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Mental health issues have become a growing public health concern around the world, particularly during the COVID-19 pandemic and the MCO. Therefore, this study aims to determine the level of anxiety and depression as well as to compare the anxiety and depression scores among the final-year undergraduate Health Sciences and Accountancy students at the UiTM during the MCO. Final-year students from the faculties of health sciences and accountancy have been given a set of study questions. Students were instructed to complete all questions using the Google Form. Out of 177 students who participated in the study, 52 (48.6%) Health Sciences students suffered from anxiety, and 25 (23.3%) suffered from depression. Meanwhile, 29 (41.4%) of accountancy students were anxious, and 15 (21.4%) were depressed. At UiTM Puncak Alam, Selangor, more than one third of the Accountancy and Health Sciences students were vulnerable to anxiety and sadness during the MCO. The findings also revealed that the mean anxiety score is significantly different between two-course groups (Health Sciences and Accountancy) students, t(170.78)=2.021, (p=0.02). This study provides authorities with information about university students' mental health, particularly during the MCO, in order to facilitate further research and useful information. © 2023,Asian Journal of University Education. All Rights Reserved.
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Introduction: Longitudinal individual response profiles could exhibit a mixture of two or more phases of increase or decrease in trend throughout the follow-up period, with one or more unknown transition points (changepoints). The detection and estimation of these changepoints is crucial. Most of the proposed statistical methods for detecting and estimating changepoints in literature rely on distributional assumptions that may not hold. In this case, a good alternative is to use a robust approach;the quantile regression model. There are methods in the literature to deal with quantile regression models with a changepoint. These methods ignore the within-subject dependence of longitudinal data. Methods: We propose a mixed effects quantile regression model with changepoints to account for dependence structure in the longitudinal data. Fixed effects parameters, in addition to the location of the changepoint, are estimated using the profile estimation method. The stochastic approximation EM algorithm is proposed to estimate the fixed effects parameters exploiting the link between an asymmetric Laplace distribution and the quantile regression. In addition, the location of the changepoint is estimated using the usual optimization methods. Results and discussion: A simulation study shows that the proposed estimation and inferential procedures perform reasonably well in finite samples. The practical use of the proposed model is illustrated using COVID-19 data. The data focus on the effect of global economic and health factors on the monthly death rate due to COVID-19 from 1 April 2020 to 30th April 2021. the results show a positive effect on the monthly number of patients with COVID-19 in intensive care units (ICUs) for both 0.5th and 0.8th quantiles of new monthly deaths per million. The stringency index, hospital beds, and diabetes prevalence have no significant effect on both 0.5th and 0.8th quantiles of new monthly deaths per million. Copyright © 2023 Ibrahim, Gad and Abd-Rabou.
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Background Infection with SARS-CoV-2 is a leading source of illness and death in the world. Millions of people contract SARS-CoV-2 every day as the incidence of infection rises. The mortality rate is mostly attributed to respiratory failure. Many studies have been carried out to identify biomarkers that can be used in the early detection of at-risk patients. CRP is a sensitive inflammatory biomarker;however, it can be measured by simple, inexpensive methods that are widely available in hospitals. Therefore, it was selected for this clinical trial. Methods This retrospective cohort analysis included 100 patients who were accepted to El-Obour Ain Shams University Specialized Hospital for Isolation between May and October 2020. Admission CRP was investigated, and data were analyzed in relation to severity and mortality. Results Regarding history, older patients or those who had been diagnosed with hypertension, diabetes mellitus, chronic hepatic diseases, or active cancer have been statistically more prone to mortality. Concerning the laboratory investigations, those who did not survive had significantly lower haemoglobin levels and a higher TLC count. In addition, serum ferritin and D-dimer levels were significantly higher in the non-survivors. As regards CRP, the non-survivor group had significantly higher levels, with a cutoff value of >129 mg/l to predict mortality. It has also been correlated with severity in terms of need for ICU admission and need for respiratory support, with a cutoff value of >55.3 mg/L. Conclusion CRP can be used as a prognostic biomarker in patients with SARS-CoV-2 infection as it is a simple and effective predictor.
