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结直肠癌手术中的吻合口漏:肠道微生物群的作用和预测方法。

Anastomotic leak in colorectal cancer surgery: Contribution of gut microbiota and prediction approaches.

机构信息

Servicio de Microbiología, Hospital Universitario Ramón y Cajal, Madrid, Spain.

Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain.

出版信息

Colorectal Dis. 2023 Nov;25(11):2187-2197. doi: 10.1111/codi.16733. Epub 2023 Sep 25.

Abstract

AIM

To monitor prospectively the occurrence of colorectal anastomotic leakage (CAL) in patients with colon cancer undergoing resectional surgery, characterizing the microbiota in both faeces and mucosal biopsies of anastomosis. In a second stage, we investigated the ability to predict CAL using machine learning models based on clinical data and microbiota composition.

METHOD

A total of 111 patients were included, from whom a faecal sample was obtained, as well as biopsy samples from proximal and distal sites in the healthy margins of the tumour piece. The microorganisms present in the samples were investigated using microbial culture and 16S rDNA massive sequencing. Collagenase and protease production was determined, as well as the presence of genes responsible for expressing enzymes with these activities. Machine learning analyses were developed using clinical and microbiological data.

RESULTS

The incidence of CAL was 9.0%, and CAL was associated with collagenase/protease-producing Enterococcus. Significant differences were found in the microbiota composition of proximal and distal biopsy samples, but not in faecal samples, among patients who developed CAL. Clinical predictors of CAL were 5-day C-reactive protein and heart disease, whereas 3-day C-reactive protein and diabetes were negative predictors.

CONCLUSION

Biopsy samples from surgical margins, rather than faecal samples, are the most appropriate samples for exploring the contribution of the intestinal microbiota to CAL. Enterococci are only enriched in the anastomosis after surgery, and their collagenases and proteases are involved in the degradation of the anastomotic scar.

摘要

目的

前瞻性监测行切除术的结肠癌患者的结直肠吻合口漏(CAL)的发生情况,对吻合口粪便和黏膜活检样本中的微生物群进行特征分析。在第二阶段,我们利用基于临床数据和微生物群组成的机器学习模型,调查了预测 CAL 的能力。

方法

共纳入 111 例患者,采集粪便样本,以及肿瘤切缘健康部位近端和远端的活检样本。使用微生物培养和 16S rDNA 大规模测序法检测样本中存在的微生物。测定胶原酶和蛋白酶的产生情况,以及表达具有这些活性的酶的基因的存在情况。使用临床和微生物学数据开发机器学习分析。

结果

CAL 的发生率为 9.0%,CAL 与产生胶原酶/蛋白酶的肠球菌有关。发生 CAL 的患者近端和远端活检样本的微生物群组成存在显著差异,但粪便样本无差异。CAL 的临床预测因子为 5 天 C 反应蛋白和心脏病,而 3 天 C 反应蛋白和糖尿病为负预测因子。

结论

与粪便样本相比,手术切缘的活检样本更适合探索肠道微生物群对 CAL 的贡献。肠球菌仅在手术后的吻合口处富集,其胶原酶和蛋白酶参与了吻合口瘢痕的降解。

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