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

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Hernández González, Patricia I. & Barquín, José & Ortega Ferrete, Ana & Patón, Víctor & Ponce Alonso, Manuel & Romero Hernández, Beatriz & Ocaña, Juan & Caminoa, Alejandra & Conde Moreno, Elisa & Galeano, Javier & del Campo Moreno, Rosa & García Pérez, Juan Carlos .Anastomotic leak in colorectal cancer surgery: Contribution of gut microbiota and prediction approaches.

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Hernández González, Patricia I. & Barquín, José & Ortega Ferrete, Ana & Patón, Víctor & Ponce Alonso, Manuel & Romero Hernández, Beatriz & Ocaña, Juan & Caminoa, Alejandra & Conde Moreno, Elisa & Galeano, Javier & del Campo Moreno, Rosa & García Pérez, Juan Carlos. Anastomotic leak in colorectal cancer surgery: Contribution of gut microbiota and prediction approaches.

https://hdl.handle.net/20.500.12080/44779
dc.contributor.author Hernández González, Patricia I.
dc.contributor.author Barquín, José
dc.contributor.author Ortega Ferrete, Ana
dc.contributor.author Patón, Víctor
dc.contributor.author Ponce Alonso, Manuel
dc.contributor.author Romero Hernández, Beatriz
dc.contributor.author Ocaña, Juan
dc.contributor.author Caminoa, Alejandra
dc.contributor.author Conde Moreno, Elisa
dc.contributor.author Galeano, Javier
dc.contributor.author del Campo Moreno, Rosa
dc.contributor.author García Pérez, Juan Carlos
dc.date.accessioned 2024-11-15T16:05:49Z
dc.date.available 2024-11-15T16:05:49Z
dc.date.created 2023
dc.identifier.uri https://hdl.handle.net/20.500.12080/44779
dc.description.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 mi crobiota 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 tu mour 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 microbio logical 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 pa tients 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 colla genases and proteases are involved in the degradation of the anastomotic scar. KEYWORDS anastomotic leakage, collagenase, colorectal cancer, Enterococcus, gut microbiot es_ES
dc.format application/pdf es_ES
dc.language eng es_ES
dc.rights CC-BY es_ES
dc.rights.uri http://creativecommons.org/licenses/by/4.0/deed.es es_ES
dc.subject anastomotic leakage, collagenase, colorectal cancer, Enterococcus, gut microbiot es_ES
dc.title Anastomotic leak in colorectal cancer surgery: Contribution of gut microbiota and prediction approaches es_ES
dc.type info:eu-repo/semantics/article es_ES
dc.rights.accessrights info:eu-repo/semantics/openAccess es_ES
dc.identifier.location N/A es_ES


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