Hussainsinger5844

The pandemic situation created an overwhelmed needs for ICU facilities, according to this problem, the need of accurate management of facilities represents boldness. In this study, prognostic risk factors for ICU admission among COVID-19 hospitalized patients were evaluated.

From 22 February to April 20, 2020. A total of 214 COVID-19 patients participated in this study. The included patients were between 18- 80 years old, and the patients who previously admitted for COVID-19 were excluded. The comorbid medical conditions, admission laboratory, demographic data, and first manifestations were analyzed between two groups, including ICU and non-ICU admitted patients. The statistical analysis, univariate and multivariate analysis were afforded. The value of the predictors in the risk assessment of ICU admission was estimated.

55(25.7%) patients were admitted in ICU. The ICU admitted patient's mortality rate was about 68%. The age was significantly higher among ICU admission group (P=0.03). Admission O2 saturation was significantly lower among ICU admitted patients (P=0.00). The kidney disease and malignancy history were more frequent in ICU-admitted patients (P=0.04, P=0.00). Myalgia was the clinical manifestation that significantly presented more frequent in ICU-admitted patients. INR, CRP, ESR, HB, and lymphocyte were significantly different between two groups. After multivariable analysis, admission O2 saturation, hematocrit, CRP and myalgia could significantly predict the risk of ICU admission. Furthermore, the value of predictors was estimated in our study.

Based on our results, the admission O2 saturation, HCT, CRP levels at first admission and myalgia presentation could be considered as the valuable predictors of ICU admission.

Based on our results, the admission O2 saturation, HCT, CRP levels at first admission and myalgia presentation could be considered as the valuable predictors of ICU admission.

The purpose of this study was to prevent the prevalence of infectious diseases in vulnerable groups by anticipating the role of actors in implementing decision-making models in conditions of uncertainty in medical universities.

This research is an applied research by combining qualitative and quantitative methods based on the foundation data theory (Grand Theory). To determine the dimensions of the model, the statistical population included crisis management managers and faculty members of Mazandaran University of Medical Sciences. The data collection was done through targeted sampling and interviews, semi-structured interviews, analysis and coding methods. The statistical population to present the model includes senior and middle managers of Mazandaran University of Medical Sciences. The simple random sampling method based on the sample size was determined by Cochran's method, and the collected data from the researcher's questionnaire were analyzed through nonparametric statistical experiments, Kolmogorov test Smirnov, SPSS SMARTPLS, Excel and the method of modeling structural equations with the least squares approach has been partial.

The path coefficient of each dimension in explaining the decision model in uncertainty conditions based on T statistic and p value and SRMR value was 0.137, which was a good value and the main actors in implementing the model were policymakers, managers and staff.

The implementation of this model will lead to a change in the decisions made by health system authorities in conditions of uncertainty, and will increase the ability of Head of medical universities and the resilience of the health system.

The implementation of this model will lead to a change in the decisions made by health system authorities in conditions of uncertainty, and will increase the ability of Head of medical universities and the resilience of the health system.

The Covid-19 epidemic in 2019 has created many public health problems. Literature that focuses on the risk factors of this issue is limited especially in developing countries. Epigenetic phosphorylation This study proposed to examine the risk factors of COVID-19 infection in the west area of Iran.

This case-control study was conducted from February to April 2020 in Nahavand county, western Iran. Cases were all patients who were coronavirus positive and, the controls included people who had clinical signs consistent with COVID-19, but their test results were negative. Two controls were selected for every case. Multivariate logistic regression was applied to evaluate the effects of epidemiological aspects on the incidence of COVID-19.

Significant risk factors for COVID-19 infection based on the multivariable logistic regression model were male gender (OR=1.82, P=0.0.15), age group over 60 years (OR=2.04, P=0.017), living in urban areas (OR=1.79, P=0.018), being married (OR=2.08, P=0.022), having history of contact with the corona patients (OR=5.61, P=0.009), and comorbidities (OR=1.78, P=0.031).

This study highlighted the factors associated with the occurrence of COVID-19 infection. These findings may help guide recommendations for the protection of high-risk groups.

This study highlighted the factors associated with the occurrence of COVID-19 infection. These findings may help guide recommendations for the protection of high-risk groups.

The2019 coronavirus disease (COVID-19) is threatening public health in many ways. The psychological situation of individuals is important and limited data is available from Iran. In this study, we aimed to illustrate the psychological distress of the general population and evaluate the factors affecting it.

An online cross-sectional survey was conducted from 29

to 31

March 2020 in South Khorasan province, affected later than other parts of the country. We included sociodemographic questions, Hospital Anxiety, and Depression Scale (HADS) questionnaire, and questions addressing various symptoms and diseases. Most questions had multiple choices to select from and some were open questions. Univariate and multivariate analysis in SPSS software was used to find significant relationships.

A total of 844 responses were collected, of which 788 records were included in the analysis. The mean age of responders was 36.61±10.97 (age range 18-88) and 484 (61.4%) of them were females. The mean scores in the anxiety and depression subscale of the HADS questionnaire were 7.