Comparison of colon adenoma detection rate using cap-assisted and artificial intelligence-assisted colonoscopy at a tertiary hospital in the Philippines: a propensity score-matched analysis
- Author:
Justin Ryan Lay TAN
1
;
Keith Brian Tan ENRIQUEZ
;
Kenneth Vergel Tecson ABALLE
;
Mary Anne Gonzales GO
;
Michael Louie Ong LIM
;
Jonard Tan CO
Author Information
- Publication Type:Original Article
- From:Clinical Endoscopy 2026;59(1):106-114
- CountryRepublic of Korea
- Language:English
-
Abstract:
Background/Aims:The integration of artificial intelligence (AI)-powered image analysis and mucosal exposure devices, such as distal attachment caps, has been demonstrated to significantly improve the adenoma detection rate (ADR) during colonoscopy. This study aimed to compare AI-assisted colonoscopy (AIC) with cap-assisted colonoscopy (CAC).
Methods:This retrospective propensity score-matched cohort study was performed at a tertiary care hospital between January 2022 and May 2022. Data were extracted from the electronic health record system and colonoscopy video recordings. Adult patients aged 40 years who underwent screening or surveillance colonoscopies were included. The primary outcome was the ADR, whereas the secondary outcome was the polyp detection rate (PDR).
Results:A 1:1 propensity score-matched analysis was performed, resulting in 49 well-matched patient pairs. One patient from each pair was assigned to the CAC group, whereas the other was assigned to the AIC group. No significant difference in ADR was observed between the CAC and AIC groups (47% vs. 51%, p=0.69). Similarly, PDR did not significantly differ between the two groups (80% vs. 71%, p=0.35).
Conclusions:Both CAC and AIC have the potential to increase ADR and PDR. However, neither modality offers a significant advantage.
