Bowel Preparation for Colonoscopy, Colonoscopy
Conditions
Keywords
Bowel preparation, Colonoscopy, Artificial intelligence
Brief summary
The quality of bowel preparation hinges on how well patients follow the prep-drug regimen, so intensive education is essential. Phone calls, texts, short videos, and mini-programs have all been shown to boost compliance and improve prep quality. Still, we also need a way to spot-early-those patients who are likely to prep poorly so we can step in with a rescue plan. In our pilot work the investigators built an AI-assisted mini-program that lets patients photograph their effluent and get an instant quality read-out. The single-center RCT showed excellent performance. Because these findings came from one center, the investigators are now launching a multicenter study to test the tool more broadly. Patients will use the AI mini-program at home; if the algorithm predicts inadequate prep it will prompt them to come in early or alert staff so the investigators can initiate a rescue protocol and, ultimately, improve bowel-cleansing quality.
Interventions
OTHERThe app group
After taking the bowel-prep solution, patients in the app group are instructed to photograph their final stool in the toilet and upload the image through our smartphone app. The AI algorithm immediately scores the prep quality. If the image is rated "poor" or "inadequate," the app displays an alert advising the patient to come to the hospital early or contact clinical staff; clinical staffs then review the photo and decide whether a rescue preparation is needed. The standard rescue was an additional packet of polyethylene glycol. If the image is rated "adequate," the patient is told the prep is acceptable and should proceed to the appointment, where clinical staffs will use the uploaded photo to confirm eligibility for colonoscopy.
Sponsors
Sixth Affiliated Hospital, Sun Yat-sen University
Tianjin Haihe Hospital
Guangdong Second Provincial General Hospital
Dongguan Humen Hospital of Traditional Chinese Medicine
Cangzhou Central Hospital
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
OTHER
Masking
SINGLE (Outcomes Assessor)
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
1. Age ≥ 18 years 2. Undergoing colonoscopy at a participating site 3. Able to defecate in a toilet (or in a setting where stool characteristics can be observed) after taking the bowel-prep solution 4. Proficient in using a smartphone 5. Willing to participate voluntarily
Exclusion criteria
* American Society of Anesthesiologists (ASA) class III or IV; * Gastric-outlet or intestinal obstruction; ③ Active gastrointestinal bleeding; ④ Enterostomy (colostomy/ileostomy); ⑤ Status post total colectomy.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Compare the bowel preparation quality between the app group and the control group. | Periprocedural | The rate of adequate and excellent bowel preparation. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Evaluate the diagnostic performance of the app-based assessment. | Periprocedural | Sensitivity, specificity, negative predictive value, positive predictive value |
| cecal intubation rate | Periprocedural | — |
| cecal intubation time | Periprocedural | — |
| withdrawal time (excluding polypectomy and biopsy) | Periprocedural | — |
| polyp-detection rate (PDR), adenoma-detection rate (ADR), advanced-adenoma-detection rate (aADR) | Periprocedural | — |
| rate of rescue preparation due to inadequate preparation | Periprocedural | — |
| clinical staffs' assessment time | Periprocedural | — |
| User satisfaction score | Periprocedural | From 0 to 10, 0 stands for the least satisfaction, and 10 stands for the most satisfaction. |
| post-procedural adverse events | From enrollment to 30 days after the procedure. | — |
| rate of rescheduled examinations due to inadequate preparation | Periprocedural | — |
Outcome results
None listed