Background: Deep vein thrombosis is a multi causal disease and its one of most common venous disorder, but only one quarter of the patients who have signs and symptoms of a clot in the vein actually have thrombosis and need treatment .The disease can be difficult to diagnose. Venous ultrasound in combination with clinical finding is accurate for venous thromboembolism, its costly because a large number of patients with suspicious signs and symptoms. Venography still the gold standard for venous thromboembolism but it is invasive. The D-dimer increasingly is being seen as valuable tool rolling out venous thromboembolism and sparing low risk patients for further workup.Objectives: this study has designed the role of D-dimer to confirm diagnosis of deep vein thrombosis for patients with positive Doppler and those show no features of thrombosis in Doppler using more accurate and sensitive instrument measuring the concentration of D- dimer.Methods: Thirty patients with deep vein thrombosis diagnosed by Doppler and clinical signs and symptoms (for those with negative Doppler) assessed for D- dimer by automachine cormy accent 200 based on immunoassay which more sensitive than the ordinary methods.Results: Twenty-eight patients out of thirty shows a significant elevation of D-dimer compared to control group which show no elevation in D- dimer level. On other side higher level of D- dimer found in those with negative Doppler as same as level to the patients with positive Doppler.Conclusion: Patients with clinical sign and symptoms of deep vein thrombosis and negative Doppler should be assessed for D- dimer using more sensitive technique based on immunological assay.Key words: deep vein thrombosis (DVT) pulmonary embolism (PE), Doppler
The present study investigates the realization and significance of textual themes in the organizational structure of M.A theses and Ph.D. dissertations, namely: the abstracts, introductions and conclusions, since in such parts the students depend on their own expressions, styles and constructions to express different viewpoints, plans, inferences, etc. The study also investigates the similarities and differences between M.A theses and Ph.D. dissertations concerning the use of textual themes;it sets out to conduct a detailed analysis of textual themes used in such texts. In conducting such an analysis, the study adopts Halliday's (1994) approach of textual themes. The results of such an analysis have clearly shown that, in spite of the di
... Show MoreSemantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po
The study aims to reveal the degree of application of the alternative evaluation strategy in social studies in public education in the Kingdom of Saudi Arabia. It also aims to identify the opinions of experts on how to implement this. The study adopted the mixed methodology, which represented in the descriptive-analytical method, and qualitative methods through the grounded theory. The study used two tools namely: a questionnaire for assessments of social studies teachers and semi-structured interview questions. The results of the study showed a medium degree of appreciation for the application of alternative evaluation strategies by social studies teachers in general education with an average of (2.28). The results also showed that ther
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreA chemical study was carried out to evaluate the efficiency of the liver enzyme concertation and uric acid level and its antagonists in the serum of the professors exposed to chemicals in the laboratories of the University of Samarra and their comparison with the healthy people. The research included 25 samples of the exposed professors and 20 samples as a group of officers.
The results of the current study showed a significant increase in the level of AST, ALT in the serum of professors exposed to chemicals compared to healthy people. The results showed no significant increase in
... Show MorePurpose: The diagnosis and determine the level of balance between the time available for life and work with the doctors in the hospitals of t the six hospitals in the City of Medicine.
Design / methodology / Approach: It has been relying on ready-scale, to make sure the diagnosis and determine the level of balance between the time available for life and work, where they were distributed on Form 42 doctors in the six hospitals in the City of Medicine, were analyzed by software (Nvivo and SPSS v.22).
Results: The results showed that there is a good level of balance between the time available for life and work with the doctors.
Research limitations: The diffi
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