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Patient-Level Predictors of Procedural Success in Colon Capsule Endoscopy: A Systematic Review and Meta-Analysis
Ian Io Lei1,2,3, Prashanth Vuggumudi3, Kiara Mcdonnell3
1Institute of Precision Diagnostics & Translational Medicine, University Hospital of Coventry and Warwickshire, Coventry, UK.
Background:
Colon capsule endoscopy (CCE) is an increasingly used noninvasive alternative to colonoscopy for colonic investigation. However, its widespread adoption is constrained by suboptimal completion rates (CR), inadequate bowel preparation, and a high follow-up endoscopy rate (FER), collectively undermining cost-effectiveness and service efficiency. Evidence on patient-level predictors of these outcomes remains fragmented.
Methods:
A systematic review and meta-analysis were conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. MEDLINE, Embase, CENTRAL, and PubMed Central were searched. Patient-level factors associated with completion rate, bowel preparation adequacy, successful CCE, and FER were extracted. Random-effects meta-analyses were performed to pool unadjusted and adjusted odds ratios.
Results:
Ten studies comprising 4374 participants met inclusion criteria. The pooled completion rate was 73% (95% CI 68%-78%), and pooled bowel preparation adequacy was 72% (95% CI 60%-81%). Chronic opioid use was consistently associated with reduced performance, demonstrating lower completion rates (unadjusted OR 0.54, 95% CI 0.40-0.73; adjusted OR 0.55, 95% CI 0.28-1.09) and poorer bowel preparation adequacy (adjusted OR 0.49, 95% CI 0.26-0.96). Diabetes was independently associated with inadequate bowel preparation (adjusted OR 0.40, 95% CI 0.36-0.45). Increasing age showed borderline statistical significance but minimal clinical impact. The pooled follow-up endoscopy rate was 61% (95% CI 56%-67%).
Conclusion:
CCE performance is strongly influenced by patient-level factors, particularly chronic opioid use and diabetes. Targeted patient selection is the most immediately actionable strategy to improve efficiency, whereas individual participant data meta-analyses are needed to enable robust risk stratification of CCE.
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