Artificial intelligence as a surrogate for inspection time to assess completeness in Esophagogastroduodenoscopy: a prospective, randomized, non-inferiority study
Xia Tan, Liwen Yao, Zehua Dong, Yanxia Li, Yuanjie Yu, Xin Gao, Kai Zhu, Wenhao Su, Haisen Yin, Wen Wang, Chaijie Luo, Jialing Li, Hang You, Huiyan Hu, Wei Zhou, Honggang YuIntroduction:
The completeness of esophagogastroduodenoscopy (EGD) is a prerequisite for detecting lesions. This study aims to explore whether the quality of complete examinations assisted by artificial intelligence (AI) would be comparable to those conducted within the guideline-recommended inspection time.
Methods:
Patients referred for diagnostic, screening, or surveillance EGD were enrolled at Renmin Hospital of Wuhan University. Patients were randomly assigned to two groups in a 1:1 ratio. In the AI-assisted group, endoscopists completed observation of the entire upper gastrointestinal (UGI) tract with AI assistance. In the control group, endoscopists were instructed to spend no less than 7 minutes (min) on each procedure. The primary outcome was the detection rate of neoplastic lesions. Non-inferiority was confirmed when the lower bound of the 95% confidence interval (CI) was greater than the margin of -1.5%.
Results:
1,723 patients were prospectively enrolled between July 3, 2023, and April 7, 2024. 796 and 763 patients in the AI-assisted and control groups were included in the final analysis, respectively. The detection rates of neoplastic lesions in the AI-assisted and control group were 3.14% and 2.36%, respectively, resulting in an absolute proportion difference of 0.78% (95%CI, -0.58%-2.14%; OR 1.342 [95%CI, 0.726-2.480]). The median inspection time was reduced by 1.5 min in the AI-assisted group (6.18[2.87] vs 7.70[1.90],
Conclusions:
Inspection time of complete EGD can be significantly shortened by AI without compromising its quality. These findings provide crucial evidence to support that AI-assisted procedural completeness serves as an objective and effective quality indicator for EGD.