Artificial Intelligence and Bowel Cleansing Quality

Study Overview
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Brief Summary
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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
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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.

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

Conditions
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Cleansing Quality of the Colon

Intervention / Treatment
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* Device: Colon preparation guided by an artificial intelligence device


Participation Criteria
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Eligibility Criteria
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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

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Diagnostic
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Single


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Colon preparation guided by an artificial intelligence device<br>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<br>* 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<br>|
| Active Comparator: Control group<br>Regular oral and written information will be provided to this group | Device: Colon preparation guided by an artificial intelligence device<br>* 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<br>|

What is the study measuring?
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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 |