Rex, Douglas K.

Abstract Artificial intelligence (AI) and mucosal exposure devices like Endocuff have independently improved the adenoma detection rate (ADR) during colonoscopy. This meta-analysis evaluated the combined effect of Endocuff and AI versus AI alone on colorectal neoplasia detection rates. We searched PubMed, Embase, and Web of Science for randomized controlled trials (RCTs) comparing the impact of Endocuff+AI versus AI alone on colorectal neoplasia detection. Primary outcome was ADR; secondary outcomes included advanced adenoma detection rate (AADR), sessile serrated lesion detection rate (SSLDR), cecal intubation time, and withdrawal time. Pooled risk ratios (RRs) and mean differences (MDs) with 95% confidence intervals (CIs) were calculated using a random-effects model. Three RCTs with 2404 subjects were included (n = 1198 Endocuff+AI vs. n = 1206 AI alone). ADR was significantly higher in the Endocuff+AI group than in the AI alone group (54% vs. 48%, respectively) (RR 1.12, 95% CI 1.03–1.21, P = 0.01, I2 = 0%). There was a trend toward higher AADR (12.3% vs. 10%, RR 1.23, 95% CI 0.96–1.59, P = 0.10, I2 = 17%) and SSLDR (17.6% vs. 15.5%, RR 1.16, 95% CI 0.96–1.40, P = 0.13, I2 = 0%) in the Endocuff+AI group compared with the AI alone group, but it did not reach statistical significance. Both cecal intubation time (MD -0.61 minutes; 95% CI -1.54–0.33; P = 0.20; I2 = 87%) and withdrawal time (MD -0.42 minutes; 95% CI -1.01–0.17; P = 0.17, I2 = 60%) were similar between the two groups. Endocuff combined with AI was superior to AI alone in improving the adenoma detection rate without increasing intubation or withdrawal times.

INTRODUCTION: Inadequate bowel preparation (IBP) before colonoscopy remains a common problem. This meta-analysis aimed to assess the risk factors associated with IBP. METHODS: We searched multiple databases for studies that assessed risk factors for IBP after adjustment and reported the data as adjusted odds ratios with 95% confidence intervals. Meta-analyses were conducted using a random-effects model, and pooled adjusted odds ratios for risk factors reported in ≥ 3 studies were constructed. RESULTS: One hundred fifty-four studies with 358,257 participants were included. We analyzed 48 unique risk factors. Sociodemographic predictors of IBP were Medicaid insurance, obesity, current tobacco use, age ≥ 65 years, Black race, low education level, male sex, and unmarried status. Comorbidity-related predictors of IBP were any psychiatric disease, cirrhosis, American Society of Anesthesiologists (ASA) class ≥ 3, poor functional status, constipation, diabetes, previous abdominopelvic surgery, and hematochezia. Medication-related predictors of IBP were tricyclic antidepressants, antidepressants, opioids, nontricyclic antidepressants, and calcium channel blockers. Preparation/procedure-related predictors of IBP were brown liquid rectal effluent, any incomplete bowel preparation (BP) intake, lack of split-dose BP, increased BP-to-defecation interval, any nonadherence to dietary instructions, increased BP-to-colonoscopy interval, any BP intolerance, previous IBP, and inpatient status. Although afternoon colonoscopy was a predictor of IBP, subgroup analysis of prospective studies revealed no significant association. DISCUSSION: Our meta-analysis focused on adjusted risk factors to provide precise estimates of the most important risk factors for IBP. Our findings could help develop a validated prediction model to identify high-risk patients for IBP, improve colonoscopy outcomes, reduce the need for repeat colonoscopies, and reduce associated healthcare costs.