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Construction and validation of a nomogram prediction model for postoperative incisional infection in ankle fractures

The aim was to investigate the independent risk factors for postoperative incisional infection in ankle fractures and to establish a nomogram prediction model accordingly. Data were collected from ankle fracture patients in the Affiliated Hospital of Xinjiang Medical University from January 2018 to...

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Autor principal: Deng, Guang-Hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10695592/
http://dx.doi.org/10.1097/MD.0000000000036408
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author Deng, Guang-Hua
author_facet Deng, Guang-Hua
author_sort Deng, Guang-Hua
collection PubMed
description The aim was to investigate the independent risk factors for postoperative incisional infection in ankle fractures and to establish a nomogram prediction model accordingly. Data were collected from ankle fracture patients in the Affiliated Hospital of Xinjiang Medical University from January 2018 to December 2022. Univariate and multivariate logistic regression analyses were used to determine the independent risk factors for postoperative incisional infection in ankle fractures and to establish the corresponding nomogram. Receiver operating characteristic curves were plotted and area under the curve was calculated, and calibration curves and decision curve analysis were plotted to evaluate the model performance. A total of 722 patients with ankle fractures were included in the study, and 76 patients developed postoperative incisional infections, with an incidence of 10.53%. After univariate and multivariate logistic regression analysis, a total of 5 variables were identified as independent risk factors for postoperative incisional infection in ankle fractures, namely, age ≥ 60 years (OR, 1.885; 95% CI, 1.156–3.045), having diabetes (OR1.625; 95% CI, 1.095–2.876), open fracture (OR, 5.564; 95% CI, 3.099–9.990), albumin < 35 g/L (OR, 2.618; 95% CI, 1.217–4.215), and operative time ≥ 2 hours (OR, 1.606; 95% CI, 1.077–3.247). The nomogram for postoperative incisional infection after ankle fracture constructed in this study has good predictive accuracy and helps orthopedic surgeons to intervene earlier in patients at high risk of postoperative incisional infection after ankle fracture.
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spelling pubmed-106955922023-12-05 Construction and validation of a nomogram prediction model for postoperative incisional infection in ankle fractures Deng, Guang-Hua Medicine (Baltimore) 7100 The aim was to investigate the independent risk factors for postoperative incisional infection in ankle fractures and to establish a nomogram prediction model accordingly. Data were collected from ankle fracture patients in the Affiliated Hospital of Xinjiang Medical University from January 2018 to December 2022. Univariate and multivariate logistic regression analyses were used to determine the independent risk factors for postoperative incisional infection in ankle fractures and to establish the corresponding nomogram. Receiver operating characteristic curves were plotted and area under the curve was calculated, and calibration curves and decision curve analysis were plotted to evaluate the model performance. A total of 722 patients with ankle fractures were included in the study, and 76 patients developed postoperative incisional infections, with an incidence of 10.53%. After univariate and multivariate logistic regression analysis, a total of 5 variables were identified as independent risk factors for postoperative incisional infection in ankle fractures, namely, age ≥ 60 years (OR, 1.885; 95% CI, 1.156–3.045), having diabetes (OR1.625; 95% CI, 1.095–2.876), open fracture (OR, 5.564; 95% CI, 3.099–9.990), albumin < 35 g/L (OR, 2.618; 95% CI, 1.217–4.215), and operative time ≥ 2 hours (OR, 1.606; 95% CI, 1.077–3.247). The nomogram for postoperative incisional infection after ankle fracture constructed in this study has good predictive accuracy and helps orthopedic surgeons to intervene earlier in patients at high risk of postoperative incisional infection after ankle fracture. Lippincott Williams & Wilkins 2023-12-01 /pmc/articles/PMC10695592/ http://dx.doi.org/10.1097/MD.0000000000036408 Text en Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle 7100
Deng, Guang-Hua
Construction and validation of a nomogram prediction model for postoperative incisional infection in ankle fractures
title Construction and validation of a nomogram prediction model for postoperative incisional infection in ankle fractures
title_full Construction and validation of a nomogram prediction model for postoperative incisional infection in ankle fractures
title_fullStr Construction and validation of a nomogram prediction model for postoperative incisional infection in ankle fractures
title_full_unstemmed Construction and validation of a nomogram prediction model for postoperative incisional infection in ankle fractures
title_short Construction and validation of a nomogram prediction model for postoperative incisional infection in ankle fractures
title_sort construction and validation of a nomogram prediction model for postoperative incisional infection in ankle fractures
topic 7100
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10695592/
http://dx.doi.org/10.1097/MD.0000000000036408
work_keys_str_mv AT dengguanghua constructionandvalidationofanomogrampredictionmodelforpostoperativeincisionalinfectioninanklefractures