second phase classifies the pneumonia level of the confirmed COVID-19 patient. We use a modified Convolution Neural Network (CNN) and k-Nearest Neighbor; we also compared the results of both models to the other classification algorithms to precisely classify lung inflammation. The experiments show that the CNN model can provide testing accuracy up to 95.65% compared with exiting classification techniques. The proposed system in this work can be applied efficiently to CT scan and X-ray image datasets. Also, in this work, the Transfer Learning technique has been used to train the pre-trained modified CNN model on a smaller dataset than the original dataset; the modified CNN achieved 92.80% of testing accuracy for detecting pneumonia on chest X-ray images for the relatively extensive dataset.

7.
13th IEEE Control and System Graduate Research Colloquium, ICSGRC 2022 ; : 114-119, 2022.
Article in English | Scopus | ID: covidwho-2018870

ABSTRACT

The COVID-19 virus pandemic in Indonesia has been going on since March 2020 and is still ongoing with conditions that need to be watched out for. This can be seen from the distribution of the daily active cases addition in Indonesia which is still changing dynamically. An alternative solution that can help to analyze countermeasures for the virus spread is modeling and simulating the spread of cases to estimate pandemic conditions that may occur in Indonesia. A common and widely used epidemiological-based model is the SIR model, which groups individuals affected by a pandemic into several compartments. Using this modeling and utilizing the concept of optimization technology, the modeling process can be carried out more efficiently and accurately. A model is developed, one of the derivatives of SIR modeling, namely SIR-FV, based on the concept of optimization to estimate and simulate various virus spread scenarios. There are 2 scenarios developed for analysis, namely the vaccination program scenario and the contact rate scenario. Based on the scenario simulation, it was found that the vaccination program could have a positive impact on efforts to deal with the COVID-19 pandemic more effectively when compared to the scenario without vaccination. The contact rate scenario also has a significant impact. However, the simulation also shows that if the vaccination program is not supported by adequate health protocols, it will not have any impact on the prevention effort. These results apply to the results of the SIR-FV model. Overall, it can be concluded that the developed model can carry out all of its functions as needed, with the level of accuracy through the MAPE metric reaching 0.012 for the SIRFV model. © 2022 IEEE.

8.
NeuroQuantology ; 20(8):7591-7595, 2022.
Article in English | EMBASE | ID: covidwho-2010532

ABSTRACT

The current research aimedto demonstrate the extent such as increase in the rate of immune response to antibodies (IgG, IgM) for people who received the first dose of the Pfizer mRNA vaccine at (1-3) weeks times period and to compare them with people who were not taken for the first dose of the same vaccine and none infected with COVID-19.Also the results appearedsignificant variations in immunoglobulin (IgG) levels (P≤ 0.05) between case (Recipients mRNA vaccination) and control patients, there were. In terms of age and gender, however, there were no significant changes (P≥ 0.05) in immunoglobulin (IgM) levels between case (Recipients mRNA vaccination) and control patients.

9.
Indian Journal of Critical Care Medicine ; 26:S13, 2022.
Article in English | EMBASE | ID: covidwho-2006325

ABSTRACT

Aim and background: Management in COVID-19 includes the use of steroids, prolonged hospital stay, and long-term ventilatory care using muscle relaxants for lung-protective ventilation. These patients are subjected to fluctuating hemodynamics, blood sugar levels, secondary sepsis, systemic inflammatory response syndrome, and multi-organ dysfunction. This causes an increased risk for developing critical illness polyneuropathy and myopathy. Objectives: The literature assessing the effect of these risk factors on mortality in patients with COVID-19 is scarce. Hence, we assessed the effect of various risk factors and interventions on the long-term outcome in these patients. Materials and methods: We collected retrospective data of critically ill COVID-19 patients who developed from critical illness myopathy. The demographic details, clinical parameters, laboratory values, effect of protocol-based physiotherapy intervention, and long-term outcome of patients in term of residual weakness, dependency, and mortality was collected. Results: Out of the total 324 critically ill COVID-19 patients, 11 patients were diagnosed with critical illness myopathy and were included for data collection. Among the patients who developed critical illness myopathy, in-hospital mortality was around 36.4%. The use of protocol-based physiotherapy interventions like long sitting (P = 0.007) and, chair mobilization (p = 0.001) led to a significant reduction in mortality in COVID-19 patients. Conclusion: In patients with COVID-19 related critical illness myopathy, the use of protocol-based physiotherapy interventions leads to improved survival. Key messages: In patients with COVID-19 related critical illness myopathy, the use of protocol-based physiotherapy interventions has survival benefits.

