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Development of a new sternal dehiscence prediction scale for decision making in sternal closure techniques after cardiac surgery

BACKGROUND: After sternotomy, the spectrum for sternal osteosynthesis comprises standard wiring and more complex techniques, like titanium plating. The aim of this study is to develop a predictive risk score that evaluates the risk of sternum instability individually. The surgeon may then choose an...

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Autores principales: Nooh, Ehab, Griesbach, Colin, Rösch, Johannes, Weyand, Michael, Harig, Frank
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201871/
https://www.ncbi.nlm.nih.gov/pubmed/34127025
http://dx.doi.org/10.1186/s13019-021-01555-2
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author Nooh, Ehab
Griesbach, Colin
Rösch, Johannes
Weyand, Michael
Harig, Frank
author_facet Nooh, Ehab
Griesbach, Colin
Rösch, Johannes
Weyand, Michael
Harig, Frank
author_sort Nooh, Ehab
collection PubMed
description BACKGROUND: After sternotomy, the spectrum for sternal osteosynthesis comprises standard wiring and more complex techniques, like titanium plating. The aim of this study is to develop a predictive risk score that evaluates the risk of sternum instability individually. The surgeon may then choose an appropriate sternal osteosynthesis technique that is risk- adjusted as well as cost-effective. METHODS: Data from 7.173 patients operated via sternotomy for all cardiovascular indications from 2008 until 2017 were retrospectively analyzed. Sternal dehiscence occurred in 2.5% of patients (n = 176). A multivariable analysis model examined pre- and intraoperative factors. A multivariable logistic regression model and a backward elimination based on the Akaike Information Criterion (AIC) a logistic model were selected. RESULTS: The model showed good sensitivity and specificity (area under the receiver-operating characteristic curve, AUC: 0.76) and several predictors of sternal instability could be evaluated. Multivariable logistic regression showed the highest Odds Ratios (OR) for reexploration (OR 6.6, confidence interval, CI [4.5–9.5], p < 0.001), obesity (body mass index, BMI > 35 kg/m(2)) (OR 4.23, [CI 2.4–7.3], p < 0.001), insulin-dependent diabetes mellitus (IDDM) (OR 2.2, CI [1.5–3.2], p = 0.01), smoking (OR 2.03, [CI 1.3–3.08], p = 0.001). After weighting the probability of sternum dehiscence with each factor, a risk score model was proposed scaling from − 1 to 5 points. This resulted in a risk score ranging up to 18 points, with an estimated risk for sternum complication up to 74%. CONCLUSIONS: A weighted scoring system based on individual risk factors was specifically created to predict sternal dehiscence. High-scoring patients should receive additive closure techniques.
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spelling pubmed-82018712021-06-16 Development of a new sternal dehiscence prediction scale for decision making in sternal closure techniques after cardiac surgery Nooh, Ehab Griesbach, Colin Rösch, Johannes Weyand, Michael Harig, Frank J Cardiothorac Surg Research Article BACKGROUND: After sternotomy, the spectrum for sternal osteosynthesis comprises standard wiring and more complex techniques, like titanium plating. The aim of this study is to develop a predictive risk score that evaluates the risk of sternum instability individually. The surgeon may then choose an appropriate sternal osteosynthesis technique that is risk- adjusted as well as cost-effective. METHODS: Data from 7.173 patients operated via sternotomy for all cardiovascular indications from 2008 until 2017 were retrospectively analyzed. Sternal dehiscence occurred in 2.5% of patients (n = 176). A multivariable analysis model examined pre- and intraoperative factors. A multivariable logistic regression model and a backward elimination based on the Akaike Information Criterion (AIC) a logistic model were selected. RESULTS: The model showed good sensitivity and specificity (area under the receiver-operating characteristic curve, AUC: 0.76) and several predictors of sternal instability could be evaluated. Multivariable logistic regression showed the highest Odds Ratios (OR) for reexploration (OR 6.6, confidence interval, CI [4.5–9.5], p < 0.001), obesity (body mass index, BMI > 35 kg/m(2)) (OR 4.23, [CI 2.4–7.3], p < 0.001), insulin-dependent diabetes mellitus (IDDM) (OR 2.2, CI [1.5–3.2], p = 0.01), smoking (OR 2.03, [CI 1.3–3.08], p = 0.001). After weighting the probability of sternum dehiscence with each factor, a risk score model was proposed scaling from − 1 to 5 points. This resulted in a risk score ranging up to 18 points, with an estimated risk for sternum complication up to 74%. CONCLUSIONS: A weighted scoring system based on individual risk factors was specifically created to predict sternal dehiscence. High-scoring patients should receive additive closure techniques. BioMed Central 2021-06-14 /pmc/articles/PMC8201871/ /pubmed/34127025 http://dx.doi.org/10.1186/s13019-021-01555-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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
Nooh, Ehab
Griesbach, Colin
Rösch, Johannes
Weyand, Michael
Harig, Frank
Development of a new sternal dehiscence prediction scale for decision making in sternal closure techniques after cardiac surgery
title Development of a new sternal dehiscence prediction scale for decision making in sternal closure techniques after cardiac surgery
title_full Development of a new sternal dehiscence prediction scale for decision making in sternal closure techniques after cardiac surgery
title_fullStr Development of a new sternal dehiscence prediction scale for decision making in sternal closure techniques after cardiac surgery
title_full_unstemmed Development of a new sternal dehiscence prediction scale for decision making in sternal closure techniques after cardiac surgery
title_short Development of a new sternal dehiscence prediction scale for decision making in sternal closure techniques after cardiac surgery
title_sort development of a new sternal dehiscence prediction scale for decision making in sternal closure techniques after cardiac surgery
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8201871/
https://www.ncbi.nlm.nih.gov/pubmed/34127025
http://dx.doi.org/10.1186/s13019-021-01555-2
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