ABSTRACT
Objective: One of the potentially fatal consequences for diabetic patients is diabetic ketoacidosis acidosis (DKA), which is also linked to poor hospital outcomes. There is no much information in literature about COVID-19 and how it relates to other hospitalizations. The impact of COVID-19 on in-hospital mortality and other clinically relevant outcomes for DKA patients is being investigated for the first time in this study. Method(s): Patients admitted with a primary diagnosis of DKA with or without a subsequent diagnosis of COVID-19 Infection were found in the National Inpatient Sample (NIS) Database 2020. Patients were divided into two groups: those who have COVID-19 and those who don't. Univariate and multivariate logistic regression models were utilized to account for frequent confounders and assess the risk of mortality and in-hospital outcomes between the two groups. Result(s): The total of 110,130 DKA admissions were identified between Jan and Dec 2020. COVID-19 Infection was diagnosed in 2,504 patients (2.2%). The average age of the cohort sample was 35 years old, 51% were male, and 60% were white. The average length of stay (LOS) was 3 days, and the average total hospital charges were 33,132 US dollars. The total number of patients who died was 225 patients. When the two groups were compared, COVID-19 Infection was associated with an increased risk of in-hospital mortality among DKA patients (OR 5.3, 95% CI 1.7-15.9, p=0.003). COVID-19 patients had a higher risk of acute respiratory failure (OR 2.9, 95% CI 1.7-3.9, p< 0.001) and septic shock (OR 3.9, 95% CI 1.5-9.8, p=0.003). There was no significant difference between the COVID-19 and non-COVID-19 groups in the risk of acute coronary syndrome (OR 1.2, 95% CI 0.49-3, p=0.66), cardiac arrest (OR 2, 95% CI 0.5-7.9, p=0.31), hypokalemia (OR 1.14, 95% CI 0.92-1.4, p=0.214), deep vein thrombosis (OR 0.59, 95% CI 0.14-2.4, p=0.47), or pulmonary embolism (OR 3.6, 95% CI 0.84 - 15.4, p=0.083). COVID-19 patients had a longer mean LOS (4.2 vs 2.9 days, p< 0.001) and higher mean total hospital charges (41,216 vs 32,973 $, p=0.004). Discussion/Conclusion: Patients admitted with DKA and concomitant COVID-19 infection found to have a higher risk of in-hospital mortality and worse hospital outcomes, particularly acute respiratory failure and septic shock. In comparison to non-COVID patients, COVID-19 patients have a longer mean LOS and a higher mean of total hospital charges.Copyright © 2023
ABSTRACT
Background The annual Ashura pilgrimage is a mass Islamic gathering during which millions of worshippers converge in the city of Karbala in Iraq. We report on the incidence of the coronavirus disease 2019 (COVID-19) in Omani pilgrims returning from Karbala in the month of Muharram (August) 2021 during the COVID-19 pandemic. Methodology This is a retrospective study using an electronic, self-completed, and Arab-language survey, composed of 17 questions, that was distributed to all pilgrims returning from Karbala. Participation was voluntary, and consent with confidentiality was obtained. Data on the demographics including sex, COVID-19 vaccination record, type of vaccine, duration of stay, compliance with wearing a face mask, using hand sanitization, and polymerase chain reaction (PCR) results for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus before the departure from Oman, upon the return to Oman, and on the eighth post-quarantine day were collected. The responses were collected from the period between August 28, 2021, and September 25, 2022. Statistical association and analysis were performed using the Statistical Package for Social Sciences (SPSS) software (IBM SPSS Statistics, Armonk, NY). Results Out of 250 pilgrims, 139 responded to the survey. Fifty-two participants (37.4%) were males, and 87 (63.6%) were females. None of the pilgrims had positive SARS-CoV-2 PCR results before their departure from Oman. Only four pilgrims (2.9%) were detected positive on PCR by the end of a compulsory quarantine on the eighth day after arrival to Oman. No hospital admissions were recorded. The vast majority of the pilgrims were vaccinated with two doses of COVID-19 vaccination, while some few pilgrims were not vaccinated at all. Most of the pilgrims were also compliant with mask wearing, and just over half the pilgrims were compliant with hand sanitization. No significant statistical association was found between contracting SARS-CoV-2 virus infection and taking SARS-CoV-2 vaccination, the number of vaccination doses, having had COVID-19 before, wearing a mask, or compliance with hand sanitization. Conclusion The incidence of COVID-19 cases among pilgrims returning from Iraq during the COVID-19 pandemic was low. No significant difference was noted between pilgrims vaccinated and compliant with the protective measures and those who were not vaccinated or compliant. Herd immunity could be a possible explanation for the low incidence of COVID-19 infection. Larger studies are needed to investigate the incidence of COVID-19 in Ashura pilgrims.