10.
Biochemical and Cellular Archives ; 22(1):1347-1351, 2022.
Article in English | EMBASE | ID: covidwho-1980145

ABSTRACT

COVID-19 (coronavirus disease 2019), cause severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) across all age groups, it’s a positive-sense single-stranded RNA virus, and a member of the Betacoronavirus genus taxonomically (Jiang et al, 2020). Given the importance roles of zinc in combating oxidative damage and viral infections, Zinc also has confirmed roles in both male and female reproduction. The possible depletion of zinc with the oxidative events of COVID-19 is especially relevant to the fertility of affected couples (Sethuram et al, 2021). The aim of study is to determine the relation between zinc value and oxidative stress level represented by ROS (Reactive Oxygen Species) and testosterone level among the recovered COVID-19 patients in reproductive age. 120 men chosen from Center of Medical City, Health Center of 9 Nisan, Poisoning Consultation Center and Kamal AL-Samarrai Hospital, 70 recovered males from COVID-19 within a period of 6 months after the last negative PCR nasopharyngeal swab and 50 as control group (uninfected COVID-19) from the Medical staff and the relatives, during the period from December/ 2020 to February / 2021. Testosterone hormone level were measured for each male, level of COVID-19 anti-nucleocapsid IgG was estimated and designed as selection criteria for recovery from COVID-19. Pearson’s correlation coefficient and A stepwise method in linear regression statistic test was applied to detect the association of testosterone hormone level with zinc and ROS. The mean and standard deviation level of studied parameters are differ between cases of current studying;recovering COVID-19 males and control group then compared with normal value of each test. The levels of COVID-19 anti-nucleocapsid IgG increase among recovering males compared with control group, statistically highly-significant (P-value = 0.00), as well oxidative stress among cases recovered from Covid-19 compared with level of control are statistically highly-significant (P-value= 0.00), while levels of zinc are decreased among cases studied compared with control group, this differences was highly-significant (P-value = 0.00). In conclusion, the most factors affecting Testosterone hormone level identified in the study are Zinc, ROS

11.
HTS Teologiese Studies / Theological Studies ; 78(4), 2022.
Article in English | Scopus | ID: covidwho-1954237

ABSTRACT

Tourism, as an industry, has become one of the most dynamic sectors of the world economy these days and has specific features that are different from other industries. In the tourism industry, production and consumption points occur spatially at the same time. In addition, the tourism industry contributes to the economic growth of developed regions and can simultaneously distribute the wealth created geographically. It is notable that the coronavirus disease 2019 (COVID-19) pandemic has caused many challenges in the tourism industry regarding the presence of tourists in tourism centres and the closing of all tourism service chains, including food, entertainment, transportation and travel services worldwide. Tourism-related businesses, which are considered as invisible export and one of the engines of development and occupation, have been rendered obsolete. In other words, the businesses, as well as multiple units and activities in the related chain, have been damaged and employees of this industry have lost their jobs. This has led to the recession and regressive course of the developing and large industry of tourism in the world. It is worth noting that the tourism industry includes various sections, the most important of which is religious tourism. All religions in the world have different religious places, works, traditions and customs, which have become amongst the most important tourist attractions. Meanwhile, Muslims and the religion of Islam play a significant role in this branch of tourism. The Hajj, pilgrimage to holy places and the existence of mourning ceremonies or religious celebrations of Muslims are amongst the largest religious tourism events in the world. Given the importance of this issue, the present study aimed to evaluate the impact of the COVID-19 pandemic on religious tourism in Iraq in 2021. This field study was conducted on 4500 Muslim managers and staff of restaurants, hotels, grocery stores, clothing stores and souvenir shops around the holy shrines of imams and religious places in Karbala, Najaf, Kufa, Samarra and Kazemi. According to the results, the tourism of Iraq, which is mainly limited to Muslim religious sites in several major Iraqi cities, has also seen a decline in the number of religious tourists. The negative effects of COVID-19 on religious tourism have also been proved statistically by the Statistical Package for the Social Sciences (SPSS), as µ ≥ 3 has been counted in all indices. Contribution: Our findings offered new insights into the impact of COVID-19 on tourism, based on statistical analysis. In this study, the authors showed how COVID-19 affects various aspects of religious tourism, which has not been addressed in previous researches. © 2022. The Authors.

