Effect of Endoscopic Mucosal Resection in the Treatment of Colon Polyps and Analysis of Recurrence-related Factors
WANG Qianhui
XU Changlong
LI Faquan
DONG Lin
Abstract：Objective To investigate the effect of endoscopic mucosal resection(EMR)in the treatment of colon pol-yps and to analyze recurrence-related factors.Methods In total,120 patients with colon polyps treated from October 2020 to December 2023 were selected and divided into two groups according to different surgical methods:EMR group(using EMR,n=69)and electrotomy group(using endoscopic high-frequency electrotomy,n=51).The operation-related indexes,clini-cal efficacy,complications and recurrence were compared between the two groups.Univariate analysis and multivariate Logis-tic regression analysis were used to investigate the related factors affecting colon polyp recurrence after EMR.Results The duration of operation,length of hospital stay and time to gastrointestinal function recovery in EMR group were shorter than those in electrotomy group,and the amount of intraoperative blood loss was less than that in electrotomy group(P＜0.01).At two months after operation,the total effective rate in EMR group(67/69,97.10%)was higher than that in electrotomy group(44/51,86.27%)(P＜0.05).The incidence of complications in EMR group(2/69,2.90%)was lower than that in elect-rotomy group(7/51,13.73%)(P＜0.05).At six months after operation,there was no significant difference in recurrence rate between the two groups(P＞0.05).Multivariate logistic regression analysis showed that body mass index and polyp di-ameter were independent risk factors for colon polyp recurrence after EMR(P＜0.01).Conclusion EMR is effective in the treatment of colon polyp,which is conducive to improving operation-related indexes and reducing postoperative complications.BMI and polyp diameter were independent risk factors for colon polyp recurrence after EMR.
Keywords：Endoscopic mucosal resectionEndoscopic high-frequency electrotomyColon polypOperation-related indexesTreatment outcomeRecurrenceComplicationsMultivariate logistic regression analysis
Publication Date：2024-06-15
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 76-80 )