ABSTRACT
Aim: The purpose of this study was to investigate into mental health outcomes such as stress, anxiety, and depression, as well as sleep quality in suspected COVID-19 quarantined cases. Methods: This is a cross-sectional study that used an online survey to target suspected COVID-19 cases in quarantine facilities. Data were collected on several aspects of participants' sociodemographic characteristics, sleep disturbance, and mental health status. Depression, anxiety, stress scale and Pittsburgh Sleep Quality Index were used to measure both the psychological impact and mental health status. Results: Of the 362 people who took the survey, 234 (64.6%) were men, and 148 were between the ages of 26-35. Poor sleep was found to be prevalent in 65% of study participants. The rates of individuals reporting severe depression, anxiety, and stress symptoms were 14.6%, 15%, and 15%, respectively. According to the findings, there were significant gender differences in depression and anxiety (p = 0.001). When compared to the other age groups, participants aged 26-35 reported the highest level of stress (p = 0.001). Being male [OR = -1.23, 95% CI (-2.75-1.95) P = 0.050], single [OR = 0.98, CI (0.15-4.20), P = 0.001], and a healthcare worker [OR = -2.20, 95% CI (-2.59-1.82), P = 0.001] were all associated with poor sleep quality. Conclusion: Approximately-one-third of quarantine COVID-19 patients had poor sleep quality with mild-moderate depression. Both anxiety and stress scales were prevalent in nearly half of the studied samples.
ABSTRACT
In recent times, humans who have been exposed to influenza A viruses (IAV) may not become hostile. Despite the fact that KLRD1 has been discovered as an influenza susceptibility biomarker, it remains to be seen if pre-exposure host gene expression can predict flu symptoms. In this paper, we enable the examination of flu using deep neural networks from input human gene expression datasets with various subtype viruses. This study enables the utilization of these datasets to forecast the spread of flu and can provide the necessary steps to eradicate the flu. The simulation is conducted to test the efficiency of the model in predicting the spread against various input datasets. The results of the simulation show that the proposed method offers a better prediction ability of 2.98% more than other existing methods in finding the spread of flu.
ABSTRACT
Background: This study aimed to describe the demographic characteristics and determine the risk factors associated with disease severity and length of hospital and intensive care unit (ICU) stay in a cohort of COVID-19 patients admitted into ICU in Saudi Arabia. Methods: This was a national, multi-center, retrospective cross-sectional study of all COVID-19 cases admitted into different ICUs in Saudi Arabia between March 2020 and September 202l. Demographic, clinical features, comorbidities, and length of stay (LOS) data were retrieved from the national Health Electronic Surveillance Network (HESN) and Taqassi databases at the Saudi Ministry of Health (MOH) for subsequent analyses. We used multiple linear regression models to determine risk factors associated with critical outcomes (including LOS in ICU) among COVID-19 cases. Results: A total of 12,436 COVID-19 patients were included in this study, with a mean age of 59.57 ± 18.30 years and 7,679 (62%) were <65 years old. COVID-19 was more common in males (N = 7,686, 61.9%) and Saudi nationals (N = 8,516, 68.5%). The clinical characteristic findings showed that 36.3% of patients required invasive ventilation whilst 65.4% received tracheostomies for ventilation, and 4% were on dialysis. Our analysis revealed that 2,978 (23.9%) patients had one comorbidity, 4,977 (47.4%) had two or more comorbidities, and diabetes (48.2%) was the most prevalent comorbidity, followed by hypertension (44.2%), and chronic cardiovascular disease (10.5%). Thirteen variables emerged as significant predictors of LOS in ICU using multiple linear regression analyses, with invasive ventilation as the strongest predictor of LOS in the ICU (beta = -0.68, p = 0.001) and hospital admission (beta = -0.65, p = 0.001). Conclusions: COVID-19 continues to affect millions of people around the world, with a mortality rate of about 2-3% of all infected patients. Our analysis revealed that comorbidities such as chronic kidney disease, cardiovascular disease, diabetes, and older age were significant risk factors associated with a poorer prognosis and longer duration of stay in hospitals and ICU.
ABSTRACT
BACKGROUND: The negative psychological impact of COVID-19 in the general population has been well documented. Similar studies among those who were infected and who underwent quarantine remain scarce, particularly in the Arab region. The present study aims to fill this gap. METHODS: In this cross-sectional study, suspected/confirmed COVID-19 individuals who were quarantined in the Ministry of Health (MOH) facilities were invited to participate in an online survey. All consenting participants answered a generalized questionnaire that included demographic characteristics, as well as a five-part questionnaire that assessed the symptoms of depression, anxiety, insomnia, and distress. RESULTS: A total of 335 suspected/confirmed COVID-19 individuals (198 males and 137 females) participated. Being female is associated with increased risk of depression (odds ratio OR 1.8 (confidence interval, CI 1.1-3.1; p = 0.03)) as well as being employed by the government (OR 2.8 (CI 1.1-7.0; p = 0.03)). Level of education (OR 2.3 (CI 1.0-5.4; p = 0.049)) and employment in government (OR 3.0 (CI 1.2-7.8; p = 0.02)) were significantly associated with distress. Increasing age (45 years and above) appeared to be protective against distress (OR 0.2 (CI 0.02-0.69; p = 0.008)), as well anxiety and sleep pattern (OR 0.3 p < 0.05). CONCLUSION: Findings of the present study highlight that infected COVID-19 populations are at higher risk for acute and detrimental psychological well-being during quarantine and/or self-isolation. Identification of the coping mechanisms of older adults during periods of distress may prove beneficial in the pandemic preparedness of younger generations.
ABSTRACT
Objective: In this descriptive cross-sectional study we aimed, to assess the level of depression, anxiety, insomnia and distress symptoms experienced by healthcare providers during the COVID-19 pandemic in Saudi Arabia. Methods: All healthcare providers currently working in different hospitals were invited to participate in this study. Data gathering started in March 2020 to May 2020. The participants answered a five-part questionnaire which includes demographic data, a 9-item Patient Health Questionnaire, a 7-item Generalized Anxiety Disorder, a 7-item Insomnia Severity Index, and a 22-item Impact of Event Scale-Revised, which assess the level of depression, anxiety, insomnia, and distress. Results: Out of 200 healthcare providers, 40% were males. 52% were aged 31-40 years old, 61% were married. The majority of the participants were Saudi nationals (84%), 74% were nurses, 11% were physicians and 15% were other healthcare providers. More than half of the participants worked as front-liners (57%). Overall, 73, 69, 62, and 83% of all healthcare providers reported symptoms of depression, anxiety, insomnia, and distress, respectively. The analysis showed severe symptoms level of depression for physicians and nurses was 35% and 20% (p < 0.05), respectively. Only three of the independent variables made a unique contribution to the model (gender, profession, and working position) (p < 0.05). Conclusion: COVID-19 pandemic has a significant impact on the mental health of healthcare providers in Saudi Arabia. Female nurses and healthcare providers working in the frontline who were directly treating patients with COVID-19 are at increased risk of severe depression, anxiety and distress.