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Comorbidity and Risk Factors for COVID-19 Confirmed Patients in Wasit Province, IRAQ
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Background: Coronavirus disease 2019 (COVID-19) is
one of the updated challenges facing the whole world.
Objective: To identify the characteristics risk factors that
present in humans to be more liable to get an infection
than others.
Methods: A cross-sectional study was conducted for
positively confirmed 35 patients with polymerase chain
reaction in Wasit province at AL-Zahraa Teaching
Hospital from the period of March 13th till April 20th. All
of them full a questionnaire regarded by risk factors and
other comorbidities. Data were analyzed by SPSS version
23 using frequency tables and percentage. For numerical
data, the median, and interquartile range (IQR) were used.
Differences between categorical groups were performed by
fissure exact test.
Results: The median age of the patients was 43 years old
and interquartile range (25-56 years). Majority of the
patients were female (60%) and (51%) of them were from
the same region (AL-ezza). The dominant blood group
among patients was (O) (40%). About 11.4% of patients
had a travel history especially to Islamic Republic of Iran,
while (77.1%) had contact with positive cases. The highest
percentage of comorbidities among patients was
hypertension (40%), and the most presenting symptoms
were cough and fever. About 51% of patients were with
mild symptoms. Diabetes, coronary heart diseases, and
chronic renal diseases were significantly related to disease
severity (P-value=0.02, 0.001, 0.01 respectively).
Conclusion: Being a female, overweight or obese, and
with blood group (O) are the major risk factors among
patients. Comorbidities can play an important role in the
severity of disease especially hypertension, diabetes,
coronary heart diseases, and chronic renal diseases.

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Publication Date
Wed Dec 22 2021
Journal Name
Plos One
Awareness and preparedness of healthcare workers against the first wave of the COVID-19 pandemic: A cross-sectional survey across 57 countries
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Background

Since the COVID-19 pandemic began, there have been concerns related to the preparedness of healthcare workers (HCWs). This study aimed to describe the level of awareness and preparedness of hospital HCWs at the time of the first wave.

Methods

This multinational, multicenter, cross-sectional survey was conducted among hospital HCWs from February to May 2020. We used a hierarchical logistic regression multivariate analysis to adjust the influence of variables based on awareness and preparedness. We then used association rule mining to identify relationships between HCW confidence in handling suspected

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Publication Date
Wed Jan 01 2020
Journal Name
Studies In Big Data
COVID-19 Diagnostics from the Chest X-Ray Image Using Corner-Based Weber Local Descriptor
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Corona Virus Disease-2019 (COVID-19) is a novel virus belongs to the corona virus's family. It spreads very quickly and causes many deaths around the world. The early diagnosis of the disease can help in providing the proper therapy and saving the humans' life. However, it founded that the diagnosis of chest radiography can give an indicator of coronavirus. Thus, a Corner-based Weber Local Descriptor (CWLD) for COVID-19 diagnostics based on chest X-Ray image analysis is presented in this article. The histogram of Weber differential excitation and gradient orientation of the local regions surrounding points of interest are proposed to represent the patterns of the chest X-Ray image. Support Vector Machine (SVM) and Deep Belief Network (DBN)

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Publication Date
Sun Sep 06 2009
Journal Name
Baghdad Science Journal
Cox proportion hazard model for patients with hepatitis disease in Iraq
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Cox regression model have been used to estimate proportion hazard model for patients with hepatitis disease recorded in Gastrointestinal and Hepatic diseases Hospital in Iraq for (2002 -2005). Data consists of (age, gender, survival time terminal stat). A Kaplan-Meier method has been applied to estimate survival function and hazerd function.

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Publication Date
Tue Apr 20 2021
Journal Name
Ndian Journal Of Forensic Medicine & Toxicology,
Detection Levels of Cytokines (IL-6 and IL-18) and Microbial Parameters in Patients with Renal Failure in Diyala Province
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Publication Date
Sun Jun 30 2024
Journal Name
Anbar Journal Of Agricultural Sciences
ESTIMATION OF MARKETING EFFICIENCY AND PRODUCTION QUANTITY AT THE BREAK-EVEN POINT FOR COTTON FARMERS IN IRAQ (BAGHDAD PROVINCE: A CASE STUDY)
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Publication Date
Sun Oct 02 2016
Journal Name
Journal Of Educational And Psychological Researches
Personality Types According to Holland's Theory and its Relationship with the Management Changing for some Administrators in the Province of Kurdistan-Iraq
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The figure of personality modes determines its privileged style in the use of modern and advanced technological tools in the process of changing and developing in order to keep up with that. The proses of selection and choosing administrators in the appropriate places are the most important functions of senior management because it is easy to adopt factory buildings or establishments But this is a human world as that of machines world. So it is required to have people in the process of changing those who have a time, Knowledge, skill, ability and strong administrative personal skills, those people (leaders) should to put a clear vision for the selection and application of the change efforts and to create the necessary climate and

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Assessing the Activity of Renin and GST in the Serum of Ladies Suffering from Polycystic Ovary Syndrome and COVID-19 to Predict the Danger of Cardiac Disease
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The coronavirus-pandemic has a major impact on women's-mental and physical-health. Polycystic-ovary-syndrome (PCOS) has a high-predisposition to many cardiometabolic-risk factors that increase susceptibility to severe complications of COVID-19 and also exhibit an increased likelihood of subfertility. The study includes the extent of the effect of COVID-19-virus on renin-levels, glutathione-s-transferase-activity and other biochemical parameters in PCOS-women. The study included 120 samples of ladies that involved: 80 PCOS-patients, and 40 healthy-ladies. Both main groups were divided into subgroups based on COVID-19 infected or not. Blood-samples were collected from PCOS-patients in Kamal-Al-Samara Hospital, at the period between Decembe

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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Using Factor Analysis In Determine the Important Influenced Factors In Student Outcomes Pheonema From Primary School In The Province Of Baghdad
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Abstract

The Purpose of This Research is The  Main Factors  In out Comes Phenomena From Primary School Which in Creased in Lost Period in Iraq And to Find Solutions to The This Problem.

In Order to Achieve Al The Aim The Research Choose a Systematic Random Sample of School Records For Students in Some Primary Schools in Karkh and Rusafa and Year of Study (2010-2015) and Size (40) Samples, included  (16) Variable , Collected in Form Prepared by The Research As a Way to Analyze The Data.

Remember to Summarize The (6) Main components Pay a Student to Drop out of Primary Schools in The Province of Baghdad are Arranged As Follows:

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Publication Date
Wed Jan 08 2020
Journal Name
Nursing & Health Sciences
Medication adherence and predictive factors in patients with cardiovascular disease: A cross‐sectional study
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Abstract<p>Adherence to cardiac medications makes a significant contribution to avoidance of morbidity and premature mortality in patients with cardiovascular disease. This quantitative study used cross‐sectional survey design to evaluate medication adherence and contributing factors among patients with cardiovascular disease, comparing patients who were admitted to a cardiac ward (<italic>n</italic> = 89) and those attending outpatient cardiac rehabilitation (<italic>n</italic> = 31) in Australia. Data collection was completed between October 2016 and December 2017. Descriptive and regression analyses were conducted to identify medication adherence and determine factors independently pred</p> ... Show More
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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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