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Development and Validation of a Stratification Tool for Predicting Risk of Deep Sternal Wound Infection after Coronary Artery Bypass Grafting at a Brazilian Hospital

OBJECTIVE: Deep sternal wound infection following coronary artery bypass grafting is a serious complication associated with significant morbidity and mortality. Despite the substantial impact of deep sternal wound infection, there is a lack of specific risk stratification tools to predict this compl...

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Autores principales: Sá, Michel Pompeu Barros Oliveira, Ferraz, Paulo Ernando, Soares, Artur Freire, Miranda, Rodrigo Gusmão Albuquerque, Araújo, Mayara Lopes, Silva, Frederico Vasconcelos, Lima, Ricardo de Carvalho
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Sociedade Brasileira de Cirurgia Cardiovascular 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5382897/
https://www.ncbi.nlm.nih.gov/pubmed/28423122
http://dx.doi.org/10.21470/1678-9741-2016-0030
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author Sá, Michel Pompeu Barros Oliveira
Ferraz, Paulo Ernando
Soares, Artur Freire
Miranda, Rodrigo Gusmão Albuquerque
Araújo, Mayara Lopes
Silva, Frederico Vasconcelos
Lima, Ricardo de Carvalho
author_facet Sá, Michel Pompeu Barros Oliveira
Ferraz, Paulo Ernando
Soares, Artur Freire
Miranda, Rodrigo Gusmão Albuquerque
Araújo, Mayara Lopes
Silva, Frederico Vasconcelos
Lima, Ricardo de Carvalho
author_sort Sá, Michel Pompeu Barros Oliveira
collection PubMed
description OBJECTIVE: Deep sternal wound infection following coronary artery bypass grafting is a serious complication associated with significant morbidity and mortality. Despite the substantial impact of deep sternal wound infection, there is a lack of specific risk stratification tools to predict this complication after coronary artery bypass grafting. This study was undertaken to develop a specific prognostic scoring system for the development of deep sternal wound infection that could risk-stratify patients undergoing coronary artery bypass grafting and be applied right after the surgical procedure. METHODS: Between March 2007 and August 2016, continuous, prospective surveillance data on deep sternal wound infection and a set of 27 variables of 1500 patients were collected. Using binary logistic regression analysis, we identified independent predictors of deep sternal wound infection. Initially we developed a predictive model in a subset of 500 patients. Dataset was expanded to other 1000 consecutive cases and a final model and risk score were derived. Calibration of the scores was performed using the Hosmer-Lemeshow test. RESULTS: The model had area under Receiver Operating Characteristic (ROC) curve of 0.729 (0.821 for preliminary dataset). Baseline risk score incorporated independent predictors of deep sternal wound infection: obesity (P=0.046; OR 2.58; 95% CI 1.11-6.68), diabetes (P=0.046; OR 2.61; 95% CI 1.12-6.63), smoking (P=0.008; OR 2.10; 95% CI 1.12-4.67), pedicled internal thoracic artery (P=0.012; OR 5.11; 95% CI 1.42-18.40), and on-pump coronary artery bypass grafting (P=0.042; OR 2.20; 95% CI 1.13-5.81). A risk stratification system was, then, developed. CONCLUSION: This tool effectively predicts deep sternal wound infection risk at our center and may help with risk stratification in relation to public reporting and targeted prevention strategies in patients undergoing coronary artery bypass grafting.
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spelling pubmed-53828972017-04-11 Development and Validation of a Stratification Tool for Predicting Risk of Deep Sternal Wound Infection after Coronary Artery Bypass Grafting at a Brazilian Hospital Sá, Michel Pompeu Barros Oliveira Ferraz, Paulo Ernando Soares, Artur Freire Miranda, Rodrigo Gusmão Albuquerque Araújo, Mayara Lopes Silva, Frederico Vasconcelos Lima, Ricardo de Carvalho Braz J Cardiovasc Surg Original Articles OBJECTIVE: Deep sternal wound infection following coronary artery bypass grafting is a serious complication associated with significant morbidity and mortality. Despite the substantial impact of deep sternal wound infection, there is a lack of specific risk stratification tools to predict this complication after coronary artery bypass grafting. This study was undertaken to develop a specific prognostic scoring system for the development of deep sternal wound infection that could risk-stratify patients undergoing coronary artery bypass grafting and be applied right after the surgical procedure. METHODS: Between March 2007 and August 2016, continuous, prospective surveillance data on deep sternal wound infection and a set of 27 variables of 1500 patients were collected. Using binary logistic regression analysis, we identified independent predictors of deep sternal wound infection. Initially we developed a predictive model in a subset of 500 patients. Dataset was expanded to other 1000 consecutive cases and a final model and risk score were derived. Calibration of the scores was performed using the Hosmer-Lemeshow test. RESULTS: The model had area under Receiver Operating Characteristic (ROC) curve of 0.729 (0.821 for preliminary dataset). Baseline risk score incorporated independent predictors of deep sternal wound infection: obesity (P=0.046; OR 2.58; 95% CI 1.11-6.68), diabetes (P=0.046; OR 2.61; 95% CI 1.12-6.63), smoking (P=0.008; OR 2.10; 95% CI 1.12-4.67), pedicled internal thoracic artery (P=0.012; OR 5.11; 95% CI 1.42-18.40), and on-pump coronary artery bypass grafting (P=0.042; OR 2.20; 95% CI 1.13-5.81). A risk stratification system was, then, developed. CONCLUSION: This tool effectively predicts deep sternal wound infection risk at our center and may help with risk stratification in relation to public reporting and targeted prevention strategies in patients undergoing coronary artery bypass grafting. Sociedade Brasileira de Cirurgia Cardiovascular 2017 /pmc/articles/PMC5382897/ /pubmed/28423122 http://dx.doi.org/10.21470/1678-9741-2016-0030 Text en http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Sá, Michel Pompeu Barros Oliveira
Ferraz, Paulo Ernando
Soares, Artur Freire
Miranda, Rodrigo Gusmão Albuquerque
Araújo, Mayara Lopes
Silva, Frederico Vasconcelos
Lima, Ricardo de Carvalho
Development and Validation of a Stratification Tool for Predicting Risk of Deep Sternal Wound Infection after Coronary Artery Bypass Grafting at a Brazilian Hospital
title Development and Validation of a Stratification Tool for Predicting Risk of Deep Sternal Wound Infection after Coronary Artery Bypass Grafting at a Brazilian Hospital
title_full Development and Validation of a Stratification Tool for Predicting Risk of Deep Sternal Wound Infection after Coronary Artery Bypass Grafting at a Brazilian Hospital
title_fullStr Development and Validation of a Stratification Tool for Predicting Risk of Deep Sternal Wound Infection after Coronary Artery Bypass Grafting at a Brazilian Hospital
title_full_unstemmed Development and Validation of a Stratification Tool for Predicting Risk of Deep Sternal Wound Infection after Coronary Artery Bypass Grafting at a Brazilian Hospital
title_short Development and Validation of a Stratification Tool for Predicting Risk of Deep Sternal Wound Infection after Coronary Artery Bypass Grafting at a Brazilian Hospital
title_sort development and validation of a stratification tool for predicting risk of deep sternal wound infection after coronary artery bypass grafting at a brazilian hospital
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5382897/
https://www.ncbi.nlm.nih.gov/pubmed/28423122
http://dx.doi.org/10.21470/1678-9741-2016-0030
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