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The COVID-19 outbreak has been affecting the health of people all around the world. With the number of confirmed cases and deaths still rising daily, so the main aim is to detect positive cases as soon as and provide them with the necessary treatment. The utilization of imaging data including chest x-rays and computed tomography (CT) was proven that is would be beneficial for quickly diagnosing COVID-19. Since Computerized Tomography provides a huge number of images, recognizing these visual traits would be difficult and take enormous amounts of time for radiologists so automated diagnosis technologies including deep learning (DL) models are recently for COVID-19 screening in CT scans. This review paper presents different researches which used deep learning approaches including various models of convolutional neural networks (CNN) used in image classification tasks well, and large training, like ResNet, VGG, AlexNet, LeNet, GoogleNet, and others for COVID-19 diagnosing and severity assessments using chest CT images. As a result, automated COVID-19 analysis on CT images is essential to save medical personnel and essential time for disease prevention. © 2023 Institute of Advanced Engineering and Science. All rights reserved.
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People and Children's infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been increasing dramatically. COVID-19 precaution measures are essential for highly susceptible groups. However, it was not known previously to what extent chronic disease patients were perceived to know about the efficacy of prevention measures. Novel coronavirus-2019 is a highly infectious disease that caused a global pandemic around the world. Saudi Arabia is one of the countries that initiated early vaccination programs despite the global challenges concerning the availability of COVID-19 vaccines. Massive vaccination campaigns have been undertaken in the country;however, negative perception and hesitancy toward vaccines may exist which could reduce public response to vaccination especially the children. Further, studies evaluating the current perception and attitude toward COVID-19 vaccines are scarce especially the children. People's and Children's perceptions of pandemic-associated risk are key factors contributing to increased public participation in disease preventive measures. Aim of the study: To assessment of the knowledge of The Risk Perceptions Attitude About The Vaccination Against Covid-19and communication practices of vaccinate about Covid-19 among Children's Saudi in Makkah Al-Mokarramah, Saudi Arabia2022. Method(s): Cross sectional study, was utilized in the present study among secondary school children and conducted from January to April 2022. conducted among Saudi Arabia primary health care center and secondary school children in Makkah Al-Mukarramah 2022. Our total participants were(200). Result(s): Regarding Attitude of the participant toward symptoms of the Vaccinate against COVID-19 Show that is a significant correlation in attitude were p-value =0.001 and X2 63.64, the majority of participant in weak attitude were(57.64%) followed by average were(32.0%), regarding the practices Show that is a significant correlation in practices were p-value =0.001 and X2 85.72. Conclusion(s): During the COVID-19 pandemic, communications designed to promote the adoption of preventive behaviors should focus on increasing the perception of seriousness. Health education programs that are tailored to various socio demographic categories, to improve public awareness, perceptions, and attitudes, are vital for increasing the adoption of outbreak preventive measures. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.
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In this study, we assess the applicability and usefulness of a particular theoretical framework for qualitative analysis of communicative strategies in discourses from beyond the English language. The theory in question is Cialdini's model of persuasion (and the related concept of pre-suasion). We present an operationalisation of this framework in terms of concrete linguistic features, which is implemented using the computer-assisted methods of corpus linguistics. As a case study, we explore a particular type of Arabic-language online public discourse surrounding an issue of pressing contemporary concern, namely the COVID-19 Pandemic. Specifically, we use a large collection of texts produced by the Ministry of Health of Saudi Arabia via the medium of the Ministry's official Twitter account. The tweets in question were produced in the context of a campaign to persuade the public to modify their behavior to comply with policies on protective measures. While the use of corpus-assisted linguistic approaches to examine public discourses around socially or culturally prominent issues is well-developed in the Anglosphere, it remains much more rarely utilized in the Arab World context, and especially in application to discourses in the Arabic language itself. In addition to the contribution arising from the improvements generated in our understanding of the particular issue at hand, this paper aims to contribute to the broader field of Arabic linguistics by modeling a suitable approach—albeit one whose use we show to be subject to some complicating factors—to address other questions in the study of persuasive language in Arabic. Copyright © 2022 Ibrahim, Abaalalaa and Hardie.
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This article aims to determine the vulnerability of migrant populations to COVID-19. Between March 2020 and November 2021, informal interviews with respondents who were stranded in various parts of the world were conducted through Skype and WhatsApp. COVID-19 endangers millions of individuals who were stranded between their homes and their destinations — and who were compelled to reside in overcrowded accommodation where the ideas of "stay home," "keep safe," and "social distancing" have little significance. © 2022, Busan University of Foreign Studies. All rights reserved.
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Malaysians' overall well-being, particularly in urban areas, has been seriously affected physically and emotionally due to the series of imposed lockdowns in the country. The number of mental health problems such as depression, anxiety, and loneliness has increased tremendously during the lockdown period. Various studies suggest that these mental health issues could be coped with if people are allowed to access urban greeneries and public green spaces during the pandemic. However, the degree to how adequate existing green areas are to fulfil an urban community's needs with strict social distancing compliance is still vaguely interpreted in the literature. It is still arguable that the current 10 per cent green area requirement is still relevant to the current context of the COVID-19 pandemic. This study aims to determine the sufficient amount of green areas for people's well-being during the pandemic, based on the local population, accessibility to green areas, and compliance with the new norm of social distancing by a minimum of one meter. Therefore, an urban neighbourhood in Iskandar Puteri, Johor, Malaysia was selected and simulated using GIS spatial analysis based on the highlighted parameters. As a result, the study found that the current size of existing green areas in the neighbourhood is insufficient in terms of compliance with the parameters, especially Malaysia's social distancing requirements. This study could provide a platform for future planning to include pandemic risk reduction into urban planning policies, especially in the context of Malaysia, to cater to future uncertainties (C) 2022 Penerbit UTM Press. All rights reserved
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AIM: To compare the clinical outcomes of conventional and digital implant impressions in all-on-4 mandibular implant prostheses. MATERIALS AND METHODS: Fifty-six participants were randomly stratified into two control groups (Axial Conventional Impression Group [ACIG] and Tilted Conventional Impression Group [TCIG]), and two test groups (Axial Digital Impression Group [ADIG] and Tilted Digital Impression Group [TDIG]). Conventional pick-up and digital impressions were made for each group, respectively. Participants in ACIG and ADIG received four axial implants, and those in TCIG and TDIG received two anterior axial and two distal tilted implants. All participants received all-on-4 mandibular prostheses and maxillary complete dentures. Implant survival, prosthetic complications, and marginal bone loss were recorded at 6, 12, and 24 months. Data were statistically described in terms of mean +/- standard deviation. RESULTS: After 24 months, the implant survival rate was 100%. A significant difference in bone loss was shown between ACIG and ADIG at 6, 12, and 24 months, with P = 0.647, 0.821, and 0.505, respectively. An insignificant difference in bone loss was shown between TCIG and TDIG at 6 ,12, and 24 months, with P = 0.671, 0.935, and 0.687, respectively. No significant difference was shown in prosthodontic complications between all groups throughout the follow-up period. CONCLUSIONS: The digital impressions showed clinically better implant survival, stable peri-implant marginal bone level, and reasonable prosthodontic complications. The present study represents a steppingstone and proof of concept that supports the routine clinical use of digital impressions, especially in a post-COVID-19 world.
