Clinical Research Directory

Comparison of Adenoma Detection Rate in 3D vs. 2D Surveillance Colonoscopy

There is substantial evidence confirming that identifying and removing colorectal adenomas during colonoscopy helps prevent the development of colorectal cancer. Among the quality indicators for colonoscopy, adenoma detection rate (ADR) is the most important, as it is closely related to the patient's future risk of colorectal cancer. Recent studies have further demonstrated that improving ADR can reduce future mortality from colorectal cancer. Notably, non-polypoid lesions (such as flat or depressed lesions) are more likely to be missed during traditional colonoscopy, making these lesions a leading cause of post-colonoscopy interval colorectal cancer. In a prospective trial conducted by our team comparing the ADR of 3D colonoscopy with standard 2D colonoscopy, we found that 3D colonoscopy significantly improved overall ADR and the detection rate of non-polypoid adenomas. According to current international guidelines, after an index colonoscopy, patients are recommended to undergo surveillance colonoscopy 1 to 10 years later, depending on their findings at index colonoscopy. Since these patients represent the majority in clinical practice, increasing the ADR during surveillance colonoscopy not only allows for more precise recommendations for the timing of the next colonoscopy but also effectively reduces the risk of post-colonoscopy colorectal cancer (PCCRC). Therefore, this multicenter, prospective, randomized trial aims to compare the clinical performance of 3D colonoscopy and standard 2D colonoscopy in the context of surveillance colonoscopy.

Artificial Intelligence (AI) Technology May Help Patients to Understand Bowel Preparation Better Before They go for Colonoscopy.This Study Attempts to Leverage AI Chatbot in Counselling Patients to Improve Bowel Cleanliness, Reduce Anxiety as Well as Increase Procedural Satisfaction

Traditional pre-colonoscopy counselling requires significant time from healthcare workers to explain procedures, limiting efficiency and patient turnover. Inadequate bowel preparation exacerbates this issue, leading to repeat procedures and increased costs. However, no study has yet evaluated the effectiveness of AI in improving the Boston Bowel Preparation Scale (BBPS) for colonoscopy preparation. By addressing this gap, AI chatbots could provide personalized guidance, reduce healthcare worker burden, improve preparation quality, and enhance patient experience.This research attempts to evaluate the effectiveness of using Artificial intelligence (AI) chat bot to improve bowel preparation, anxiety level and patient's satisfaction among colonoscopy patients in Hospital Tuanku Muhriz (HCTM), compared to conventional instructions