Correlation Engine 2.0
Clear Search sequence regions


  • adenoma (19)
  • ADR 1 (1)
  • humans (1)
  • meta analysis (3)
  • odds ratios (1)
  • Sizes of these terms reflect their relevance to your search.

    A network meta-analysis showed that low-cost optimization of existing resources was as effective as distal add-on devices in increasing adenoma detection rate (ADR). We assessed the impacts of water exchange (WE), Endocuff, and cap colonoscopy on ADR and advanced adenoma detection rate (AADR). We hypothesized that WE may be superior at improving ADR and AADR. The literature was searched for all randomized controlled trials (RCTs) that reported ADR as an outcome and included the keywords colonoscopy, and water exchange, Endocuff, or cap. We performed traditional network meta-analyses with random effect models comparing ADR and AADR of each method using air insufflation (AI) as the control and reported the odds ratios with 95% confidence interval. Performances were ranked based on P-score. Twenty-one RCTs met inclusion criteria. Fourteen RCTs also reported AADR. Both WE [1.46 (1.20-1.76)] and Endocuff [1.39 (1.17-1.66)] significantly increase ADR, while cap has no impact on ADR [1.00 (0.82-1.22)]. P-scores for WE (0.88), Endocuff (0.79), cap (0.17), and AI (0.17) suggest WE has the highest ADR. WE [1.38 (1.12-1.70)], but not Endocuff [0.96 (0.76-1.21)] or cap [1.06 (0.85-1.32)], significantly increases AADR. P-scores for WE (0.98), cap (0.50), AI (0.31), and Endocuff (0.21) suggest WE is more effective at increasing AADR. The results did not change after adjusting for age, proportion of males, and withdrawal time. WE may be the modality of choice to maximally improve ADR and AADR.

    Citation

    Paul P Shao, Aileen Bui, Tahmineh Romero, Hui Jia, Felix W Leung. Adenoma and Advanced Adenoma Detection Rates of Water Exchange, Endocuff, and Cap Colonoscopy: A Network Meta-Analysis with Pooled Data of Randomized Controlled Trials. Digestive diseases and sciences. 2021 Apr;66(4):1175-1188

    Expand section icon Mesh Tags

    Expand section icon Substances


    PMID: 32451757

    View Full Text