Objectives: To assess patients' satisfaction to nursing care at hemodialysis units and determine the relationship
between patients' satisfaction and patients' demographic data.
Methodology: A descriptive study was carried out at hemodialysis units of Baghdad teaching hospitals from Feb.
4
th
, 2010 through Sep. 5
th, 2010. A purposive (non-probability) sample of (150) patients ta hemodialysis units ni
Baghdad teaching hospitals was selected. The data were collected through the use of constructing questionnaire
and by means of an interview technique with the patients; the questionnaire consists of two parts (1)
demographic data (2) patients' satisfaction to nursing care. The validity of the study questionnaire was
determined through the panel of experts and the reliability of the study questionnaire was determined through
the pilot study. Descriptive statistical analysis procedure (frequency, percentage and mean of score) and
inferential analysis procedure (person correlation coefficient, chi-square test and t-test) were used for data
analysis.
Results: The findings of the study indicated that there is high satisfaction to clinical nursing care, communication
/patient –nurse relationship and moderate satisfaction toward nursing health education. Not statistical
significant difference between (gender, age, educational status, marital status, occupational status, frequency of
hemodialysis and duration of hemodialysis). While there is a statistical significant difference between patients'
occupational status and their satisfaction toward communication /patient –nurse relationship.
Recommendations: Great emphasize should be directed toward the educational aspects of hemodialysis unit by
providing educational posters, guidelines, pamphlets and manuals.
Rheumatoid arthritis is a worldwide inflammatory chronic autoimmune disease with varying severity. Due to no definitive cure for this disease, current therapies aim to decrease the pain and slow further damage. The interleukin (IL)‐36 cytokine was little known for its role in rheumatoid arthritis; this research aimed to evaluate the serum IL36 levels in RA patients compared to healthy controls. This study included 80 patients with rheumatoid arthritis registered at the Rheumatology Clinic in Baghdad teaching hospital. The patients were divided into three groups based on the treatments received. Group 1 included patients treated with biological therapy (etanercept, adalimumab), Group2 patients with non-biological treatment (methotr
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The aim of the present study is to compare the biochemical action of the three vaccines taken in Iraq: Pfizer Biontech, AstraZeneca Oxford and Sinopharm based on biochemical parameters. Seventy COVID-19 Iraqi patients ( males and females ) were participated in the present study and classified into 7 groups : Gc : COVID-19 patients ( without vaccine ) , Gp1: COVID-19 patients took one dose of Pfizer Biontech, Gp2 : COVID-19 patients took two doses of Pfizer Biontech, Ga1 : patients took one dose of AstraZeneca Oxford vaccine , Ga2: patients took two doses of AstraZeneca Oxford vaccine , Gs1 : patients took one dose of Sinopharm vaccine and Gs2:
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β-thalassemia major is a genetic disease that causes sever defect in normal hemoglobin synthesis. The patients with β-thalassemia major need periodic blood transfusions that can result in accumulation of body iron, so treatment with iron chelating agent is required. Complications of this iron overload affecting many vital organs, including the liver. The aim of this work was to evaluate liver enzymes in β -thalassemia major patients with deferasirox versus without it. Two groups of β-thalassemia major patients were involved in this study named group A; 40 β-thalassemia patients of blood transfusion dependent without deferasirox, group B; 40 β-thalassemia patients of blood transfusion dependent on de
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... Show MoreThe use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow
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