Australasian paediatric gastroenterologist practices of coeliac disease diagnosis before and during the COVID-19 pandemic.

AIM: To explore the perceptions and practices of Australasian paediatric gastroenterologists in diagnosing coeliac disease (CD) before and during the COVID-19 pandemic. METHODS: Paediatric gastroenterologists in Australasia were invited via email to complete an anonymous online questionnaire over a 2-week period in 2021. RESULTS: The questionnaire was completed by 39 respondents: 33 from Australia and six from New Zealand (NZ) equating to a 66% response rate. Thirty-four (87%) of the 39 respondents reported they currently practised non-biopsy diagnosis of CD in eligible children, while the rest diagnosed CD using biopsy confirmation only. All NZ respondents practised non-biopsy CD diagnosis. A majority of responders (76%) who practised non-biopsy CD diagnosis followed the 2020 European Society for Paediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN) guidelines. Twenty-two (56%) respondents reported that they started using a non-biopsy CD diagnosis protocol before the pandemic and did not change their practice during the pandemic, 10 (26%) started diagnosing non-biopsy CD during the pandemic, 5 (13%) stated their practices of CD were not impacted by the pandemic and 2 (5%) did not respond on whether the pandemic changed their practice. CONCLUSION: The majority of Australasian gastroenterologist respondents reported they routinely utilised the 2020 ESPGHAN diagnostic criteria in eligible children; half of them started prior to the pandemic and another quarter started this approach due to the pandemic. A minority of practitioners routinely rely only on biopsy confirmation to diagnose CD.

Prevalence, risk factors and sources of anxiety among Emergency Department healthcare workers in Pakistan during COVID-19 pandemic: A single center survey

COVID-19 has challenged the mental health of healthcare workers confronting it world-wide. Our study identifies the prevalence and risk of anxiety among emergency healthcare workers confronting COVID-19 in Pakistan. We conducted a cross-sectional survey in an Emergency Department using the Generalized Anxiety Scale (GAD-7), and questions about sources of anxiety. Of 107 participants, 61.7% were frontline workers. The prevalence of anxiety was 50.5%. Nonparametric tests determined that nurses, younger and inexperienced staff, developed significant anxiety. Multivariate ordinal regression determined independent risk factors for developing anxiety were younger age (OR 2.11, 95% CI 0.89-4.99) and frontline placement (OR 1.34, 95% CI 0.33-1.66). Significant sources of stress were fear of infecting family (P = 0.003), lack of social support when the health care providers were themselves unwell (P = 0.02) and feelings of inadequate work performance (P = 0.05). Our study finds that HCWs' anxiety is considerable. Appropriate measures for its alleviation and prevention are required. ©

Using a multidisciplinary, multi-method and collaborative research design to investigate the health communication power of the early childhood sector

This paper details the research design of a multidisciplinary, multi-method, collaborative research project investigating health communication from the experiences of the early childhood education (ECE) sector during the COVID-19 pandemic. With the rapidly evolving pandemic, the ECE sector was instantly tasked with expanding their required health practices to prevent the spread of infection. It was evident that the sector needed a system to communicate health advice in a timely, consistent and effective manner. Founded on a partnership model based on 'knowledge brokering' theory, this project demonstrates the value of a multidisciplinary research team collaborating with stakeholder organisations to investigate how COVID-19 health information traversed through complexities of organisational layers and diverse communities of families and staff. Detailing our data collection and analysis protocols, we conclude by outlining how our innovative research design is generating actionable and impactful recommendations for both the ECE and health sectors.

Diagnosis of COVID-19 infection using three-dimensional semantic segmentation and classification of computed tomography images

Coronavirus 19 (COVID-19) can cause severe pneumonia that may be fatal. Correct diagnosis is essential. Computed tomography (CT) usefully detects symptoms of COVID-19 infection. In this retrospective study, we present an improved framework for detection of COVID-19 infection on CT images;the steps include pre-processing, segmentation, feature extraction/ fusion/selection, and classification. In the pre-processing phase, a Gabor wavelet filter is applied to enhance image intensities. A marker-based, watershed controlled approach with thresholding is used to isolate the lung region. In the segmentation phase,COVID-19 lesions are segmented using an encoder- /decoder-based deep learning model in which deepLabv3 serves as the bottleneck and mobilenetv2 as the classification head. DeepLabv3 is an effective decoder that helps to refine segmentation of lesion boundaries. The model was trained using fine-tuned hyperparameters selected after extensive experimentation. Subsequently, the Gray Level Co-occurrence Matrix (GLCM) features and statistical features including circularity, area, and perimeters were computed for each segmented image. The computed features were serially fused and the best features (those that were optimally discriminatory) selected using a Genetic Algorithm (GA) for classification. The performance of the method was evaluated using two benchmark datasets: The COVID-19 Segmentation and the POF Hospital datasets. The results were better than those of existing methods. © 2021 Tech Science Press. All rights reserved.

Psychological impact of COVID-19 lockdown on general population of Hail, Saudi Arabia

Background: Pandemics are associated with anxiety, depression, and/or even death. The present study was planned to measure the psychological stress due to current pandemic-COVID19 amongst resident of Hail, Saudi Arabia. Method: It was a survey based cross sectional study. Non-Probability convenient sampling was used to collect the information from 240 respondents. Generalized Anxiety Disorder scale (GAD-7) was used as study tool. Data was displayed as number and percentages. Chi square test was used to measure inferential statistics. Results: More than 55% of study respondent reportedly found to have some level of anxiety during lockdown. However, nearly 35% had mild anxiety. Interestingly, statistically significant association was observed amongst, gender, level of education, Income, nationality, profession, place of resident, and age. Conclusion: The findings of present study may not be generalizable to Hail city. However, more than 50% of study respondent reported some sort of anxiety. Mild anxiety was most commonly reported. Level of anxiety was found to be statistically associated with various socio demographic variables. It is recommended to have further studies to measure the relationship of psychological stress on individuals of various backgrounds.