Background: Non-alcoholic fatty liver disease (NAFLD) is the most common liver disorder globally. The prevalence is 25% worldwide, distributed widely in different populations and regions. The highest rates are reported for the Middle East (32%). Due to modern lifestyles and diet, there has been a persistent increase in the number of NAFLD patients. This increase occurred at the same time where there were also increases in the number of people considered being obese all over the world. By analyzing fatty liver risk factors, studies found that body mass index, one of the most classical epidemiological indexes assessing obesity, was associated with the risk of fatty liver. Objectives: To assess age, sex, and body mass index (BMI) as risk factors in NAFLD. Subjects and Methods: It is a case-control cross-sectional study from September 2020 till June 2021 which included all obese patients consulted the obesity research and therapy unit during the period of the study. Age and sex were recorded, body mass indices were calculated for all patients and categorized into normal with BMI < 25kg/m2, overweight with BMI 25-30 kg/m2, and obese with BMI > 30 kg/m2, ultrasonography was done to them to diagnose fatty liver changes which were categorized into three grades; mild, moderate and severe Results: 192 patients were enrolled in the study with an age range from 18-55 years with a mean of 38.09, males were 48 and females were 144. Sever NAFLD is present in 2.8% of obese females and 5.5% of obese male with 0% in normal and overweight individuals. Conclusion: NAFLD was more prevalent with increasing BMI and age in all sexes.
The electrical activity of the heart and the electrocardiogram (ECG) signal are fundamentally related. In the study that has been published, the ECG signal has been examined and used for a number of applications. The monitoring of heart rate and the analysis of heart rhythm patterns, the detection and diagnosis of cardiac diseases, the identification of emotional states, and the use of biometric identification methods are a few examples of applications in the field. Several various phases may be involved in the analysis of electrocardiogram (ECG) data, depending on the type of study being done. Preprocessing, feature extraction, feature selection, feature modification, and classification are frequently included in these stages. Ever
... Show MoreMultiplesclerosis(MS)isachronic,inflammatory,immune-mediateddiseaseof the central nervous system (CNS). More than 2 million people worldwidehave MS. The goal of the present study was to compare Iraqi patients' treat-ment satisfaction with three different disease-modifying therapies (DMTs),administeredorally,subcutaneously,andbyslowinfusion;namely,fin-golimod, interferon beta-1b (IFNβ-1b), and natalizumab, respectively. Aswell as to assess the individual differences among these therapies about theireffectiveness, convenience and global satisfaction also to assess the role ofcertain predictors on treatment satisfaction. Patient satisfaction with medi-cation assessed by the Treatment Satisfaction Questi
... Show More
Background. Echinococcosis/ hydatitdosis is a zoonotic parasitic disease caused by the infestation of the larval form of the tapeworm of the genus Echinococcus .The Liver, lungs, and kidneys are the common areas of infestation.Objectives: To describe hydatid disease in hospitalized patients from a clinico-epidemiological perspectives.Methods:: A retrospective study was conducted over a period of 6 months extending from 15th of November 2011 to the 15th of May 2012 by reviewing records of 125 patients who were hospitalized at Baghdad Teaching Hospital during 2011and received medical and surgical treatment for hydatid cyst disease. The information covered the socio-demographic and clinical characteristics of the patientsResults:.The presen
... Show MoreMost of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B
... Show MoreBackground:This is a prospective study of three children presented to us in the Orbital clinic in AL ShahidGazi Al Hariri Hospital with painless proptosiswith suspension of Hydatid disease.Objectives: : Orbital hydatid disease is a rare lesion accounting for less than 1% of the total lesions of the body (1, 2). Orbital cysts presented as a primary lesion in our study which is rare to have such lesion without involvement of other organs (3). Humans represent the intermediate host where the commonly affected organ are liver and the lung (10-15%) (4). Methods:This is a prospective study of three Children presented to us in the Orbital clinic in Al Shahid Ghazi Alhariri Hospital with painless proptosis with suspension of Hydatid disease, dep
... Show MoreResearchers have recently increased their focus on the link between autoimmune diseases and infections. Most of the recent research indicates that silent human cytomegalovirus (HCMV), may have diverse roles in the initiation, development, and exacerbation of autoimmune diseases, such as coeliac Disease (CD) and inflammatory bowel disease. The aim of this study is to evaluate the role of HCMV infection in Iraqi patients with CD. Serum samples were obtained from 60 patients with CD, and from 60 healthy subjects. Enzyme-linked immunosorbent assay was used to determine the Anti-Transglutaminase IgG/IgA, Anti-gliadin IgA/ IgG, as well as the HCMV IgM/ IgG levels in the serum samples. Significantly higher percentage of positivity for seru
... Show MoreThe logistic regression model is one of the oldest and most common of the regression models, and it is known as one of the statistical methods used to describe and estimate the relationship between a dependent random variable and explanatory random variables. Several methods are used to estimate this model, including the bootstrap method, which is one of the estimation methods that depend on the principle of sampling with return, and is represented by a sample reshaping that includes (n) of the elements drawn by randomly returning from (N) from the original data, It is a computational method used to determine the measure of accuracy to estimate the statistics, and for this reason, this method was used to find more accurate estimates. The ma
... Show More