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Double-Scope Peroral Endoscopic Myotomy (POEM) for Esophageal Achalasia: The First Trial of a New Double-Scope POEM

Overview of attention for article published in Clinical Endoscopy, March 2016
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Title
Double-Scope Peroral Endoscopic Myotomy (POEM) for Esophageal Achalasia: The First Trial of a New Double-Scope POEM
Published in
Clinical Endoscopy, March 2016
DOI 10.5946/ce.2015.108
Pubmed ID
Authors

Hee Jin Hong, Ga Won Song, Weon Jin Ko, Won Hee Kim, Ki Baik Hahm, Sung Pyo Hong, Joo Young Cho

Abstract

With the accumulation of clinical trials demonstrating its efficacy and safety, peroral endoscopic myotomy (POEM) has emerged as a less invasive treatment option for esophageal achalasia compared with laparoscopic Heller myotomy. However, the difficulty in determining the exact extent of myotomy, a critical factor associated with the success and safety of the procedure, remains a limitation. Although the various endoscopic landmarks and ancillary techniques have been applied, none of these has been proven sufficient. As a solution for this limitation, the double-scope POEM technique with a second endoscope to assure the exact length of the submucosal tunnel has been applied since 2014. Before double-scope POEM was introduced, the second endoscope was applied only to confirm the accuracy of the procedure. In the present study, we performed double-scope POEM in the treatment of esophageal achalasia through a novel procedure of simultaneous application of the second endoscope to assist in the conventional POEM procedure.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 2 33%
Professor > Associate Professor 1 17%
Researcher 1 17%
Student > Postgraduate 1 17%
Unknown 1 17%
Readers by discipline Count As %
Medicine and Dentistry 4 67%
Unknown 2 33%