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External Validation of the Endoscopic Features of Sessile Serrated Adenomas in Expert and Trainee Colonoscopists

Overview of attention for article published in Clinical Endoscopy, September 2016
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Title
External Validation of the Endoscopic Features of Sessile Serrated Adenomas in Expert and Trainee Colonoscopists
Published in
Clinical Endoscopy, September 2016
DOI 10.5946/ce.2016.107
Pubmed ID
Authors

Hyo-Joon Yang, Jeong In Lee, Soo-Kyung Park, Yoon Suk Jung, Jin Hee Sohn, Kyu Yong Choi, Dong Il Park

Abstract

It is unclear whether the endoscopic features of sessile serrated adenomas (SSAs) would be useful to trainee colonoscopists to predict SSA. Therefore, the present study aimed to identify features that expert and trainee colonoscopists can use to independently and reliably predict SSA by using high-resolution white-light endoscopy. Endoscopic images of 81 polyps (39 SSAs, 22 hyperplastic polyps, and 20 tubular adenomas) from 43 patients were retrospectively evaluated by 10 colonoscopists (four experts and six trainees). Eight endoscopic features of SSAs were assessed for each polyp. According to multivariable analysis, a mucous cap (odds ratio [OR], 10.44; 95% confidence interval [CI], 5.72 to 19.07), indistinctive borders (OR, 4.21; 95% CI, 2.74 to 7.16), dark spots (OR, 3.64; 95% CI, 1.89 to 7.00), and cloud-like surface (OR, 2.43; 95% CI, 1.27 to 4.668) were independent predictors of SSAs. Among these, a mucous cap, indistinctive borders, and cloud-like surface showed moderate interobserver agreement (mean κ >0.40) among experts and trainees. When ≥1 of the three predictors was observed, the sensitivity and specificity for diagnosing SSAs were 79.0% and 81.4%, respectively. Colonoscopy trainees and experts can use several specific endoscopic features to independently and reliably predict SSAs.

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Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Librarian 1 20%
Researcher 1 20%
Student > Postgraduate 1 20%
Unknown 2 40%
Readers by discipline Count As %
Medicine and Dentistry 3 60%
Unknown 2 40%