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Background/Case Studies: Massive transfusion protocols (MTPs) are designed to rapidly provide large quantities of cellular and liquid blood products, in a predetermined ratio, to massively bleeding patients. Cold-stored, low-titer group O whole blood (LTOWB) has been utilized extensively for massive transfusion in the military and is gaining acceptance in the civilian setting. This study aims to characterize the effect on AB plasma inventory and MTP activation workflow efficiency metrics following LTOWB inclusion at an academic level I trauma center. Study Design/Methods: Data from adult trauma MTP activations post-inclusion of LTOWB in the protocol were retrospectively analyzed. Upon implementation, and depending on availability, up to 4 LTOWB units were included in the 1st cycle of adult trauma MTPs with the remaining units comprising group O packed red blood cells (pRBC) and AB plasma components in a 1:1 ratio, e.g. 2 LTOWB, 2 pRBC, and 2 plasma units. As available, and until the patient's ABO group was determined, additional LTOWB units could be issued in subsequent cycles to a cumulative maximum of 8. A single donor apheresis platelet was issued with every other cycle beginning on the 2nd cycle and a 5-pack of cryoprecipitate was issued with every other cycle beginning on the 5th cycle. AB plasma utilization and time to first cycle pack being ready for pick-up were compared between trauma MTP activations with or without LTOWB availability. Mean transfused units for each blood component type were also compared. Results/Findings: Ninety-seven trauma MTPs were analyzed. A total of 129 units of LTOWB were transfused to 49 (50.5%) MTP activations, with a theoretical AB plasma savings of 129 units. Among trauma MTP activations including LTOWB, 18 (36.7%) received only one unit while 6 (12.2%) received 5 units or more LTOWB. Mean numbers of transfused units per patient of pRBC, plasma, platelets, and cryoprecipitate in patients who received LTOWB was generally less compared to those who received component therapy only (8.5;7.7;10.2 and 2 versus 8.4;9.6;14 and 3.8 respectively). Time to first cycle pack ready for pickup was 0.4 minutes less in MTP activations including LTOWB as compared to those prepared with component therapy only. Conclusions: These data demonstrate that inclusion of LTOWB for adult trauma MTP activations can result in both theoretical AB plasma unit savings as well as improve time to product availability for clinical teams. Blood collection constraints, exacerbated with the COVID-19 pandemic, reinforce the need for transfusion services to optimize universal product utilization. Addition of LTOWB for adult trauma MTP activations may prove a tool in that regard.
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Background: A novel human coronavirus, also known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV2), emerged in China in late 2019 and has since claimed more than one million lives. COVID-19 infection is perceived to be seasonally recurrent and a rapid non-invasive biomarker to accurately diagnose patients early-on in their disease course will be necessary to meet the operational demands for COVID-19 control in the coming years.Objective: To evaluate the role of exhaled breath volatile breath biomarkers in identifying patients with suspected or confirmed COVID 19 infection, based on their underlying reverse transcriptase polymerase chain reaction (RT-PCR) status. Methods: We conducted an observational study at Glenfield Hospital, Leicester, United Kingdom, recruiting adult patients with suspected or confirmed COVID19 pneumonia. Breath samples were collected using a standard breath collection bag, modified with appropriate filters to comply with local infection control recommendations and samples were analysed using gas chromatography mass spectrometry (GC-MS).Findings: 81 patients were recruited, of whom 52/81 (64%) have subsequently tested positive for COVID19. A LASSO regression analysis, with the dependent variable as PCR status was run. A set of seven features were extracted that had non-zero regression coefficients in at least 70 out of 100 runs of 10-fold cross validation. Compound identities were confirmed using the Metabolomics Standards Initiative (MSI). These were benzaldehyde, 1-propanol (MSI level 1), 3,6-methylundecane (MSI level 2), camphene and beta-cubebene (MSI level 1 and 2 respectively). Iodobenzene was also extracted, likely of exogenous origin, and an unidentified compound. A logistic regression model was fitted with the dependent variable as PCR status and independent variables as the seven features selected by the LASSO model. Partial Least Squares Discriminant Analysis (PLSDA) and Principal Component Analysis (PCA) were applied to the seven features, with the dependent variable as PCR status. The AUC for the first discriminant function score was 0.836 (95% CI: 0.745-0.928), Sensitivity was 0.68 (95% CI 0.551-0.809), Specificity was 0.857 (95% CI 0.728-0.987), positive predictive value (PPV) was 0.895 (95% CI 0.797-0.992) and negative predictive value (NPV) was 0.6 (95% CI 0.448-0.752). The AUC for the first PCA was 0.799 (95% CI: 0.698-0.900), Sensitivity was 0.7 (95% CI 0.573-0.827), Specificity was 0.786 (95% CI 0.634-0.938), PPV was 0.854 (95% CI 0.745-0.962) and NPV was 0.595 (95% CI 0.436-0.753).Conclusions: breath analysis has promising combined sensitivity and specificity in detecting COVID19, raising the possibility of mass rapid testing, pending external validation of the identified biomarkers.
