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Risk factors and nomogram predictive model of surgical site infection in closed pilon fractures

OBJECTIVES: In this study, we try to investigate the risk factors of postoperative surgical site infection (SSI) in closed pilon fractures and establish a nomogram prediction model. METHODS: From January 2012 to June 2021, 516 closed pilon fracture patients were included in this study. Of these, 387...

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Autores principales: Ke, Chenrong, Dong, Xiaoyu, Xiang, Guangheng, Zhu, Juanjuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10408134/
https://www.ncbi.nlm.nih.gov/pubmed/37553679
http://dx.doi.org/10.1186/s13018-023-04058-z
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author Ke, Chenrong
Dong, Xiaoyu
Xiang, Guangheng
Zhu, Juanjuan
author_facet Ke, Chenrong
Dong, Xiaoyu
Xiang, Guangheng
Zhu, Juanjuan
author_sort Ke, Chenrong
collection PubMed
description OBJECTIVES: In this study, we try to investigate the risk factors of postoperative surgical site infection (SSI) in closed pilon fractures and establish a nomogram prediction model. METHODS: From January 2012 to June 2021, 516 closed pilon fracture patients were included in this study. Of these, 387 patients were randomly assigned to the training group and 129 patients were assigned to the validation group (3:1). By univariate and multivariate Cox analysis, we identified independent risk factors for postoperative SSI after Pilon fracture. We established a nomogram model and used receiver operating characteristic (ROC) and calibration chart to evaluate its discriminant and calibration. RESULTS: SSI occurred in 71 patients in the training group and 23 patients in the validation group. Ultimately, age, preoperative blood sugar, operative time, Tscherne classification and fracture classification were identified as independent risk factors for SSI. The AUC values for SSI of the training and validation group were 0.898 and 0.880, and the P value of the Hosmer–Lemeshow test was 0.125. We established a nomogram prediction model based on age, preoperative blood sugar, operative time, Tscherne classification and fracture classification. CONCLUSION: Our nomogram model had good discrimination and calibration power, so it could be used to predict SSI risk in patients with pilon fracture.
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spelling pubmed-104081342023-08-09 Risk factors and nomogram predictive model of surgical site infection in closed pilon fractures Ke, Chenrong Dong, Xiaoyu Xiang, Guangheng Zhu, Juanjuan J Orthop Surg Res Research Article OBJECTIVES: In this study, we try to investigate the risk factors of postoperative surgical site infection (SSI) in closed pilon fractures and establish a nomogram prediction model. METHODS: From January 2012 to June 2021, 516 closed pilon fracture patients were included in this study. Of these, 387 patients were randomly assigned to the training group and 129 patients were assigned to the validation group (3:1). By univariate and multivariate Cox analysis, we identified independent risk factors for postoperative SSI after Pilon fracture. We established a nomogram model and used receiver operating characteristic (ROC) and calibration chart to evaluate its discriminant and calibration. RESULTS: SSI occurred in 71 patients in the training group and 23 patients in the validation group. Ultimately, age, preoperative blood sugar, operative time, Tscherne classification and fracture classification were identified as independent risk factors for SSI. The AUC values for SSI of the training and validation group were 0.898 and 0.880, and the P value of the Hosmer–Lemeshow test was 0.125. We established a nomogram prediction model based on age, preoperative blood sugar, operative time, Tscherne classification and fracture classification. CONCLUSION: Our nomogram model had good discrimination and calibration power, so it could be used to predict SSI risk in patients with pilon fracture. BioMed Central 2023-08-08 /pmc/articles/PMC10408134/ /pubmed/37553679 http://dx.doi.org/10.1186/s13018-023-04058-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Ke, Chenrong
Dong, Xiaoyu
Xiang, Guangheng
Zhu, Juanjuan
Risk factors and nomogram predictive model of surgical site infection in closed pilon fractures
title Risk factors and nomogram predictive model of surgical site infection in closed pilon fractures
title_full Risk factors and nomogram predictive model of surgical site infection in closed pilon fractures
title_fullStr Risk factors and nomogram predictive model of surgical site infection in closed pilon fractures
title_full_unstemmed Risk factors and nomogram predictive model of surgical site infection in closed pilon fractures
title_short Risk factors and nomogram predictive model of surgical site infection in closed pilon fractures
title_sort risk factors and nomogram predictive model of surgical site infection in closed pilon fractures
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10408134/
https://www.ncbi.nlm.nih.gov/pubmed/37553679
http://dx.doi.org/10.1186/s13018-023-04058-z
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