ABSTRACT
The COVID pandemic has brought many changes to the field of education so that educators are asked to have learning innovations that can help learners meet learning goals. This study aims to develop a facilitation model to develop conscientizacao during the COVID pandemic. This facilitation model utilizes SIPEJAR in compiling learning tools according to the learner's learning needs. The research method used was adapted from the R2D2 development model which showed the results that the facilitation model had been developed in accordance with predetermined indicators and in accordance with the learner's learning needs. © 2022 IEEE.
ABSTRACT
Cataclysmic changes by the gradual spread of COVID-19 have triggered the interest of scientists, scholars, academicians, and linguists in analyzing the discourse related to the spread of the pandemic. The descriptions made by all of these scholars not only contribute to language with linguistic innovations but also cause the emergence of human attitudes and behaviours. At the same time, the issues raised through the language used during the challenging time of such crises shape and reveal several human schemas of language, discourse, society, and culture. Several studies on past situations of diseases and calamities have provided critical analyses of these schemas of difficult times in human history. Discourses through various linguistic practices in this regard play a crucial role in shaping and demonstrating the schemas of the crisis hit societies. Media discourse, specifically, has hidden powers to exercise, identify and report various socio-cultural issues. The current study focuses on finding the themes of socio-cultural attitudes and behaviours that emerged from newspaper editorials published in Pakistani newspapers in February, March and April, 2020. To achieve this goal, the corpus-driven analysis of 198 newspaper editorials having 215,842 words was conducted. The study revealed various themes that prevailed in this pre-vaccination period of COVID-19 in Pakistan. The themes included the metaphoric use of the language such as battle, corps and frontline;racism while naming the virus as China virus or Hazara virus;conspiracy theories assumed to be associated with COVID-19 spread i.e. suspected involvement of Bill Gates and the Centers for Disease Control (CDC), US and World Health Organization (WHO);negligence on the part of people;and criticism on government for health facilities and implications of globalization. It is concluded, based on these findings, that media representation of pre-vaccination phase of COVID-19 in Pakistan is loaded with unhealthy discourse which could have been avoided in order to shape positive attitudes and behaviours of the masses. © 2022, Penerbit Universiti Kebangsaan Malaysia. All rights reserved.
ABSTRACT
Background and Objective: Non-alcoholic fatty liver disease (NAFLD) is reported to be the only hepatic ailment increasing in its prevalence concurrently with both;obesity & Type 2 Diabetes Mellitus. Abdominal ultrasonography is done for NAFLD screening diagnosis which has a high monetary cost associated with it. • In the wake of a massive strain on global health resources due to COVID-19 pandemic, NAFLD is bound to be neglected and shelved. Machine learning is explored, here, to propose screening-diagnostic tools for NAFLD that can be easily deployed without the requirement of substantial resources and can provide instantaneous screening-diagnosis predictive results. Methods: The study takes in data from Huang BX et al. : 4053 subjects, 2436 men and 1617 women between 20 and 88 years of age, after excluding those patients that had a history of co-morbid conditions as well as those with a lack of hepatic ultrasonography data. The Graif’s criteria was adopted to diagnose Fatty liver disease on ultrasonography. Mljar, the current state-of-the-art automated ML zero-code machine learning web platform, was adopted with a ‘homogenous’ approach for the development of the models vis-à-vis the preprocessing & tuning protocols as well as system specifications so as to keep the model development bias to a minimum. The discriminative ability of the models were the primary outcome variables. The ‘Area under the receiver operating curve’ (AUROC) analysis was adopted to measure that ability. Results: All 8 of the algorithms, trained in accordance with the aforementioned Homogenous Development Framework, came out to have good discriminating ability to designate the dichotomous variable of interest. Random Forest came out to have the highest discriminating ability with a computation time of minutes 9 seconds. Out of the proposed models, K-Nearest Neighbor had the least AUC but a considerably less computation time of only 6 seconds. Conclusion: Our proposed models are the very first effort, to the best of our knowledge, to leverage the current state-of-the-art for autoML to develop machine learning models that are trained to have a good discriminating ability to predict NAFLD using only anthropometric measures. The proposed models neither require costly analysis so that variables, such as ultrasonographic signals, may be fed into them for training nor do they require considerably high computation time & resources to be deployed. A study comparing the presented models’ predicted diagnosis with an abdominal ultrasound diagnosis for NAFLD, the predictions subsequently assessed against hepatic biopsy, is proposed to be in order to explore the presented models’ potential to replace abdominal ultrasound as a cost-effective screening diagnostic modality for NAFLD. Keywords: Non-alcoholic fatty liver disease, Machine learning, prediction, abdominal ultrasonography, Diabetes mellitus Abbreviations: NAFLD: Non-alcoholic fatty liver disease;autoML: Automated machine learning Funding and Conflicts of Interest None