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Prevalence of Anxiety and Depression Symptoms among Post Bariatric Surgery Patients in Baghdad-Iraq
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Background: Obesity is a major public health concern and is on the rise worldwide. Numerous studies revealed that the best method for treating morbid obesity is bariatric surgery, which has indicated its effectiveness in controlling weight. Published studies reported that patients who had undergone bariatric surgery may have psychiatric illnesses when compared to other obese individuals with similar preoperative characteristics.

Objectives:  Estimate the rates of anxiety and depression among post-operative bariatric surgery patients.

Methods: A cross-sectional study on 61 patients was conducted at the bariatric clinic in the Gastroenterology and Hepatology Baghdad teaching hospital and the Private Nursing Home Hospital in Medical city, Baghdad-Iraq from 1st of April to the 30th of December 2021. Generalized Anxiety Assessment – 7 (GAD-7) Scale, and Patient Health Questionnaire – 9 (PHQ-9) scale were applied to assess these conditions.

Results: The prevalence of depression among the studied patients was 32.8%, while the prevalence of anxiety was 44.3%. Marital status, diabetes mellitus, post-operative BMI, and past psychiatric history were significantly associated with depression, P value < 0.05. Chronic diseases (diabetes mellitus and hypertension), post-operative BMI,nd psychiatric history were significantly associated with anxiety, P value<0.05.

Conclusions: Anxiety was found to be more common than depression among patients who underwent bariatric surgery. Variables predicting both depression and anxiety were diabetes mellitus, post-operative severe obesity, and a history of psychiatric disorders before surgery.

Received May. 2023

Accepted July 2023

Published Jan. 2023

 

J. Fac. Med. Baghdad

2023. Vol 65, No. 4

 

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Publication Date
Mon Oct 01 2018
Journal Name
International Journal Of Biosciences
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Fri May 19 2017
Journal Name
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Mon Jun 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Study the Effect Different Radioactive Dose on Mechanical Properties of Composite Material from Novolak Resin Exposure to High – Energy Radiation
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The research involves using phenol – formaldehyde (Novolak) resin as matrix for making composite material, while glass fiber type (E) was used as reinforcing materials. The specimen of the composite material is reinforced with (60%) ratio of glass fiber.

      The impregnation method is used in test sample preparation, using molding by pressure presses.

      All samples were exposure to (Co60) gamma rays of an average energy (2.5)Mev. The total doses were (208, 312 and 728) KGy.

      The mechanical tests (bending, bending strength, shear force, impact strength and surface indentation) were performed on un irradiated and irrad

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Choosing the best method for estimating the survival function of inverse Gompertz distribution by using Integral mean squares error (IMSE)
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In this research , we study the inverse Gompertz distribution (IG) and estimate the  survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Choosing the best method for estimating the survival function of inverse Gompertz distribution by using Integral mean squares error (IMSE)
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In this research , we study the inverse Gompertz distribution (IG) and estimate the  survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
An Integrated Information Gain with A Black Hole Algorithm for Feature Selection: A Case Study of E-mail Spam Filtering
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     The current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,

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Publication Date
Mon Jan 20 2020
Journal Name
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Assessment of Long Distance Chasing Photometer (NAG-ADF-300-2) by Estimating the Drug Atenolol with Povidone Iodine Via CFIA
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     Atenolol was used with povidone iodine to prove the efficiency, reliability and repeatability of the long distance chasing photometer (NAG-ADF-300-2) using continuous flow injection analysis. The method is based on reaction between atenolol and povidone iodine in an aqueous medium. Optimum parameters was studied to increase the sensitivity development of method. Calibration graph was linear in the range of 2-19 mmol/L for cell A and 5-19 mmol/L for cell B. Limit of detection 146.4848 ng/55 µL and 2.6600 µg/200 µL respectively to cell A and cell  B. Correlation coefficient (r) 0.9957 for cell A and 0.9974 for cell. Relative standard deviation (RSD %) was lower than 1%, (n=8) for the determination of

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Publication Date
Sat Apr 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Use aggregate slide estimate additive splines estimation for the diagnosis of non-linear composite model self-regression with practical application
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Nonlinear time series analysis is one of the most complex problems ; especially the nonlinear autoregressive with exogenous variable (NARX) .Then ; the problem of model identification and the correct orders determination considered the most important problem in the analysis of time series . In this paper , we proposed splines  estimation method for model identification , then we used three criterions for the correct orders determination. Where ; proposed method used to estimate the additive splines for model identification , And the rank determination depends on the additive property  to avoid the problem of curse dimensionally . The proposed method is one of the nonparametric methods , and the simulation results give a

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