Objective: to assess the risk factors of coronary artery disease patients.
Methodology: A non-probability (purposive) sample of (100) patients. The study population consisted of
a sample of adults from both genders whose ages were 30 years and more, and was newly diagnosed as
having CAD by coronary angiography in the cardiac catheterization unit of An Nasiriyah heart center.
Results: The result of the study showed that the most common modifiable risk factors were low HDL-C
levels (58%), smoking (53%), hypertension (46%), diabetes mellitus (34%), obesity (30%), high
triglycerides (19%), hypercholesterolemia (17%), and high LDLC (14%). All these factors were positively
and significantly associated with the development

Diabetes mellitus type 2 (T2DM) formerly called non-insulin dependent diabetes mellitus (NIDDM) or adult-onset diabetes is a common disease. Rheumatoid factor is a well-established test used in the diagnosis and follows the prognosis of rheumatoid arthritis (RA). Rheumatoid factor is sometimes found in serum of patients with other diseases including diabetes mellitus (DM), due to the presence of pro-inflammatory cytokines such as TNF- α which play an important role in chronic inflammatory and autoimmune diseases like rheumatoid arthritis (RA). The aim of the study is to investigate the associations between type 2 diabetes mellitus (T2DM) and rheumatoid arthritis (RA) in scope of rheumatoid factor (RF), hyperglycemia a

Background:  Imaging has a critical role in the diagnosis and evaluation of cardiac diseases, beginning with chest radiography and fluoro-scopy and progressing to coronary angio-graphy, echocardiography, nuclear medicine and recently  multidetector computed tomo-graphy (MDCT) as well as magnetic resonance (MR) imaging

Objective: To highlight the role of Multi-detector CT in the evaluation of coronary artery disease and its importance of being noninvasive diagnostic technique.

Methods: A cross sectional study for 20 patients. Patients were asked to fast 6 hours prior to the examination and the patients with heart rates above 65 beats per minute were given cardio-

Afamin, which is a human plasma glycoprotein, a putative multifunctional transporter of hydrophobic molecules and a marker for metabolic syndrome. Afamin concentration have been proposed to have a significant role as a predictor of metabolic disorders. Since NAFLD is associated with metabolic risk factors, e.g., dyslipidemia, insulin resistance and visceral obesity, it is considered as the hepatic manifestation of the metabolic syndrome. The objective of this study is to determine Afamin levels in hypothyroid patients with and without fatty liver disease and compare the results with controls. Also to study the relationship of Afamin level with the Anthropometric and Clinical Features (Age, Gender, BMI and Duration of Hypothyroidism) , Serum

Renal function tests are commonly used in clinical practice to look for renal disease, the most common includes the serum urea, uric acid and creatinine. Heart failure patients have a higher incidence of renal function test abnormalities than individuals who do not have heart failure disease. Fifty subjects of adults (male) were divided in to two groups, 25 subjects (healthy) as control (group1) and 25 subjects with heart failure (group 2). Our results indicate that serum uric acid, urea, and creatinine values were significantly elevated (P≤0.05) in patients group (2) compared with healthy group (1). The results also showed, the effect of age categories on uric acid blood urea nitrogen and creatinine values (P≤0.05) and there were no si

Background: Congenital cardiac defects have a wide spectrum of severity in infants. About 30-40% of patients with congenital cardiac defects will be symptomatic in the 1^st year of life, while the diagnosis was established in 60% of patients by the 1^st month of age.

Objectives: To identify the occurrence of specific types of CHD among hospitalized patients and to evaluate of growth of patients by different congenital heart lesions.

Methods: A retrospective study, done on ninety-six patients (51 male and 45 female) with congenital heart disease (CHD) admitted to central teaching hospital of pediatrics, Baghdad from 1^st September 2009 to 30

Background : The hepatopulmonary syndrome (HPS) is defined as the triad of liver disease, arterial deoxygenation, and pulmonary vascular dilatation. The reported prevalence of HPS in cirrhotic patients varies between 5% -17.5%.Objective : To estimate the prevalence of hepatopulmonary syndrome among patients with chronic liver disease and portal hypertension and to study the correlation between HPS and the severity of liver disease.Patients and methods : Thirty patients were studied for the presence of HPS using transthoracic contrast echocardiography for detection of pulmonary vasodilatation. Arterial oxygen saturation (SaO2) was determined in erect and supine position using a pulse oximeter , (SaO2 ≤ 92 % in supine position and/or a d

Background Cardiovascular disease (CVD) is a leading cause of death worldwide. Ischemic heart disease is a major cause of morbidity and mortality. Lack of blood supply to the brain can cause tissue death if any of the cerebral veins, carotid arteries, or vertebral arteries are blocked. An ischemic stroke describes this type of event. One of the byproducts of methionine metabolism, the demethylation of methionine, is homocysteine, an amino acid that contains sulfur. During myocardial ischemia, the plasma level of homocysteine (Hcy) increases and plays a role in many methylation processes. Hyperhomocysteinemia has only recently been recognized as a major contributor to the increased risk of cardiovascular disease (CVD) owing to its eff

Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac