Background: Rheumatoid arthritis (RA) is an inflammatory disease of unknown etiology characterized by joint inflammation and the presence of autoantibodies, mostly Anti-cyclic citrullinated peptide antibody (ACCP) which are released when the body loses its ability to distinguish between self and foreign molecules. Serum amyloid A2 (SAA2) is an acute phase protein produced in response to inflammatory conditions including RA.

Objectives: To investigate the prognostic ability of SAA2 in comparison with ACCP and the prediction of disease activity and response to treatment by Methotrexate and Etanercept in Iraqi RA patients.  

Patients and methods: A case control study, on a to

Objective: This study aims to assess the awareness of patients suffering from cardiovascular
diseases.
Methodology: A descriptive design was applied in this study. A purposive sample consisted of
(100) patients with cardiovascular disease in the Mosul's hospitals were interviewed to achieve study
objectives. A questionnaire was used for data collection after tested for validity and reliability by pilot
study.
Results: The study results showed the mean of patients awareness are (1.78) cut point of (3) and
the majority of patients84% were aged more than 50 years or above. Slightly increase proportion of
male more than females. Most of them are married81%, retired, smokers, and a period of developing
the disease a

Heart disease identification is one of the most challenging task that requires highly experienced cardiologists. However, in developing nations such as Ethiopia, there are a few cardiologists and heart disease detection is more challenging. As an alternative solution to cardiologist, this study proposed a more effective model for heart disease detection by employing random forest and sequential feature selection (SFS). SFS is an effective approach to improve the performance of random forest model on heart disease detection. SFS removes unrelated features in heart disease dataset that tends to mislead random forest model on heart disease detection. Thus, removing inappropriate and duplicate features from the training set with sequential f

    In recent years, predicting heart disease has become one of the most demanding tasks in medicine. In modern times, one person dies from heart disease every minute. Within the field of healthcare, data science is critical for analyzing large amounts of data. Because predicting heart disease is such a difficult task, it is necessary to automate the process in order to prevent the dangers connected with it and to assist health professionals in accurately and rapidly diagnosing heart disease. In this article, an efficient machine learning-based diagnosis system has been developed for the diagnosis of heart disease. The system is designed using machine learning classifiers such as Support Vector Machine (SVM), Nave Bayes (NB), and K-Ne

Aim of the present study is Identification of specific gene for GPCR using specific primers .and identification of difference in PCR analysis in patients with heart thrombosis and compared with healthy, Sequencing of PCR product regarding GPCR compared for all three subject, Identification the similarity of human GPCR with local strain of yeast fifty healthy control and fifty patients with thrombosis which diagnosed medically with cardiac specific troponin t, troponin 1 levels and electro myocardiogram ECG. The aged for all subjects ranged (39-75) years patients were lying in cardiac care unit at Ibn- al- Nafees teaching hospital and Sheikh Zayed teaching hospital. Genomic DNA of whole blood was extracted from buffy coat and cell cu

   One of the most common forms of diabetes is Type-2 that occurs due to the failure of cells in recognizing and responding to insulin if not accurately treated. The aim of this work is to evaluate the relations of thyroid hormones, vitamins, and lipid peroxidation with the glycemic index in patients experiencing Type-2 diabetes. Some tests of biochemical parameters and vitamins were conducted on 35 patients experiencing Diabetes Mellitus (DM) and 35 healthy subjects. The results indicated the increase in the levels of MDA (3.86 ± 0.97 µmol/L), HbA1c (8.27 ± 1.66 %), FBS (198.34 ± 32.41 mg/dl) and TSH (5.67 ±0.34 mIU/L) in the blood of diabetic subjects in comparison to the controls at a P value lower than 0.05. These incr

Women with diabetes in pregnancy (type 1, type 2 and gestational) are at increased risk for adverse pregnancy outcomes which also include infant development of congenital heart disease and even fetal death. Adequate glycemic control before and during pregnancy is crucial to improve outcome

Background: Atrial fibrillation (AF) is a common arrhythmia in daily practice and one of the heart disorders with the highest morbidity and death rates, as it is responsible for a huge number of negative consequences. In our country, there is limited information on the prevalence or natural history of the less well-defined clinical types.

Objective: to evaluate the clinical profile and coronary artery findings in atrial fibrillation patients.

Patients and Methods: This cross-sectional study was conducted during the period from the first of October 2019 to end of July 2021 at the Iraqi Center for the heart disease at Baghdad Medical City. Included 32 Iraqi patients with atri

Background: Cytokines produced by inflammatory cells play a pivotal role in synovial inflammation and joint destruction in rheumatoid arthritis.
Patients and Methods: The cytokine serum levels were measured by EASIA (Enzyme amplified sensitivity immunoassay) in sera from 50 RA patients, and 40 healthy donors. Cytokine levels were compared in different RA subpopulations (positive or negative rheumatoid factor (RF), long term or recent onset disease, high or low disease activity). In addition, the possible association with other demographic and clinical parameters (gender, age, etc) was also analyzed.
Results: It was demonstrated that IL-2, IL-6 and IFN-δ levels were elevated in serum samples of RA pati