Clinical trial NCT05871814: Artificial Intelligence and Bowel Cleansing Quality
Official title: Strategy for Decreasing Inadequate Bowel Cleansing in Colonoscopy Based on an Artificial Intelligence System: A Randomized and Controlled Study
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Cleansing Quality of the Colon
Lead sponsor: University of La Laguna
Sponsor class: OTHER
First posted: 2023-05-23
Enrollment: 774
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: DIAGNOSTIC

Brief summary: The main purpose of the study is to assess if a strategy based on a mobile application linked to a neural network is useful for guiding colon cleansing in a more personalized way is better than the usual care defined as regular oral and written instructions. The secondary aim will be the acceptance of this artificial intelligence device defined as the proportion of patients assigned to the intervention group that actually used the device.

Detailed description: The patient's perception of colon cleanliness prior to undergoing a colonoscopy has been studied as a predictor of colon cleanliness quality, demonstrating to be a powerful predictor of inadequate cleanliness. A convolutional neural network developed by our group, trained with photographs of rectal effluents at different moments of colon preparation, has achieved high diagnostic accuracy. Based on all this experience, the next step would be to evaluate in a randomized clinical trial whether this neural network integrated into a computer application associated with cleaning recommendations improves the colon cleanliness quality of patients compared to a control group, being the objective of this project Therefore, the main purpose of the study is to assess if a strategy based on a mobile application linked to a neural network is useful for guiding colon cleansing in a more personalized way is better than the usual care defined as regular oral and written instructions. The secondary aim will be the acceptance of this artificial intelligence device defined as the proportion of patients assigned to the intervention group that actually used the device. Consecutive outpatient patients meeting inclusion criteria and none of the exclusion criteria who have been requested to undergo colonoscopy will be included in the study and randomized to mobile artificial intelligence application or control group The intervention group will receive a response from the AI system in order to determine the quality of colon cleansing: adequate preparation or inadequate preparation. In addition, the system will issue specific recommendations based on the quality of cleansing. Patients assigned to the control group will undergo colonoscopy preparation according to standard recommendations.

Eligibility criteria: Inclusion Criteria:

* Age ≥ 18 years.
* Patients referred for outpatient colonoscopy
* Sign informed consent

Exclusion Criteria:

* Incomplete colonoscopy (except for poor bowel preparation)
* Contraindication for colonoscopy
* Allergies.
* Refusal to participate in the study or impairment to sign the informed consent.
* Colectomy (more than 1 segment)
* Dementia with difficulty in the intake of the preparation.
* Inability to use the smartphone application

Primary outcomes:
measure: Quality of bowel cleansing assessed by the Boston Bowel Preparation Scale
timeFrame: 3 months
Secondary outcomes:
measure: Participation rate
timeFrame: 3 months
Other outcomes:
Locations:
city: La Laguna
country: Spain
facility: Hospital Universitario de Canarias
state: Santa Cruz de Tenerife
Study officials:
affiliation: Hospital Universitario de Canarias
name: Antonio Z Gimeno García, MD, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Gimeno-Garcia AZ, Benitez-Zafra F, Hernandez A, Hernandez-Negrin D, Nicolas-Perez D, Hernandez G, Baute-Dorta JL, Cedres Y, Del-Castillo R, Mon J, Jimenez A, Navarro-Davila MA, Rodriguez-Hernandez E, Alarcon O, Romero R, Felipe V, Segura N, Hernandez-Guerra M. Agreement between the perception of colon cleansing reported by patients and colon cleansing assessed by a validated colon cleansing scale. Gastroenterol Hepatol. 2024 Feb;47(2):130-139. doi: 10.1016/j.gastrohep.2023.02.009. Epub 2023 Mar 2. English, Spanish.
citation: Berzin TM, Parasa S, Wallace MB, Gross SA, Repici A, Sharma P. Position statement on priorities for artificial intelligence in GI endoscopy: a report by the ASGE Task Force. Gastrointest Endosc. 2020 Oct;92(4):951-959. doi: 10.1016/j.gie.2020.06.035. Epub 2020 Jun 19.
citation: Mori Y, East JE, Hassan C, Halvorsen N, Berzin TM, Byrne M, von Renteln D, Hewett DG, Repici A, Ramchandani M, Al Khatry M, Kudo SE, Wang P, Yu H, Saito Y, Misawa M, Parasa S, Matsubayashi CO, Ogata H, Tajiri H, Pausawasdi N, Dekker E, Ahmad OF, Sharma P, Rex DK. Benefits and challenges in implementation of artificial intelligence in colonoscopy: World Endoscopy Organization position statement. Dig Endosc. 2023 May;35(4):422-429. doi: 10.1111/den.14531. Epub 2023 Mar 13.