Skip to main content
OpenTrials
Completed

NCT Number: NCT05871814

Artificial Intelligence and Bowel Cleansing Quality

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.

Completed

Looking for future studies?

Notify Me

Key information

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Hospital Universitario de Canarias

San Cristóbal de La Laguna, Santa Cruz de Tenerife, 38320, Spain

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

Colon preparation guided by an artificial intelligence device

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

Primary outcomes

  1. Quality of bowel cleansing assessed by the Boston Bowel Preparation Scale

    Time frame: 3 months

    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.

Secondary outcomes

  1. Participation rate

    Time frame: 3 months

    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.

Sponsors and collaborators

Lead sponsor

University of La Laguna

Other

Registry information

Official study title

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

Acronym: CALPER3

Important dates

Study start
2023
Primary completion
2024
Study completion
2024
First posted
May 23, 2023
Registry last updated
Jun 4, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.