Artificial Intelligence and Bowel Cleansing Quality (CALPER3)

Strategy for Decreasing Inadequate Bowel Cleansing in Colonoscopy Based on an Artificial Intelligence System: A Randomized and Controlled Study

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.

Study Overview

• Status: Not yet recruiting
• Conditions: Cleansing Quality of the Colon
• Intervention / Treatment: Device: Colon preparation guided by an artificial intelligence 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.

• Study Type: Interventional
• Enrollment (Estimated): 774
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Antonio Z Gimeno Garcia, MD, PhD; Phone Number: 34-922678039; Email: antozeben@gmail.com

Study Locations

• Spain
  • Santa Cruz De Tenerife
    • La Laguna, Santa Cruz De Tenerife, Spain, 38320
      • Hospital Universitario de Canarias
      • Contact: Antonio Z Gimeno, MD, PhD; Phone Number: +34699205181; Email: antozeben@gmail.com

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

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

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Diagnostic
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Colon preparation guided by an artificial intelligence device; Regular oral and written information will be provided to this group. In addition, participants will take a picture of the last rectal effluent with the smart phone that have to upload to a server. A convolutional neural network will assess whether the bowel preparation is correct or not (clean or not). The system will issue specific recommendations based on the quality of cleansing.	Device: Colon preparation guided by an artificial intelligence device; Regular oral and written information will be provided to this group. In addition, participants will take a picture of the last rectal effluent with the smart phone that have to upload to a server. A convolutional neural network will assess whether the bowel preparation is correct or not (clean or not). The system will issue specific recommendations based on the quality of cleansing
Active Comparator: Control group; Regular oral and written information will be provided to this group	Device: Colon preparation guided by an artificial intelligence device; Regular oral and written information will be provided to this group. In addition, participants will take a picture of the last rectal effluent with the smart phone that have to upload to a server. A convolutional neural network will assess whether the bowel preparation is correct or not (clean or not). The system will issue specific recommendations based on the quality of cleansing

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Quality of bowel cleansing assessed by the Boston Bowel Preparation Scale	The Boston Bowel Preparation Scale assesses the quality of bowel cleansing in the three segments of the colon (proximal, transverse, and distal) on a scale of 0 (no preparation) to 3 points (excellent preparation), with a maximum score of 9 points.	3 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Participation rate	Proportion of participants assigned to the intervention group who used the device. It will be assessed by self-reported information from the patients and by the presence of a picture in a server for the storage of images.	3 months

Collaborators and Investigators

• Sponsor: University of La Laguna
• Investigators: Principal Investigator: Antonio Z Gimeno García, MD, PhD, Hospital Universitario de Canarias

Publications and helpful links

General Publications

• 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.
• 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. 2023 Mar 2:S0210-5705(23)00043-2. doi: 10.1016/j.gastrohep.2023.02.009. Online ahead of print. English, Spanish.
• 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.

Study record dates

Study Major Dates

• Study Start (Estimated): November 30, 2023
• Primary Completion (Estimated): September 30, 2024
• Study Completion (Estimated): October 15, 2024

Study Registration Dates

• First Submitted: May 13, 2023
• First Submitted That Met QC Criteria: May 22, 2023
• First Posted (Actual): May 23, 2023

Study Record Updates

• Last Update Posted (Estimated): November 14, 2023
• Last Update Submitted That Met QC Criteria: November 11, 2023
• Last Verified: November 1, 2023

More Information

Terms related to this study

• Other Study ID Numbers: Bowel Cleansing application

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No