12.
INTELLIGENT AUTOMATION AND SOFT COMPUTING ; 35(1):163-180, 2023.
Article in English | Web of Science | ID: covidwho-1939715

ABSTRACT

The numbers of cases and deaths due to the COVID-19 virus have increased daily all around the world. Chest X-ray is considered very useful and less time-consuming for monitoring COVID disease. No doubt, X-ray is considered as a quick screening method, but due to variations in features of images which are of X-rays category with Corona confirmed cases, the domain expert is needed. To address this issue, we proposed to utilize deep learning approaches. In this study, the dataset of COVID-19, lung opacity, viral pneumonia, and lastly healthy patients' images of category X-rays are utilized to evaluate the performance of the Swin transformer for predicting the COVID-19 patients efficiently. The performance of the Swin transformer is compared with the other seven deep learning models, including ResNet50, DenseNet121, InceptionV3, EfficientNetB2, VGG19, ViT, CaIT, Swim transformer provides 98% recall and 96% accuracy on corona affected images of the X-ray category. The proposed approach is also compared with state-of-the-art techniques for COVID-19 diagnosis, and proposed technique is found better in terms of accuracy. Our system could support clinicians in screening patients for COVID-19, thus facilitating instantaneous treatment for better effects on the health of COVID-19 patients. Also, this paper can contribute to saving humanity from the adverse effects of trials that the Corona virus might bring by performing an accurate diagnosis over Corona-affected patients.

13.
2nd International Conference on Digital Futures and Transformative Technologies, ICoDT2 2022 ; 2022.
Article in English | Scopus | ID: covidwho-1922690

ABSTRACT

In recent years, the rapid growth of data in healthcare has prompted a lot of interest in artificial intelligence (AI). Powerful AI algorithms are essential for extracting information from medical data and assisting clinicians in establishing quick and accurate diagnoses of a variety of ailments. In the current COVID-19 outbreak, critically ill patients were intubated and various medical tubes, including an endotracheal tube (ETT), were implanted to protect the airways. The Nasogastric tube (NGT) is used for feeding, whereas the Central Venous Catheter (CVC) is utilized for a variety of medical operations. The adoption of medical protocols by doctors to ensure proper tube installation is a major issue. Manual examination of CXR pictures takes time and frequently leads to misinterpretation. This research aims to create an Automated Medical Tube Detection System that can detect misplaced tubes from chest x-rays (CXR) using deep learning. As a result, using chest x-rays to detect poorly positioned tubes can save lives. On CXR the proposed CNN-based EfficientNet architecture efficiently detects and classifies incorrectly positioned tubes. After detailed experimentation, we were able to achieve 0.95 average area under the ROC curve (AUC). © 2022 IEEE.

14.
2nd International Conference on Computer Science and Engineering, IC2SE 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1922620

ABSTRACT

The Pandemic caused due to COVID-19 has overweighed the current healthcare system and made us realize that how unaware we were of our health. Although lots of rational and harsh measured were taken to curb the spread of COVID-19 but still we lost millions of lives. During this pandemic technology played a vital role ranging from the invention of vaccine to remotely monitoring the usage with the help of IoT. Among several emerging technologies wearable smart devices were burgeoning as they are also powered by IoT now. Wearable devices are being used in different scenarios ranging from tracking and monitory infected patients to utilize the data for policy making. Proposed is a framework of an ecosystem "AWARE"which comprises of a smart band with advanced PPG and EEG sensors to detect Heart rate, Heart rate Variability, Respiration rate, SpO2, Step and Sleep data. The sensor data will be transferred to the AWARE application on host mobile through BLE and from mobile the user data it will be transferred to AWARE cloud for pre and post processing using Machine Learning algorithms. AWARE can used for monitoring and detection of health anomalies and diseases such as COVID-19 or chronic lifestyle diseases. AWARE works on a multi-Tenancy cardinality framework were the group (i.e., kids, elders, domestic worker) users can share the cloud storage and receive customized notifications. Also, the group manager (i.e., father, employer) will be notified in case of emergencies. Cloud data can be accessed by the users through dashboards. Government authorities can also access user data through APIs. Wearables are widely accepted these days due to its less intrusiveness. Although some professionals are skeptical of these devices, but the advantages are far beyond the minor pitfalls. In fact, several countries have already implemented wearables devices as the primary medium of COVID-19 detection, monitoring. © 2021 IEEE.

