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Abdominal vascular emergencies: US and CT assessment

Overview of attention for article published in The Ultrasound Journal, July 2013
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Title
Abdominal vascular emergencies: US and CT assessment
Published in
The Ultrasound Journal, July 2013
DOI 10.1186/2036-7902-5-s1-s10
Pubmed ID
Authors

Eugenio Annibale Genovese, Paolo Fonio, Chiara Floridi, Monica Macchi, Anna Maccaferri, Antonio Amato Stabile Ianora, Lucio Cagini, Gianpaolo Carrafiello

Abstract

Acute vascular emergencies can arise from direct traumatic injury to the vessel or be spontaneous (non-traumatic).The vascular injuries can also be divided into two categories: arteial injury and venous injury.Most of them are life-treatening emergencies, sice they may cause an important ipovolemic shock or severe ischemia in their end organ and require prompt diagnosis and treatment.In the different clinical scenarios, the correct diagnostic approach to vascular injuries isn't firmly established and advantages of one imaging technique over the other are not obvious.Ultrasound (US) is an easy accessible, safe and non-invasive diagnostic modality but Computed Tomography (CT) with multiphasic imaging study is an accurate modality to evaluate the abdominal vascular injuries therefore can be considered the primary imaging modality in vascular emergencies.The aim of this review article is to illustrate the different imaging options for the diagnosis of abdominal vascular emergencies, including traumatic and non traumatic vessel injuries, focusing of US and CT modalities.

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Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 7 15%
Other 6 13%
Researcher 6 13%
Professor > Associate Professor 6 13%
Student > Postgraduate 4 9%
Other 11 23%
Unknown 7 15%
Readers by discipline Count As %
Medicine and Dentistry 34 72%
Nursing and Health Professions 2 4%
Computer Science 1 2%
Engineering 1 2%
Unknown 9 19%