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Nomogram model to predict postoperative infection after mandibular osteoradionecrosis surgery

Osteoradionecrosis of the mandible (ORNM) is one of the most dreaded complications of radiotherapy. The poor healing capacity of soft tissue after radiation may lead to surgical failure. The current study was designed to identify prognostic factors for postoperative infection (PPI) and propose corre...

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Autores principales: Liu, Zhonglong, Dai, Tianguo, Wang, Zhonghe, Zhang, Zhiyuan, Qiu, Weiliu, He, Yue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5471205/
https://www.ncbi.nlm.nih.gov/pubmed/28615689
http://dx.doi.org/10.1038/s41598-017-03672-2
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author Liu, Zhonglong
Dai, Tianguo
Wang, Zhonghe
Zhang, Zhiyuan
Qiu, Weiliu
He, Yue
author_facet Liu, Zhonglong
Dai, Tianguo
Wang, Zhonghe
Zhang, Zhiyuan
Qiu, Weiliu
He, Yue
author_sort Liu, Zhonglong
collection PubMed
description Osteoradionecrosis of the mandible (ORNM) is one of the most dreaded complications of radiotherapy. The poor healing capacity of soft tissue after radiation may lead to surgical failure. The current study was designed to identify prognostic factors for postoperative infection (PPI) and propose corresponding prophylaxis and intervention protocols. A retrospective study was conducted concerning ORNM patients from 2000 to 2015. A risk-stratification score and nomogram model were established to predict the risk of PPI. A total of 257 patients were analyzed, and the total incidence of PPI was 23.3% (60/257). In multiple logistic regression analysis, radiation dose [Formula: see text] 80 Gy (versus <80 Gy, OR = 2.044, P = 0.035, 95% CI: 1.05–3.979), bilateral ORNM (versus unilateral, OR = 4.120, P = 0.006, 95% CI: 1.501–11.307), skin fistula (versus none, OR = 3.078, P = 0.040, 95% CI: 1.05–9.023), and implant utilization (versus none, OR = 2.115, P = 0.020, 95% CI: 1.125–3.976) were significantly associated with PPI. The susceptibility to PPI in patients with risk-stratification scores of 14–22 was 2.833 times that of patients with scores of 7–13, and 7.585 times that of cases defined as scores of 0–6. The discrimination capability of the nomogram model was estimated using a ROC curve with an AUC of 0.708, revealing potentially useful predictive abilities. In conclusion, current risk-stratification scores and nomogram models effectively predicted the risk of PPI in ORNM patients.
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spelling pubmed-54712052017-06-19 Nomogram model to predict postoperative infection after mandibular osteoradionecrosis surgery Liu, Zhonglong Dai, Tianguo Wang, Zhonghe Zhang, Zhiyuan Qiu, Weiliu He, Yue Sci Rep Article Osteoradionecrosis of the mandible (ORNM) is one of the most dreaded complications of radiotherapy. The poor healing capacity of soft tissue after radiation may lead to surgical failure. The current study was designed to identify prognostic factors for postoperative infection (PPI) and propose corresponding prophylaxis and intervention protocols. A retrospective study was conducted concerning ORNM patients from 2000 to 2015. A risk-stratification score and nomogram model were established to predict the risk of PPI. A total of 257 patients were analyzed, and the total incidence of PPI was 23.3% (60/257). In multiple logistic regression analysis, radiation dose [Formula: see text] 80 Gy (versus <80 Gy, OR = 2.044, P = 0.035, 95% CI: 1.05–3.979), bilateral ORNM (versus unilateral, OR = 4.120, P = 0.006, 95% CI: 1.501–11.307), skin fistula (versus none, OR = 3.078, P = 0.040, 95% CI: 1.05–9.023), and implant utilization (versus none, OR = 2.115, P = 0.020, 95% CI: 1.125–3.976) were significantly associated with PPI. The susceptibility to PPI in patients with risk-stratification scores of 14–22 was 2.833 times that of patients with scores of 7–13, and 7.585 times that of cases defined as scores of 0–6. The discrimination capability of the nomogram model was estimated using a ROC curve with an AUC of 0.708, revealing potentially useful predictive abilities. In conclusion, current risk-stratification scores and nomogram models effectively predicted the risk of PPI in ORNM patients. Nature Publishing Group UK 2017-06-14 /pmc/articles/PMC5471205/ /pubmed/28615689 http://dx.doi.org/10.1038/s41598-017-03672-2 Text en © The Author(s) 2017 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Liu, Zhonglong
Dai, Tianguo
Wang, Zhonghe
Zhang, Zhiyuan
Qiu, Weiliu
He, Yue
Nomogram model to predict postoperative infection after mandibular osteoradionecrosis surgery
title Nomogram model to predict postoperative infection after mandibular osteoradionecrosis surgery
title_full Nomogram model to predict postoperative infection after mandibular osteoradionecrosis surgery
title_fullStr Nomogram model to predict postoperative infection after mandibular osteoradionecrosis surgery
title_full_unstemmed Nomogram model to predict postoperative infection after mandibular osteoradionecrosis surgery
title_short Nomogram model to predict postoperative infection after mandibular osteoradionecrosis surgery
title_sort nomogram model to predict postoperative infection after mandibular osteoradionecrosis surgery
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5471205/
https://www.ncbi.nlm.nih.gov/pubmed/28615689
http://dx.doi.org/10.1038/s41598-017-03672-2
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