ABSTRACT
Background COVID-19 caused by SARS-CoV-2 is a worldwide epidemic. Children are less commonly infected and have less severe symptoms than adults. However, they are at risk for COVID-19-associated severe sickness and hospitalization. The duration of stay is a major driver of effective health treatment during hospitalization; thus, it is only logical to attempt to comprehend the factors influencing the length of stay (LOS) for these patients, particularly in light of the ongoing pandemic caused by the new SARS-CoV-2 virus. As predictors of hospital LOS, several variables, including age, gender, disease severity, hospital mortality, insurance type, and hospital location, have been discovered. In our study, we focused on the severity of the patient's condition, the presence of comorbidities, and the necessary therapeutic regimen to predict the duration of stay. This study aimed to answer the following questions: If a patient has comorbidity and has COVID-19 requiring hospital treatment, will the patient's comorbidity elongate the duration of stay at the hospital for further management in the pediatric age group? What are the risk factors that play a significant role in the hospital stay duration in pediatrics? Methodology We gathered data from 100 hospitalized children aged up to 14 years who tested positive for COVID-19, which was not specific to variants of SARS-CoV-2, over 24 months (February 2020-February 2022) at Queen Rania Al Abdullah Hospital for Children, one of the Health Care Accreditation Council accredited facilities. Clinical symptoms, signs, oxygen demand, imaging study results, laboratory data, and usage of corticosteroid and antiviral medication were all taken from patients' medical records. There were no limitations in taking the sample of patients. All patients in the duration mentioned were included. Results Clinical data of 100 COVID-19-positive pediatric patients were analyzed; 52% of the patients had associated chronic illnesses, while 48% were medically free. The longest duration of LOS was 28 days, the shortest was one day, the median was eight days, and five days was the most frequent among patients owing to 21% of patients, using mean descriptive statistics. We compared LOS to having or not having comorbidities. The mean LOS of patients with the comorbid disease was 6.15 days, with a maximum of 28 days, while for patients without chronic illnesses, the mean was 4.81 days with a maximum of 14 days. The significance was 0.07. Our results also showed a significant correlation between using steroids and LOS, as it had an advantageous effect by decreasing it with a significance value of 0.04. Having abnormal findings on chest computed tomography (CT) scan was also associated with increased LOS with a significant value of 0.00. Conclusions According to our research, there was no direct association between comorbidity and hospital LOS, which is counterintuitive, as it was influenced by multiplayers of variables such as using steroids, which decreased the LOS, and abnormal findings on chest CT, which resulted in lengthening of the hospital stay. Our findings cannot be proven without further research and a larger patient sample.
ABSTRACT
Introduction: The first report on COVID-19 was in Wuhan, Hubei Province, China on December 31, 2019. COVID-19 was declared a pandemic by the World Health Organization on March 11, 2020. As a result of the COVID-19 pandemic, the world had to adopt certain modifications to hinder the transmission of the disease. These changes have affected patients' sleeping, dietary, and lifestyle habits. Little research is conducted on these changes among patients presenting at primary healthcare settings following the pandemic. Therefore, we conducted this study to determine the self-reported changes in these habits in patients attending primary health care centers of Dubai both before and during the pandemic. Material and Methods: A cross-sectional study was conducted among patients attending primary health care centers in Dubai from November 2020 to August 2021. Patients filled out an online questionnaire that included items for sociodemographic characteristics and study outcomes. The outcomes included changes in sleeping, smoking, dietary, and sporting habits both before and during the pandemic. Data were further stratified by gender. Results: A total number of 385 patients participated in this study. Significant changes in sleeping habits both before and during the pandemic were observed among included patients (p = 0.004) which were consistent in female patients only (p = 0.025). Most patients were not smokers both before and during the pandemic (92.98% vs. 92.46%);however, no significant change was noted across male (p = 0.503) and female patients (p = 0.391). There was a positive change in sporting habits across both male (p = 0.005) and female patients (p = 0.001). The majority of patients reported no change in the number of daily meals eaten (50.13%) following the pandemic. Conclusion: Our study highlighted that sleeping habits among primary care patients were negatively affected during the pandemic as compared to before. However, there was a positive change in their sporting habits with no change in smoking. Additionally, no substantial change in dietary habits was noted. However, further research is needed to confirm our findings.
ABSTRACT
Online learning has been the center of the education systems around the world for approximately two years now. Since the COVID pandemic appeared, many nations have resorted to online learning formats in their schools and higher education institutes. Consequently, private tutoring in all education levels started to rise as students were trying to cope with the sudden changes in their courses. However, the effect of private tutoring is somewhat ambiguous due to the lack of feedback from students. This study presents an online survey on students' experiences with private tutoring in the higher education institutions in Jordan. A total of 107 students participated in this study from different academic levels. The results of the survey showed that 63% of participants believed that the online learning format in their courses was one of the reasons they went to private tutoring. However, nearly half of the sample did not believe that instructors played a role in them resorting to private tutoring. The results also showed that senior level students believed that private tutoring improved their academic standings. In fact, their answers were statistically significantly different than students from the other academic levels. The results also showed that students in the lower academic levels (freshmen, and sophomores) expressed their disappointment in the outcomes of private tutoring. © 2022 IEEE.
ABSTRACT
Since the early days of 2020, COVID-19 has tragic effects on the lives of human beings all over the world. To combat this disease, it is important to survey the infected patients in an inexpensive and fast way. One of the most common ways of achieving this is by performing radiological testing using chest X-Rays and patient coughing sounds. In this work, we propose a Convolutional Neural Network-based solution which is able to identify the positive COVID-19 patients using chest X-Ray images. Multiple CNN models have been adopted in our work. Each of these models provides a decision whether the patient is affected with COVID-19 or not. Then, a weighted average selection technique is used to provide the final decision. To test the efficiency of our model we have used publicly available chest X-ray images of COVID positive and negative cases. Our approach provided a classification performance of 88.5%. © Al-Zaytoonah University of Jordan (ZUJ).
ABSTRACT
This report announces the complete genome sequences of two severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) isolates detected in Egypt. The isolates were obtained from oropharyngeal swab specimens from two Egyptians in Upper and Lower Egypt. Sequence analysis showed mutations that differentiate Egyptian strains from the reference strain 2019-nCoV WHU01.
ABSTRACT
Recently, several types of research in Chatbot systems have been developed in the literature by their means of having a considerable number of languages such as English, French, and other languages, which serve in various fields of a number of real-life cases. Chatbots are considered unfamiliar besides their little usage. To the best knowledge of the research, no previous research has been conducted in improving an Arabic Chatbot in Jordanian universities. With the outbreak of the COVID-19 pandemic and its global effects, the need to reduce the load on the admissions director and possibly other users became critical. Hence, this paper aims to develop an Intelligent Arabic Chatbot System that can reduce such a load. In particular, this system supports an Arabic spoken by using a Jordanian dialect with students, particularly at the Al-Zaytoonah Private University of Jordan. Therefore, the proposed system represents a primary Jordan chatbot that uses a Jordanian dialect. © 2021 IEEE.