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A New Nomogram Based on Early Postoperative NLR for Predicting Infectious Complications After Gastrectomy

PURPOSE: Our study aimed to construct a visible model to evaluate the risk of infectious complications after gastrectomy. METHODS: The clinical data of 856 patients who underwent gastrectomy were used to retrieve medical records. Univariate and multivariate analyses were performed to correlate early...

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Autores principales: Wang, Chen, Huang, Han-zhang, He, Yu, Yu, Yu-jun, Zhou, Qing-miao, Wang, Rong-jian, He, Jian-bo, Han, Shao-liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7012247/
https://www.ncbi.nlm.nih.gov/pubmed/32104070
http://dx.doi.org/10.2147/CMAR.S238530
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author Wang, Chen
Huang, Han-zhang
He, Yu
Yu, Yu-jun
Zhou, Qing-miao
Wang, Rong-jian
He, Jian-bo
Han, Shao-liang
author_facet Wang, Chen
Huang, Han-zhang
He, Yu
Yu, Yu-jun
Zhou, Qing-miao
Wang, Rong-jian
He, Jian-bo
Han, Shao-liang
author_sort Wang, Chen
collection PubMed
description PURPOSE: Our study aimed to construct a visible model to evaluate the risk of infectious complications after gastrectomy. METHODS: The clinical data of 856 patients who underwent gastrectomy were used to retrieve medical records. Univariate and multivariate analyses were performed to correlate early postoperative NLR and operative variables with postoperative complications, and the construction of the nomogram was based on logistic regression. The concordance index and receiver operating characteristic curves were used to evaluate the model performance. RESULTS: The postoperative infectious and noninfectious complication rates after gastrectomy were 18.5% (158/856 cases) and 12.3% (105/856 cases) respectively. Postoperative NLR (within 24 h) independently predicted the development of postoperative infectious complication. Multivariate analysis revealed that age, diabetes, body mass index (BMI), intraoperative blood transfusion and postoperative NLR were independent risk factors. The nomogram model showed a good performance in terms of predicting infectious complications after gastrectomy (concordance index=0.718). CONCLUSION: Age, diabetes, BMI, intraoperative blood transfusion and postoperative NLR were independent risk factors of postoperative infectious complications after gastrectomy, and a novel nomogram based on these results can be used to predict postoperative infection and has the advantages of simple application and easy access.
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spelling pubmed-70122472020-02-26 A New Nomogram Based on Early Postoperative NLR for Predicting Infectious Complications After Gastrectomy Wang, Chen Huang, Han-zhang He, Yu Yu, Yu-jun Zhou, Qing-miao Wang, Rong-jian He, Jian-bo Han, Shao-liang Cancer Manag Res Original Research PURPOSE: Our study aimed to construct a visible model to evaluate the risk of infectious complications after gastrectomy. METHODS: The clinical data of 856 patients who underwent gastrectomy were used to retrieve medical records. Univariate and multivariate analyses were performed to correlate early postoperative NLR and operative variables with postoperative complications, and the construction of the nomogram was based on logistic regression. The concordance index and receiver operating characteristic curves were used to evaluate the model performance. RESULTS: The postoperative infectious and noninfectious complication rates after gastrectomy were 18.5% (158/856 cases) and 12.3% (105/856 cases) respectively. Postoperative NLR (within 24 h) independently predicted the development of postoperative infectious complication. Multivariate analysis revealed that age, diabetes, body mass index (BMI), intraoperative blood transfusion and postoperative NLR were independent risk factors. The nomogram model showed a good performance in terms of predicting infectious complications after gastrectomy (concordance index=0.718). CONCLUSION: Age, diabetes, BMI, intraoperative blood transfusion and postoperative NLR were independent risk factors of postoperative infectious complications after gastrectomy, and a novel nomogram based on these results can be used to predict postoperative infection and has the advantages of simple application and easy access. Dove 2020-02-07 /pmc/articles/PMC7012247/ /pubmed/32104070 http://dx.doi.org/10.2147/CMAR.S238530 Text en © 2020 Wang et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Wang, Chen
Huang, Han-zhang
He, Yu
Yu, Yu-jun
Zhou, Qing-miao
Wang, Rong-jian
He, Jian-bo
Han, Shao-liang
A New Nomogram Based on Early Postoperative NLR for Predicting Infectious Complications After Gastrectomy
title A New Nomogram Based on Early Postoperative NLR for Predicting Infectious Complications After Gastrectomy
title_full A New Nomogram Based on Early Postoperative NLR for Predicting Infectious Complications After Gastrectomy
title_fullStr A New Nomogram Based on Early Postoperative NLR for Predicting Infectious Complications After Gastrectomy
title_full_unstemmed A New Nomogram Based on Early Postoperative NLR for Predicting Infectious Complications After Gastrectomy
title_short A New Nomogram Based on Early Postoperative NLR for Predicting Infectious Complications After Gastrectomy
title_sort new nomogram based on early postoperative nlr for predicting infectious complications after gastrectomy
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7012247/
https://www.ncbi.nlm.nih.gov/pubmed/32104070
http://dx.doi.org/10.2147/CMAR.S238530
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