Literature DB >> 28842052

Polyp detection at colonoscopy: Endoscopist and technical factors.

Douglas K Rex1.   

Abstract

The adenoma detection rate (ADR) has emerged as the most important quality measure in colonoscopy, as it predicts the risk of interval cancer after colonoscopy. Measuring and improving ADR is the central focus of the current quality movement in colonoscopy. High ADRs can be achieved by a colonoscopist with a thorough understanding of the wide range of endoscopic appearances of precancerous lesions in the colorectum, effective bowel preparation, and meticulous technique using high definition colonoscopes. The knowledgeable and effective examiner needs no adjunctive devices or techniques to achieve master level ADRs. However, measurement reveals that many colonoscopists have ADRs that are below recommended minimum thresholds or below master levels. These colonoscopists, and even master level performers, can choose from a variety of adjunctive tools to improve ADR. This review describes these tools according to whether they are non-device methods (e.g. double right colon examination, patient position change, water exchange), mucosal exposure devices (wide angle colonoscopy, fold flattening devices), and lesion highlighting techniques (e.g. chromoendoscopy, electronic chromoendoscopy).
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Adenoma detection rate; Colon polyps; Colonoscopy; Colorectal cancer; Quality

Mesh:

Year:  2017        PMID: 28842052     DOI: 10.1016/j.bpg.2017.05.010

Source DB:  PubMed          Journal:  Best Pract Res Clin Gastroenterol        ISSN: 1521-6918            Impact factor:   3.043


  9 in total

1.  Adenoma detection rate: is it the master key for the colonoscopy quality indicator?

Authors:  Su Young Kim; Hyun-Soo Kim
Journal:  Transl Gastroenterol Hepatol       Date:  2018-01-19

Review 2.  Burden and Cost of Gastrointestinal, Liver, and Pancreatic Diseases in the United States: Update 2018.

Authors:  Anne F Peery; Seth D Crockett; Caitlin C Murphy; Jennifer L Lund; Evan S Dellon; J Lucas Williams; Elizabeth T Jensen; Nicholas J Shaheen; Alfred S Barritt; Sarah R Lieber; Bharati Kochar; Edward L Barnes; Y Claire Fan; Virginia Pate; Joseph Galanko; Todd H Baron; Robert S Sandler
Journal:  Gastroenterology       Date:  2018-10-10       Impact factor: 22.682

3.  The contribution of endoscopy quality measures to the development of interval colorectal cancers in the screening population: a systematic review.

Authors:  Deirdre M Nally; Athena Wright Ballester; Gintare Valentelyte; Dara O Kavanagh
Journal:  Int J Colorectal Dis       Date:  2018-10-29       Impact factor: 2.571

4.  A prospective RCT comparing combined chromoendoscopy with water exchange (CWE) vs water exchange (WE) vs air insufflation (AI) in adenoma detection in screening colonoscopy.

Authors:  J W Leung; A W Yen; H Jia; C Opada; A Melnik; J Atkins; C Feller; M D Wilson; F W Leung
Journal:  United European Gastroenterol J       Date:  2019-02-19       Impact factor: 4.623

Review 5.  Increase your adenoma detection rate without using fancy adjunct tools.

Authors:  Yu-Hsi Hsieh; Felix W Leung
Journal:  Ci Ji Yi Xue Za Zhi       Date:  2018 Jul-Sep

6.  How to improve the adenoma detection rate in colorectal cancer screening? Clinical factors and technological advancements.

Authors:  Maciej Matyja; Artur Pasternak; Mirosław Szura; Michał Wysocki; Michał Pędziwiatr; Kazimierz Rembiasz
Journal:  Arch Med Sci       Date:  2018-04-06       Impact factor: 3.318

7.  Implicit domain adaptation with conditional generative adversarial networks for depth prediction in endoscopy.

Authors:  Anita Rau; P J Eddie Edwards; Omer F Ahmad; Paul Riordan; Mirek Janatka; Laurence B Lovat; Danail Stoyanov
Journal:  Int J Comput Assist Radiol Surg       Date:  2019-04-15       Impact factor: 2.924

8.  Unsupervised Monocular Depth Estimation for Colonoscope System Using Feedback Network.

Authors:  Seung-Jun Hwang; Sung-Jun Park; Gyu-Min Kim; Joong-Hwan Baek
Journal:  Sensors (Basel)       Date:  2021-04-11       Impact factor: 3.576

9.  Artificial intelligence-based assessments of colonoscopic withdrawal technique: a new method for measuring and enhancing the quality of fold examination.

Authors:  Wei Liu; Yu Wu; Xianglei Yuan; Jingyu Zhang; Yao Zhou; Wanhong Zhang; Peipei Zhu; Zhang Tao; Long He; Bing Hu; Zhang Yi
Journal:  Endoscopy       Date:  2022-04-07       Impact factor: 9.776

  9 in total

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