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Randomized controlled study of the prediction of diminutive/small colorectal polyp histology using didactic versus computer-based self-learning module in gastroenterology trainees

  • The Birmingham Colonic Polyp Characterisation Group
  • University of Birmingham
  • University Hospitals Birmingham NHS Foundation Trust
  • Harvard University
  • Birmingham Biomedical Research Centre
  • University of Calgary

Research output: Contribution to journalArticlepeer-review

Abstract

Background and Aim: The aim of this randomized trial was to evaluate the performance of self-training versus didactic training in order to increase the diagnostic accuracy of diminutive/small colonic polyp histological prediction by trainees. Methods: Sixteen trainees reviewed 78 videos (48 iSCAN-OE and 30 NBI) of diminutive/small polyps in a pretraining assessment. Trainees were randomized to receive computer-based self-learning (n = 8) or didactic training (n = 8) using identical teaching materials and videos. The same 78 videos, in a different randomized order, were assessed. The NICE (NBI International Colorectal Endoscopic) and SIMPLE (Simplified Identification Method for Polyp Labeling during Endoscopy) classification systems were used to classify diminutive/small polyps. Results: A higher proportion of high-confidence predictions of polyps was made by the self-training group versus the didactic group using both the SIMPLE classification (77.1% [95% CI 73.4–80.3] vs 69.9% [95% CI 66.1–73.5%] [P = 0.005]) and the NICE classification (77% [95% CI 73.2–80.4%] vs 69.8% [95% CI 66–73.4%] [P = 0.006]). When using NICE, sensitivity of the self-training group compared with the didactic group was 72% versus 83% (P = 0.0005), and the accuracy was 66.1% versus 69.1%. The training improved the confidence of participants and SIMPLE was preferred over NICE. Conclusion: Self-learning for the prediction of diminutive/small polyp histology is a method of training that can achieve results similar to didactic training. Availability of adequate self-learning teaching modules could enable widespread implementation of optical diagnosis in clinical practice.

Original languageEnglish
Pages (from-to)535-543
Number of pages9
JournalDigestive Endoscopy
Volume31
Issue number5
DOIs
Publication statusPublished - 1 Sep 2019
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 4 - Quality Education
    SDG 4 Quality Education

Keywords

  • colonic polyp
  • optical enhancement
  • polyp characterization
  • training module
  • virtual chromoendoscopy

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