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Analysis of the variation in learning curves for achieving competency in convex EUS training: a prospective cohort study using a standardized assessment tool by Masafumi Chiba; Masayuki Kato; Yuji Kinoshita; Takafumi Akasu; Hiroaki Matsui; Nana Shimamoto; Youichi Tomita; Takahiro Abe; Keisuke Kanazawa; Shintaro Tsukinaga; Masanori Nakano; Yuichi Torisu; Hirobumi Toyoizumi; Machi Suka; Kazuki Sumiyama is a Medicine article available to read on EtoBox.
What is Analysis of the variation in learning curves for achieving competency in convex EUS training: a prospective cohort study using a standardized assessment tool about?
Background and Aims The need for mastering standard imaging techniques for convex EUS in the biliopancreatic regions has been increasing; however, large variations in the aptitude for achieving EUS competency hinder expert development. Therefore, we investigated the factors influencing the achievement of expert competency in EUS using a new assessment tool for multiple imaging items. Methods Between January 2018 and February 2022, 3277 consecutive EUS procedures conducted by 5 beginners (EUS procedures <250), 7 intermediate trainees (250-749), and 2 experts (≥750) were prospectively evaluated. Immediately after each EUS procedure, the success or failure of imaging for each item was recorded using a newly developed EUS assessment tool that requires 17 items to be photographed. After correcting for missing values using multiple imputation, learning curves of EUS scores were created, and a competency was set based on expert scores. Finally, a comparative analysis between high and low performers was performed to extract factors influencing EUS scores. Results Although 3 of 7 intermediates (43%; mean, 317 cases) achieved competency, none of the beginners achieved competency. During a co
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- Author
- Masafumi Chiba; Masayuki Kato; Yuji Kinoshita; Takafumi Akasu; Hiroaki Matsui; Nana Shimamoto; Youichi Tomita; Takahiro Abe; Keisuke Kanazawa; Shintaro Tsukinaga; Masanori Nakano; Yuichi Torisu; Hirobumi Toyoizumi; Machi Suka; Kazuki Sumiyama
- Publisher
- Elsevier BV
- Published
- 2023
- Language
- EN
- Field
- Medicine (Health Sciences)