15.
Support Care Cancer ; 30(9): 7665-7678, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-1888882

ABSTRACT

PURPOSE: Telemedicine use during the COVID-19 pandemic among financially distressed patients with cancer, with respect to the determinants of adoption and patterns of utilization, has yet to be delineated. We sought to systematically characterize telemedicine utilization in financially distressed patients with cancer during the COVID-19 pandemic. METHODS: We conducted a cross-sectional analysis of nationwide survey data assessing telemedicine use in patients with cancer during the COVID-19 pandemic collected by Patient Advocate Foundation (PAF) in December 2020. Patients were characterized as financially distressed by self-reporting limited financial resources to manage out-of-pocket costs, psychological distress, and/or adaptive coping behaviors. Primary study outcome was telemedicine utilization during the pandemic. Secondary outcomes were telemedicine utilization volume and modality preferences. Multivariable and Poisson regression analyses were used to identify factors associated with telemedicine use. RESULTS: A convenience sample of 627 patients with cancer responded to the PAF survey. Telemedicine adoption during the pandemic was reported by 67% of patients, with most (63%) preferring video visits. Younger age (19-35 age compared to ≥ 75 age) (OR, 6.07; 95% CI, 1.47-25.1) and more comorbidities (≥ 3 comorbidities compared to cancer only) (OR, 1.79; 95% CI, 1.13-2.65) were factors associated with telemedicine adoption. Younger age (19-35 years) (incidence rate ratios [IRR], 1.78; 95% CI, 24-115%) and higher comorbidities (≥ 3) (IRR; 1.36; 95% CI, 20-55%) were factors associated with higher utilization volume. As area deprivation index increased by 10 units, the number of visits decreased by 3% (IRR 1.03, 95% CI, 1.03-1.05). CONCLUSIONS: The rapid adoption of telemedicine may exacerbate existing inequities, particularly among vulnerable financially distressed patients with cancer. Policy-level interventions are needed for the equitable and efficient provision of this service.


Subject(s)
COVID-19 , Neoplasms , Telemedicine , Adult , Cross-Sectional Studies , Humans , Neoplasms/therapy , Pandemics , Telemedicine/methods , Young Adult
16.
Revue Internationale et Strategique ; 125(1):143-151, 2022.
Article in French | Scopus | ID: covidwho-1810390

ABSTRACT

The deferral of the 12th ministerial conference (CM-XII) of the World Trade Organization (WTO), initially scheduled for December 2021, revives the dual crisis of efficiency and legitimacy of the multilateral trade system, as well as of the organisation itself. The Doha Development Agenda (DDA) model, launched in 2001 and based on mercantilist growth strategies with special and differentiated treatment depending on the countries' level of development, appears less and less operational. Indeed, the WTO has to deal with new balances of wealth and power in a changing international economy. This article aims to outline the potential trajectories of the multilateral trading system by first reviewing the history of the DDA and the preparatory process for the CM-XII, and then focusing on what they reveal about the international economic relations and the prospects for the evolution of multilateral trade cooperation in times of Covid-19 pandemic. © 2022 Institut de Relations Internationales et Strategiques. All rights reserved.

17.
Turkish Online Journal of Distance Education ; 23(2):140-152, 2022.
Article in English | Web of Science | ID: covidwho-1801662

ABSTRACT

To assess the patterns of social media uses and their impact on the learning of male medical students during the COVID-19 pandemic. A cross-sectional descriptive study was conducted from March to May 2020 at the College of Medicine, University of Bisha (UBCOM) in Saudi Arabia. A validated questionnaire was used to collect data from the students at first year, pre-clerkship and clerkship levels about the types, patterns and benefits of social media usage in their learning. A five-Likert scale was used to measure the students' responses. Descriptive statistics and ANOVA tests were used for data analysis. Of the 203 students enrolled, 89.2% (n=181) were responded. Most students commonly used Twitter (75.1%), followed by YouTube (52.5%) and Facebook (24.3%). The highest usage of Twitter was found among clerkship students (85.1%) compared to first-year (76.2%) and pre-clerkship students (69.6%), with no significant differences (p = 0.133). About 38.7% of students spent over 10 hours per week on social media and pre-clerkship students being the highest group (43.5%). Most students (67.9%) showed that social media enhance learning activities, 65.2% are interested in using social media in their learning and 64.1% suggested that their inappropriate use consumes time. We concluded social media become interactive tools of learning in medical schools during the urgent situation such as the COVID-19 pandemic. Such findings highlighted the benefits of considering social media inclusion when designing medical curricula.

