Related Experiment Video
Updated: Oct 15, 2025

Structured Approach to Colonoscopy Technique Optimization: A Single-Center Experience with Novice Endoscopists
Published on: July 11, 2025
The analysis of multilevel factors affecting adenoma detection rates for colonoscopies: a large-scale retrospective
Liang Huang1, Yue Hu1,2, Shan Liu3
1Department of Gastroenterology, First Affiliated Hospital of Zhejiang, Chinese Medical University, 54 Youdian Road, Hangzhou, Zhejiang, China.
Background:
Adenoma detection rate (ADR) is a validated primary quality indicator for colonoscopy procedures. However, there is growing concern over the variability associated with ADR indicators. Currently, the factors that influence ADRs are not well understood.
Aims:
In this large-scale retrospective study, the impact of multilevel factors on the quality of ADR-based colonoscopy was assessed.
Methods:
A total of 10,788 patients, who underwent colonoscopies performed by 21 endoscopists between January 2019 and December 2019, were retrospectively enrolled in this study. Multilevel factors, including patient-, procedure-, and endoscopist-level characteristics were analyzed to determine their relationship with ADR.
Results:
The overall ADR was 20.21% and ranged from 11.4 to 32.8%. Multivariate regression analysis revealed that higher ADRs were strongly correlated with the following multilevel factors: patient age per stage (OR 1.645; 95% CI 1.577-1.717), male gender (OR 1.959; 95% CI 1.772-2.166), sedation (OR 1.402; 95% CI 1.246-1.578), single examiner colonoscopy (OR 1.330; 95% CI 1.194-1.482) and senior level endoscopists (OR 1.609; 95% CI 1.449-1.787).
Conclusion:
The ADR is positively correlated with senior level endoscopists and single examiner colonoscopies in patients under sedation. As such, these procedure- and endoscopist-level characteristics are important considerations to improve the colonoscopy quality.
More Related Videos
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Related Concept Videos
Comparing the Survival Analysis of Two or More Groups
Cancer Survival Analysis