Background: Dilated cardiomyopathy (DCM) is a well-recognized cause of cardiovascular morbidity and mortality.Objectives: To evaluate the prognostic implications of the restrictive left ventricular filling pattern (RFP) in dilated cardiomyopathy.Methods: Patients with DCM admitted to Ibn AL-Bitar Hospital for Cardiac Surgery, Baghdad-Iraq, from May 2006 to August 2008, underwent a full clinical evaluation and Doppler echocardiography study. Patients were classified into three groups: Group I had persistent restrictive filling pattern; Group II had reversible restrictive filling pattern; and Group III had nonrestrictive filling pattern. Results: The current study was conducted on a total number of 80 patients with DCM, fifty (62.5 %) were males and 30(37.5%) were females with a male to female ratio 1.6:1. Patients with restrictive filling pattern (Group I&II) were 51 (63.8%), while patients with nonrestrictive filling pattern (Group III) were 29 (36.2%). During follow up, patients with persistent restrictive filling pattern (30; 37.5%) had higher New York Heart Association (NYHA) class symptoms, low ejection fraction (EF) and higher mortality; 6 (20%) died within the first year, 6 (20%) died in the second year. Clinical improvement was significantly frequent in Group II and III than Group I.Conclusions: In patients with DCM, the persistence of restrictive filling at 3 months is associated with a high mortality the patients with reversible restrictive filling have a high probability of improvement and excellent survival.
Objective: Determine the effectiveness of the Nutrition Education Program upon the pregnant mothers'
nutritional knowledge.
Methodology: ٨ quazi-experimental study was carried out to determine the effectiveness of the nutrition
education program upon the pregnant mother's nutritional knowledge. A non-probability "purposive sample" of
(60) pregnant mother was selected from Al-bayaa' Primary Health Care Center in Baghdad City. These mothers
were divided into two equal groups; study group and control group. A questionnaire was developed as a tool of
data collection for the purpose of the study. A pilot study and follow-up was carried out to test the reliability and
validity of the questionnaire for the period of Octobe
Objective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questio
In the present work advanced oxidation process, photo-Fenton (UV/H2O2/Fe+2) system, for the treatment of wastewater contaminated with oil was investigated. The reaction was influenced by the input concentration of hydrogen peroxide H2O2, the initial amount of the iron catalyst Fe+2, pH, temperature and the concentration of oil in the wastewater. The removal efficiency for the system UV/ H2O2/Fe+2 at the optimal conditions and dosage (H2O2 = 400mg/L, Fe+2 = 40mg/L, pH=3, temperature =30o C) for 1000mg/L load was found to be 72%.
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration
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