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Besides its effects on physical health, the coronavirus disease 2019 (COVID-19) pandemic has resulted in adverse consequences on mental health of health-care workers. Several factors such as safety concerns and fear of infecting self or family members, social isolation measures, strict infection control procedures, lack of protective measures, exhaustion due to increased duration of working, and seeing patients die or colleagues infected can contribute to the development of mental health problems in health-care workers during the current COVID-19 pandemic. Some health-care staff including nurses, advanced practice providers, frontline health-care workers, and health-care workers who have children are more vulnerable to these mental health problems. Prevention of infection and staff burnout in health-care workers, provision of a timely mental health care, and social support are among the most important measures to provide a mental health care for health-care workers during the current COVID-19 pandemic.
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Background The Coronavirus Disease-19 (COVID-19) pandemic continues to cause significant disruption worldwide. Within the UK there were considerable adjustments in all healthcare settings to ensure appropriate management of patients affected by COVID-19, with consequent disruption to existing services. Lung cancer is associated with a high mortality rate, not least because there are often delays in diagnosis. We examined referrals before and during the COVID-19 pandemic to determine whether this affected the number of patients seen and the speed to diagnosis. Methods We compared referrals to our Lung Cancer Service during the four months prior to and immediately following the onset of the UK COVID-19 pandemic in March 2020. We collected data relating to the numbers and origins of referrals, as well as the time intervals at different stages of our diagnostic pathway. Results Our service received fewer referrals following the onset of the pandemic, with a mean of 97 patients per month from November 2019 to February 2020, compared to 79 patients per month between March and June 2020. Urgent cancer referrals from General Practitioners ('twoweek-wait') were reduced (50% to 44%) during the pandemic. A greater proportion of patients presented via alternative pathways, including A&E, suggesting a later presentation. The gender of patients referred remained similar between both timeframes, although during the COVID-19 pandemic, the mode average age was slightly younger at 73 years (79 years previously), with an age range 29-97 years (21-93 years pre-COVID-19). After receiving a referral, the time to first review remained stable (98% vs 99%). The mean time from referral to diagnosis remained 14 days. 91% of patients received a lung cancer diagnosis within 28 days of referral, despite the COVID-19 pandemic (94% previously). Conclusion Time to lung cancer diagnosis was not affected by changes to our clinical service during the COVID-19 pandemic. However, there was a significant reduction in the overall number of referrals (almost one fifth). We will monitor to review whether there is an increase in late presentations in the coming months due to delays in referral. The fear is that future increases in COVID-19 cases nationally will further delay these patients presenting.
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BackgroundThe Coronavirus Disease-19 (COVID-19) pandemic continues to cause significant disruption worldwide. Within the UK there were considerable adjustments in all healthcare settings to ensure appropriate management of patients affected by COVID-19, with consequent disruption to existing services.Lung cancer is associated with a high mortality rate, not least because there are often delays in diagnosis. We examined referrals before and during the COVID-19 pandemic to determine whether this affected the number of patients seen and the speed to diagnosis.MethodsWe compared referrals to our Lung Cancer Service during the four months prior to and immediately following the onset of the UK COVID-19 pandemic in March 2020. We collected data relating to the numbers and origins of referrals, as well as the time intervals at different stages of our diagnostic pathway.ResultsOur service received fewer referrals following the onset of the pandemic, with a mean of 97 patients per month from November 2019 to February 2020, compared to 79 patients per month between March and June 2020. Urgent cancer referrals from General Practitioners (‘two-week-wait’) were reduced (50% to 44%) during the pandemic. A greater proportion of patients presented via alternative pathways, including A&E, suggesting a later presentation. The gender of patients referred remained similar between both timeframes, although during the COVID-19 pandemic, the mode average age was slightly younger at 73 years (79 years previously), with an age range 29–97 years (21–93 years pre-COVID-19).After receiving a referral, the time to first review remained stable (98% vs 99%). The mean time from referral to diagnosis remained 14 days. 91% of patients received a lung cancer diagnosis within 28 days of referral, despite the COVID-19 pandemic (94% previously).ConclusionTime to lung cancer diagnosis was not affected by changes to our clinical service during the COVID-19 pandemic. However, there was a significant reduction in the overall number of referrals (almost one fifth). We will monitor to review whether there is an increase in late presentations in the coming months due to delays in referral. The fear is that future increases in COVID-19 cases nationally will further delay these patients presenting.