Abstract

The present paper attempts to detect the level of (COVID-19) pandemic panic attacks among university students, according to gender and stage variables.

To achieve this objective, the present paper adopts the scale set up by (Fathallah et al., 2021), which has been applied electronically to a previous cross-cultural sample consisting of (2285) participants from Arab countries, including Iraq. The scale includes, in its final form, (69) optional items distributed on (6) dimensions:  physical symptoms (13) items, psychological and emotional symptoms (12) items, cognitive and mental symptoms (11) items, social symptoms (8) items, general symptoms (13) items and daily living practices (12) items

    Polycystic ovary syndrome (PCOS) is a heterogeneous disorder . PCOS affects 6–10% of women during their reproductive life. Patients with PCOS are in the high risk for coronary heart disease because of their abnormal lipid profile, insulin resistance and obesity. The present study aimed to shed a light on the contribution of  sialic acid, paraoxonase and immunoglobulin G as a clinical indicator in the pathogenesis of PCOS. Seventy five female patients with age range (16-38) years taken from Al-Sadder Teaching Hospital and AlZahrawi Hospital in Governorate of    Messan through the period from July 2013 to December 2013 and twenty five apparently health subject as a control group were

This study is descriptive and theory of Dawn syndrome as the problem of research lies in the need to identify the identification of the causes of Dawn syndrome and its symptoms and methods of dealing with it, which has become a problem that needs treatment, especially after the numbers have become high in Iraq, which has not yet taken the necessary importance for treatment and care.

The objectives of the research were summarized in the identification of the most important causes of Dawn syndrome and its symptoms and diagnosis and ways or methods of dealing with people with Dawn syndrome in order to develop therapeutic plans for him.

Susceptibility to the pandemic coronavirus disease 2019 (COVID-19) has recently been associated with ABO blood groups in patients of different ethnicities. This study sought to understand the genetic association of this polymorphic system with risk of disease in Iraqi patients. Two outcomes of COVID-19, recovery and death, were also explored. ABO blood groups were determined in 300 hospitalized COVID-19 Iraqi patients (159 under therapy, 104 recovered, and 37 deceased) and 595 healthy blood donors. The detection kit for 2019 novel coronavirus (2019-nCoV) RNA (PCR-Fluorescence Probing) was used in the diagnosis of disease.

Background: The global threat of COVID-19 outbreak and on the 11 March 2020, WHO acknowledged that the virus would likely spread to all countries across the globe and declared the coronavirus outbreak a pandemic which is the fifth pandemic since 20 century and this has brought human lives to a sudden and complete lockdown and the confirmed cases of this disease and deaths continue to rise in spite of people around the world are taking important actions to mitigate and decrease transmission and save lives. Objectives: To assess the effect of exercise and physical activity on the immunity against COVID-19. Methods: Collected electronic databases including (Medline, EMBASE, Google Scholar, PubMed and Web of Science) were searched with

SUMMARY. The objectives of the present study were to assess the possible predictors of COVID-19 severity and duration of hospitalization and to identify the possible correlation between patient parameters, disease severity and duration of hospitalization. The study included retrospective medical record extraction of previous coron avirus COVID-19 patients in Basra hospitals, Iraq from March 1st and May 31st, 2020. The information of the participants was investigated anonymously. All the patients’ characteristics, treatments, vital signs and laboratory tests (hematological, renal and liver function tests) were collected. The analysis was conducted using the SPSS (version 22, USA). Spearman correlation was used to measure the relations

             Polycystic syndrome (PCOS) is a considerable infertility disorder in adolescents and adult women in reproductive age. Obesity is a vigorous risk factor related to POCS.  This study aims to evaluate the association of obesity and PCOS by investigating several parameters including:  anthropological, biochemical (lipid profile, fasting blood sugar, glucose tolerance test, and hormone levels (LH, FSH, LH/FSH ratio, Estradiol2 and Testosterone),and genetic parameters (Fat mass and Obesity associated gene (FTO) polymorphism at rs17817449) in 63 obese and non-obese PCOS women. The biochemical tests were investigated by colorimetric methods while FTO gene polymorp

The objective of this study is to evaluate the level of parathyroid hormone, Co enzyme Q and total antioxidant status in serum’s women with fibromyalgia syndrome firstly, then to demonstrate if these biochemical markers affected by age and obesity.

      This study was performed at Rheumatology and Rehabilitation Consultation Unit in Baghdad Teaching Hospital. Venous blood sample were drawn from (59) female with FMS and (30) control (without FMS). The serum was obtained after on standing in order to coagulate then centrifuged. The mean age± SD of FMS group was (42.22±15.34) years and for control was (40.7±18.22) years. Those participants were subdivided into four different groups acc

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings