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H1N1 INFLUENZA VERSUS SEASONAL INFLUENZA MORBIDITY AND MORTALITY: A PROSPECTIVE STUDY IN AL-KINDY TEACHING HOSPITAL/ IRAQ-BAGHDAD
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Background: H1N1 influenza pandemic or swine flu was an influenza pandemic first described in Iraq in October 2009 .The virus appeared to be anew strain of H1N1 causes wide range of morbidity and mortality among different genders and age groups as part of worldwide pandemics.Seasonal flu is a contagious respiratory illness caused by influenza viruses that infect the nose, throat, and lungs. It can cause mild to severe illness, and at times can lead to death. The best way to prevent the flu is by getting a flu vaccine each year.

Objectives: Is to determine the morbidity and mortality in different age groups in patients with H1N1 influenza versus those patients with seasonal influenza who were admitted at the same time to AL-kindy teaching hospital during pandemic 2009. Type of the study: A retrospective observational study.

Methods: A total number of 210 cases with influenza symptoms and signs were included in this study which was conducted at AL-kindy teaching hospital , Baghdad, Iraq at inpatient medical wards over a period from October to December 2009. All cases were tested by real time PCR for H1N1 influenza virus by taking nasal and throat swab in addition to monitoring symptoms and signs of influenza and chest radiographs.

Results: Out of 210 cases, 90 (42.85%) cases were positive for H1N1 influenza and 120 (57.14%) cases had negative test are considered having seasonal influenza. Of the positive cases(64.44%) were males and (35.55%) were females. Of negative cases(seasonal flu)male gender were (61.66%) , while female gender were (38.33%). 57.77% of positive cases developed flue like illness compared with 54.16% of negative while 25.55% of positive developed pneumonia compared with 22.5% of negative.5.55% of positive cases developed ARDS compared with 5% only in negative cases.11.11% had different presentation in positive cases (bronchitis ,gastroenteritis) while 18.33%of negative. Mortality in positive cases are 14.4% compared with only 10% in negative cases.

Conclusions: Influenza A/H1N1had same symptoms and signs of epidemic seasonal influenza but run aggressive and short course of morbidity in 3-5 days with high percentage of complication and high mortality compared with seasonal epidemic influenza with rare affection above 65 years old, both groups had same incidence of complication with pneumonia and ARDS

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Indian Academy Of Oral Medicine And Radiology
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Publication Date
Thu Nov 09 2023
Journal Name
Beirut: Al-arif Publishing House
Arabic-English Dictionary of Euphemistic and Non-literal Expressions in the Glorious Qur’an
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Lipid Peroxidation and Antioxidant Status in β-Thalassemic Patients: Effect of Iron Overload
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Publication Date
Sun Feb 03 2019
Journal Name
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Iraq's Position For Lebanese Civil War 1975-1976 in Iraqi and Arabian Newspapers
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The research focused on the Iraq's position towards the externd proposed solutions to solve the Lebanese civil war.

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Publication Date
Sat Aug 30 2025
Journal Name
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Seroprevalence and Molecular Detection of Human Parvovirus B19 in Beta Thalassemia Major Patients
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Beta thalassemia major (BTM) is a genetic disorder that has been linked to an increased risk of contracting blood-borne viral infections, primarily due to the frequent blood transfusions required to manage the condition. One such virus that can be transmitted through blood is the Human Parvovirus B19 (B19V). The aim of this study was to investigate the frequency and molecular detection of B19V. This study included 60 blood donors as controls and 120 BTM patients. B19V was identified by serology, which measured B19-IgG and B19-IgM antibodies. Nested Polymerase Chain Reaction (nPCR) was employed to target the VP1/VP2 structural proteins. The results showed that B19V seropositivity represents 27.5% (33 out of 120) in BTM patients, and

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Publication Date
Mon Apr 11 2011
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Employing Neural Network and Naive Bayesian Classifier in Mining Data for Car Evaluation
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In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Publication Date
Mon Apr 04 2022
Journal Name
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Publication Date
Mon Sep 03 2018
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