18.
Pakistan Journal of Medical and Health Sciences ; 6(1):1054-1057, 2022.
Article in English | EMBASE | ID: covidwho-1772277

ABSTRACT

A cluster of atypical pneumonia cases were reported in Wuhan china at the end of 2019. The disease was subsequently named covid-19. Later on it spread across the globe and WHO declared it as greatest pandemic of 21st century. Previous studies show that majority of the patients have hyponatremia, hypokalemia and hypochloremia. Recent study also suggests that the value of D-Dimer, ferritin and troponin I increasewhile O2 saturation drops in covid-19 patients.A cross sectional observational study was carried out in Peshawar Pakistan. A total of 195 patients above 18 years of age, confirmed through real time PCR were studied. Most of the patients have normal levels of electrolytes (Reference range of sodium 135-150mmol/L, potassium 3.5-5.1mmol/L, chloride 96-112mmol/L)while the patients with abnormal levels includedhyponatremic patients (having sodium level less than 135mmol/L), hyperkalemic patients (having potassium level higher than 5.1mmol/L) and hypochloremic patients (having chloride level less than 96mmol/L). The abnormal level of electrolytes is due to renal abnormalities. An association of O2 saturation exists with ferritin and D-Dimer. The level ofTroponin I raisestwofold in COVID-19 patients, which is an important circulatory biomarker associated with myocardial injury.

19.
Open Forum Infectious Diseases ; 8(SUPPL 1):S275, 2021.
Article in English | EMBASE | ID: covidwho-1746652

ABSTRACT

Background. Guidelines recommend use of tocilizumab (TCZ), an inhibitor of pro-inflammatory IL-6 signaling, for hospitalized patients with progressive severe or critical Coronavirus disease 2019 (COVID-19). The incidence of infectious complications following the use of TCZ for COVID-19 has not been well-described. Methods. We conducted a retrospective, observational matched cohort study of severely ill, hospitalized adult patients with confirmed COVID-19 who were treated with TCZ between 2/24/2021 and 6/1/2021. The intervention group, comprised of patients who received a single dose of TCZ, was matched based on c-reactive protein (CRP) and fraction of inspired oxygen (FiO2) with a control group who did not receive TCZ, and were hospitalized between 10/12/2020 and 3/6/2021. The primary outcome of the study was diagnosis of a bacterial or fungal infection after day 3 of the index hospitalization. Secondary outcomes included all-cause mortality during the study period and length of stay. Results. 75 patients who received TCZ were identified during the study period, and matched 1:1 with 75 control patients. Baseline CRP and FiO2 were similar between groups, while the median age in the TCZ group was younger (61 versus 71 years), reflecting the epidemiology of the outbreak during the TCZ and control study periods. 15 bacterial and fungal infections were identified in the TCZ group (20.0%) and 4 (5.3%) infections in the control group (p = 0.012). The majority of infections in both groups were bacterial, with a disproportionate number of bloodstream infections in the TCZ group [7 (9.3%) vs 2(2.6%);p = 0.166]. 28 patients (37.3%) died in the TCZ group compared to 39 (52.0%) in the matched control (p = 0.068). Median time to discharge was similar between TCZ and control patients (11 versus 12 days;95% CI -2,2). Conclusion. Secondary infections in adult patients with severe and critical COVID-19 were more common in patients who had received TCZ. Prospective studies are needed to confirm and further describe this association.

20.
15th International Conference on Open Source Systems and Technologies, ICOSST 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1735810

ABSTRACT

Novel coronavirus (COVID-19) is a hazardous virus. Initially, detected in China and spread worldwide, causing several deaths. Over time, there have been several variants of COVID-19, we have grouped all of them into two major categories. The categories are known to be variants of concern and variants of interest. Talking about the first of these two, it is very dangerous, and we need a system that can not only detect the disease but also classify it without physical interaction with a patient suffering from COVID-19. This paper proposes a Bag-of-Features (BoF) based deep learning framework that can detect as well as classify COVID-19 and all of its variants as well. Initially, the spatial features are extracted with deep convolutional models, while hand-crafted features have been extracted from several hand-crafted descriptors. Both spatial and hand-crafted features are combined to make a feature vector. This feature vector feeds the classifier to classify different variants in respective categories. The experimental results show that the proposed methodology outperforms all the existing methods. © 2021 IEEE.

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