Background: Gray-scale sonography is generally
considered as a first-line diagnostic tool for patient with
suspected acute cholecystitis. It is suggested by gallstones,
Murphy's sign, thickening of the gallbladder wall and bile
sludging, but the specificity of these sonographic findings
are not as high as their sensitivity. Blood flow of the
gallbladder wall is increased in acute inflammation.
Objective: To evaluate the sensitivity and specificity of
power Doppler sonography and compared with conventional
color Doppler and gray-scale sonography in diagnosing
patients with acute cholecystitis.
Type of the study: This was a cross sectional study.
Patients and methods: The study was conducted through
the period from August 2014 to August 2015 on 80 patients
with acute right upper quadrant abdominal pain and
clinically suspected acute cholecystitis. Firstly, gray-scale
sonography of the abdomen was performed. Next, color
Doppler and power Doppler sonography of the gallblader
wall was done to detect mural flow. Quantifying intramural
vascularity was performed using Uggowitzer scoring
system. Grading of vascularity ++ and +++ were suggestive
of acute cholecystitis. Results of gray-scale and Doppler
sonography were compared with post cholecystectomy
histopathological results.
ABSTRACTBackground: Concerns about hepatitis A infections is increasing worldwide specially after improving economic and sanitary conditions in many countries making older age groups who escape infection on early life vulnerable to infection.Objectives: The objectives were to estimate the frequency of hepatitis A among children consulting Al Alwyia pediatric Teaching Hospital during the year 2013 and to study some demographic characteristics of the disease.Methods: This cross - sectional hospital -based study wasconducted during 2013-2014 and include pediatric patients(43525 patients) who consult Al Alwyia pediatric hospitalduring that time. The outcome is total IgM antibodies tohepatitis A virus detected using Enzyme Linked FluorescentA
... Show MoreThe study deals with reactivity insertion linear and non linear and/or Ramp reactivity expressed as a polynomial in time in the presence of two Feedback mechanisms, using the neutronic-thermohydraulic coupling in order to predict the neutron behavior as a function of time in terms of reactor power. Also, a comparative study has been achieved in the case of the presence of the feedback mechanisms. Insertion of Ramp reactivities in terms of polynomial in time to study the behavior of power and reactivity as a function of time in the presence of two feedback mechanisms (fuel and coolant) has been carried out and the results are displayed as plots, and showed this results corresponding with international results. The present study shows t
... Show MoreEight patients (3 male and 5 female) were treated in this study by Endovenous Laser Ablation (EVLA); Mathematical models are proposed to estimate the applied laser power and to assess the recovery period. The estimations of the applied laser power and recovery period in these models will be depended mainly on the diameter of the incompetent vein. In addition, Excel Program was utilized to find the proposed models. A 1470 nm diode laser up to 15W continuous power (CW) was used in the treatment of venous ulcers by EVLA procedure. Following up by duplex ultrasound was started in the 1st week after the first session until the vein is completely closed. The present study concluded that the relationship both between
... Show Morehemorrhagic fever (VHF), one of which is Filoviridae. The Filoviridae family includes the Ebola virus , is responsible for the current VHF outbreak in West Africa. Viral hemorrhagic fevers (VHFs) occur in various regions around the world, yet traditional diagnostic testing for these diseases has typically been conducted in major reference laboratories located in Europe and the United States. In this review, we explore the current understanding of the mechanisms driving the pathogenesis of viral hemorrhagic fevers (VHFs) and examine the progress in developing preventive and therapeutic strategies for these infections.
After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings
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