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Effect of Preoperative Automatic Reminder System on Colonoscopy

W

Wuhan University

Status

Unknown

Conditions

Colonoscopy

Treatments

Device: AI based preoperative automatic reminder system

Study type

Interventional

Funder types

Other

Identifiers

NCT04996888
EA-21-007

Details and patient eligibility

About

In this study, the investigators proposed an artificial intelligence-based preoperative automatic reminder system on colonocopy, which can improve the quality of bowel preparation and the rate of polyps and adenomas detection.

Full description

Despite advances in bowel preparation methods, bowel preparation is inadequate in up to one-third of all colonoscopies in reported series. Inadequate bowel cleansing results in negative con-sequences for the examination, including incomplete visualization of the colon, missed lesions(22-48%), procedural difficulties, prolonged procedure time and reduced time interval until follow-up, and an estimated 12-22% increase in overall colonoscopy cost.

The adequacy of a bowel preparation is closely linked to patient compliance with both dietary and purge instructions. Previous work has shown that 18-23.5% of the patients with poor preparation had failed to follow preparation instructions. One study performed in Asia showed that non-compliance with bowel preparation instructions, lower education level, and a long wait for the colonoscopy appointment were independent risk factors for poor bowel preparation. A survey among doctors showed that gastroenterologists with the highest number of patients with inadequate bowel preparation believed that patients are unwilling to follow preparation instructions, struggle with the prescribed diet, and are unable to tolerate the full course of purgative. It is reasonable to hypothesis that efforts to improve education and maximize patient compliance during the preparatory period will enhance the efficacy of bowel preparation.

A research has shown that telephone-based re-education about the details of bowel preparation on the day before colonoscopy significantly improved the quality of bowel preparation and polys detection rate. In recent years, artificial intelligence (AI) has been successfully applied in multiple medical fields. But there has not been an artificial-intelligence-based system which can automatically remind patients of the details of bowel preparation on the day before colonoscopy.

In this study, we proposed an artificial intelligence-based preoperative automatic reminder system on colonoscopy, which can improve the quality of bowel preparation and the rate of polyps and adenomas detection.

Enrollment

829 estimated patients

Sex

All

Ages

50 to 75 years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  1. Male or female between 50-75 years old;
  2. Able to read, understand and sign informed consent
  3. The investigator believes that the subjects can understand the process of the clinical study, are willing and able to complete all study procedures and follow-up visits, and cooperate with the study procedures
  4. Outpatients requiring colonoscopy

Exclusion criteria

  1. colorectal surgical history
  2. Severe colonic stricture or obstructive tumor
  3. Obvious gastroparesis or gastric outlet obstruction or intestinal infarction
  4. Pregnant or lactating women
  5. Dysphagia or impaired swallowing reflex or mental state
  6. Intestinal obstruction or perforation is known
  7. Severe chronic renal failure(CCR< 30ml/min)
  8. Severe congestive heart failure(NYHA ⅢorⅣ)
  9. Uncontrolled hypertension( systolic pressure>170mmHg,diastolic pressure>100mmHg)
  10. Dehydration or electrolyte disorder
  11. Toxic colitis or megacolon
  12. Inable to give informed consent
  13. Hemodynamic instability

Trial design

Primary purpose

Screening

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

Double Blind

829 participants in 2 patient groups

with AI preoperative automatic reminder system
Experimental group
Description:
After receiving regular instructions at the time of their appointment to discuss colonoscopy and education about colonoscopy provided by one nurse, including the importance of bowel preparation, the side effects of the agents used, and the exact preparation instructions, the patients in the experimental group will be sent a message and a phone call by AI system on the day before colonoscopy, which will emphasize the importance of bowel preparation, the directions for use and side effects of purgatives, the proper food type, and the start time.
Treatment:
Device: AI based preoperative automatic reminder system
without AI preoperative automatic reminder system
No Intervention group
Description:
The patients in the control group accept colonoscopy routinely without AI based preoperative automatic reminder system. All patients will receive regular instructions at the time of their appointment to discuss colonoscopy and education about colonoscopy provided by one nurse, including the importance of bowel preparation, the side effects of the agents used, and the exact preparation instructions.

Trial contacts and locations

1

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Central trial contact

Honggang Yu, Doctor

Data sourced from clinicaltrials.gov

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