Cargando…
Prediction model for anastomotic leakage after laparoscopic rectal cancer resection
OBJECTIVE: This study was performed to identify risk factors for anastomotic leakage (AL) and combine these factors to create a prediction model for the risk of AL after laparoscopic rectal cancer resection. METHODS: This retrospective study involved 185 patients with rectal cancer who underwent lap...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7520932/ https://www.ncbi.nlm.nih.gov/pubmed/32962496 http://dx.doi.org/10.1177/0300060520957547 |
_version_ | 1783587875852386304 |
---|---|
author | Shiwakoti, Enesh Song, Jianning Li, Jun Wu, Shanshan Zhang, Zhongtao |
author_facet | Shiwakoti, Enesh Song, Jianning Li, Jun Wu, Shanshan Zhang, Zhongtao |
author_sort | Shiwakoti, Enesh |
collection | PubMed |
description | OBJECTIVE: This study was performed to identify risk factors for anastomotic leakage (AL) and combine these factors to create a prediction model for the risk of AL after laparoscopic rectal cancer resection. METHODS: This retrospective study involved 185 patients with rectal cancer who underwent laparoscopic resection from March 2012 to February 2017. Five risk factors were analyzed by multivariate analysis. A prediction model was established by combining the risk factors from the multivariate analysis, and the accuracy of the model was evaluated by a receiver operating characteristic curve. RESULTS: The overall AL rate was 17.84%. The multivariate analysis identified the following independent risk factors for AL: high body mass index (odds ratio [OR], 3.009; 95% confidence interval [CI], 1.127–7.125), preoperative radiochemotherapy (OR, 3.778; 95% CI, 1.168–12.219), larger tumor size (OR, 2.710; 95% CI, 1.119–6.562), and longer surgical time (OR, 2.476; 95% CI, 1.033–5.932). We established a prediction model that can evaluate the risk of AL by determining the predictive probability. The area under the curve for the model’s predictive performance was 0.70 (95% CI, 0.598–0.795). CONCLUSION: A prediction model was created to predict the risk of AL after laparoscopic rectal cancer resection. |
format | Online Article Text |
id | pubmed-7520932 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-75209322020-10-06 Prediction model for anastomotic leakage after laparoscopic rectal cancer resection Shiwakoti, Enesh Song, Jianning Li, Jun Wu, Shanshan Zhang, Zhongtao J Int Med Res Retrospective Clinical Research Report OBJECTIVE: This study was performed to identify risk factors for anastomotic leakage (AL) and combine these factors to create a prediction model for the risk of AL after laparoscopic rectal cancer resection. METHODS: This retrospective study involved 185 patients with rectal cancer who underwent laparoscopic resection from March 2012 to February 2017. Five risk factors were analyzed by multivariate analysis. A prediction model was established by combining the risk factors from the multivariate analysis, and the accuracy of the model was evaluated by a receiver operating characteristic curve. RESULTS: The overall AL rate was 17.84%. The multivariate analysis identified the following independent risk factors for AL: high body mass index (odds ratio [OR], 3.009; 95% confidence interval [CI], 1.127–7.125), preoperative radiochemotherapy (OR, 3.778; 95% CI, 1.168–12.219), larger tumor size (OR, 2.710; 95% CI, 1.119–6.562), and longer surgical time (OR, 2.476; 95% CI, 1.033–5.932). We established a prediction model that can evaluate the risk of AL by determining the predictive probability. The area under the curve for the model’s predictive performance was 0.70 (95% CI, 0.598–0.795). CONCLUSION: A prediction model was created to predict the risk of AL after laparoscopic rectal cancer resection. SAGE Publications 2020-09-22 /pmc/articles/PMC7520932/ /pubmed/32962496 http://dx.doi.org/10.1177/0300060520957547 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by-nc/4.0/ Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Retrospective Clinical Research Report Shiwakoti, Enesh Song, Jianning Li, Jun Wu, Shanshan Zhang, Zhongtao Prediction model for anastomotic leakage after laparoscopic rectal cancer resection |
title | Prediction model for anastomotic leakage after laparoscopic rectal cancer resection |
title_full | Prediction model for anastomotic leakage after laparoscopic rectal cancer resection |
title_fullStr | Prediction model for anastomotic leakage after laparoscopic rectal cancer resection |
title_full_unstemmed | Prediction model for anastomotic leakage after laparoscopic rectal cancer resection |
title_short | Prediction model for anastomotic leakage after laparoscopic rectal cancer resection |
title_sort | prediction model for anastomotic leakage after laparoscopic rectal cancer resection |
topic | Retrospective Clinical Research Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7520932/ https://www.ncbi.nlm.nih.gov/pubmed/32962496 http://dx.doi.org/10.1177/0300060520957547 |
work_keys_str_mv | AT shiwakotienesh predictionmodelforanastomoticleakageafterlaparoscopicrectalcancerresection AT songjianning predictionmodelforanastomoticleakageafterlaparoscopicrectalcancerresection AT lijun predictionmodelforanastomoticleakageafterlaparoscopicrectalcancerresection AT wushanshan predictionmodelforanastomoticleakageafterlaparoscopicrectalcancerresection AT zhangzhongtao predictionmodelforanastomoticleakageafterlaparoscopicrectalcancerresection |