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Diagnostic accuracy of laparoscopy following computed tomography (CT) scanning for assessing the resectability with curative intent in pancreatic and periampullary cancer

Overview of attention for article published in this source, November 2013
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6 X users
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3 Wikipedia pages

Citations

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Title
Diagnostic accuracy of laparoscopy following computed tomography (CT) scanning for assessing the resectability with curative intent in pancreatic and periampullary cancer
Published by
John Wiley & Sons, Ltd, November 2013
DOI 10.1002/14651858.cd009323.pub2
Pubmed ID
Authors

Allen, Victoria B, Gurusamy, Kurinchi Selvan, Takwoingi, Yemisi, Kalia, Amun, Davidson, Brian R

Abstract

Surgical resection is the only potentially curative treatment for pancreatic and periampullary cancer. A considerable proportion of patients undergo unnecessary laparotomy because of underestimation of the extent of the cancer on computed tomography (CT) scanning. Laparoscopy can detect metastases not visualised on CT scanning, enabling better assessment of the spread of cancer (staging of cancer). There has been no systematic review or meta-analysis assessing the role of diagnostic laparoscopy in assessing the resectability with curative intent in patients with pancreatic and periampullary cancer.

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X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 1 2%
Unknown 53 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 22%
Student > Doctoral Student 9 17%
Student > Master 6 11%
Student > Ph. D. Student 5 9%
Other 3 6%
Other 9 17%
Unknown 10 19%
Readers by discipline Count As %
Medicine and Dentistry 30 56%
Social Sciences 3 6%
Immunology and Microbiology 1 2%
Nursing and Health Professions 1 2%
Agricultural and Biological Sciences 1 2%
Other 1 2%
Unknown 17 31%