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Nomogram for predicting chylous ascites after right colectomy

BACKGROUND: Chylous ascites following right colectomy has a high incidence which is a critical challenge. At present, there are few studies on the factors affecting chylous ascites after right colectomy and especially after D3 Lymphadenectomy. A predictive model for chylous ascites has not yet been...

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Autores principales: Zheng, Hui-Da, Liu, Yu-Rong, Chen, Zhen-Ze, Sun, Ya-Feng, Xu, Chun-Hao, Xu, Jian-Hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8649560/
https://www.ncbi.nlm.nih.gov/pubmed/34950426
http://dx.doi.org/10.4240/wjgs.v13.i11.1361
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author Zheng, Hui-Da
Liu, Yu-Rong
Chen, Zhen-Ze
Sun, Ya-Feng
Xu, Chun-Hao
Xu, Jian-Hua
author_facet Zheng, Hui-Da
Liu, Yu-Rong
Chen, Zhen-Ze
Sun, Ya-Feng
Xu, Chun-Hao
Xu, Jian-Hua
author_sort Zheng, Hui-Da
collection PubMed
description BACKGROUND: Chylous ascites following right colectomy has a high incidence which is a critical challenge. At present, there are few studies on the factors affecting chylous ascites after right colectomy and especially after D3 Lymphadenectomy. A predictive model for chylous ascites has not yet been established. Therefore, we created the first nomogram to predict the incidence of chylous ascites after right hemicolectomy. AIM: To analyze the risk factors for chylous ascites after right colectomy and establish a nomogram to predict the incidence of chylous ascites. METHODS: We retrospectively collected patients who underwent right hemicolectomy between January 2012 and May 2021 and were pathologically diagnosed with cancer. Multivariate logistic regression was used to analyze the influencing factors of chylous ascites and a nomogram was established. The predictive ability was assessed by the area under the receiver operating characteristic (ROC) curve. RESULTS: Operative time, the type of operation (standard or extended), the number of lymph nodes retrieved, and somatostatin administration were considered important risk factors. Multivariate logistic regression and nomograms can be used to accurately predict whether chylous ascites occurs. The area under the ROC curve of the model is 0.770. The C-statistic of this model is 0.770 which indicates that it has a relatively moderate ability to predict the risk of chylous ascites. CONCLUSION: We found a novel set of risk factors, created a nomogram, and validated it. The nomogram had a relatively accurate forecasting ability for chylous ascites after right hemicolectomy and can be used as a reference for risk assessment of chylous ascites and whether to prevent it after surgery.
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spelling pubmed-86495602021-12-22 Nomogram for predicting chylous ascites after right colectomy Zheng, Hui-Da Liu, Yu-Rong Chen, Zhen-Ze Sun, Ya-Feng Xu, Chun-Hao Xu, Jian-Hua World J Gastrointest Surg Case Control Study BACKGROUND: Chylous ascites following right colectomy has a high incidence which is a critical challenge. At present, there are few studies on the factors affecting chylous ascites after right colectomy and especially after D3 Lymphadenectomy. A predictive model for chylous ascites has not yet been established. Therefore, we created the first nomogram to predict the incidence of chylous ascites after right hemicolectomy. AIM: To analyze the risk factors for chylous ascites after right colectomy and establish a nomogram to predict the incidence of chylous ascites. METHODS: We retrospectively collected patients who underwent right hemicolectomy between January 2012 and May 2021 and were pathologically diagnosed with cancer. Multivariate logistic regression was used to analyze the influencing factors of chylous ascites and a nomogram was established. The predictive ability was assessed by the area under the receiver operating characteristic (ROC) curve. RESULTS: Operative time, the type of operation (standard or extended), the number of lymph nodes retrieved, and somatostatin administration were considered important risk factors. Multivariate logistic regression and nomograms can be used to accurately predict whether chylous ascites occurs. The area under the ROC curve of the model is 0.770. The C-statistic of this model is 0.770 which indicates that it has a relatively moderate ability to predict the risk of chylous ascites. CONCLUSION: We found a novel set of risk factors, created a nomogram, and validated it. The nomogram had a relatively accurate forecasting ability for chylous ascites after right hemicolectomy and can be used as a reference for risk assessment of chylous ascites and whether to prevent it after surgery. Baishideng Publishing Group Inc 2021-11-27 2021-11-27 /pmc/articles/PMC8649560/ /pubmed/34950426 http://dx.doi.org/10.4240/wjgs.v13.i11.1361 Text en ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
spellingShingle Case Control Study
Zheng, Hui-Da
Liu, Yu-Rong
Chen, Zhen-Ze
Sun, Ya-Feng
Xu, Chun-Hao
Xu, Jian-Hua
Nomogram for predicting chylous ascites after right colectomy
title Nomogram for predicting chylous ascites after right colectomy
title_full Nomogram for predicting chylous ascites after right colectomy
title_fullStr Nomogram for predicting chylous ascites after right colectomy
title_full_unstemmed Nomogram for predicting chylous ascites after right colectomy
title_short Nomogram for predicting chylous ascites after right colectomy
title_sort nomogram for predicting chylous ascites after right colectomy
topic Case Control Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8649560/
https://www.ncbi.nlm.nih.gov/pubmed/34950426
http://dx.doi.org/10.4240/wjgs.v13.i11.1361
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