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Pre-operative clinical predictors for cardiology referral prior to total joint arthroplasty: the ‘asymptomatic’ patient

BACKGROUND: No validated pre-operative cardiac risk stratification tool exists that is specific for total hip and total knee arthroplasty (THA and TKA, respectively). To reduce the risk of post-operative cardiac complication, surgeons need clear guidance on which patients are likely to benefit from...

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Autores principales: Elsiwy, Yassin, Symonds, Tristan, Doma, Kenji, Hazratwala, Kaushik, Wilkinson, Matthew, Letson, Hayley
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654604/
https://www.ncbi.nlm.nih.gov/pubmed/33168074
http://dx.doi.org/10.1186/s13018-020-02042-5
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author Elsiwy, Yassin
Symonds, Tristan
Doma, Kenji
Hazratwala, Kaushik
Wilkinson, Matthew
Letson, Hayley
author_facet Elsiwy, Yassin
Symonds, Tristan
Doma, Kenji
Hazratwala, Kaushik
Wilkinson, Matthew
Letson, Hayley
author_sort Elsiwy, Yassin
collection PubMed
description BACKGROUND: No validated pre-operative cardiac risk stratification tool exists that is specific for total hip and total knee arthroplasty (THA and TKA, respectively). To reduce the risk of post-operative cardiac complication, surgeons need clear guidance on which patients are likely to benefit from pre-operative cardiac optimisation. This is particularly important for asymptomatic patients, where the need is harder to determine. METHODS: Primary THA and TKA performed between January 1, 2010, and December 31, 2017, were identified from a single orthopaedic practice. Over 25 risk factors were evaluated as predictors for patients requiring additional cardiac investigation beyond an ECG and echocardiogram, and for cardiac abnormality detected upon additional investigation. A multivariate logistic regression was conducted using significant predictor variables identified from inferential statistics. A series of predictive scores were constructed and weighted to identify the influence of each variable on the ability to predict the detection of cardiac abnormality pre-operatively. RESULTS: Three hundred seventy-four patients were eligible for inclusion. Increasing age (p < 0.001), history of cerebrovascular accident (p = 0.018), family history of cardiovascular disease (FHx of CVD) (p < 0.001) and decreased ejection fraction (EF) (p < 0.001) were significant predictors of additional cardiac investigation being required. Increasing age (p = 0.003), male gender (p = 0.042), FHx of CVD (p = 0.001) and a reduced EF (p < 0.001) were significantly predictive for the detection of cardiac abnormality upon additional cardiac investigation. CONCLUSIONS: Increasing age, male gender, FHx of CVD and decreased ejection fraction are important risk factors to consider for pre-operative cardiac optimisation in THA and TKA patients. These findings can be applied towards future predictive models, to determine which asymptomatic patients are likely to benefit from pre-operative cardiac referral.
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spelling pubmed-76546042020-11-12 Pre-operative clinical predictors for cardiology referral prior to total joint arthroplasty: the ‘asymptomatic’ patient Elsiwy, Yassin Symonds, Tristan Doma, Kenji Hazratwala, Kaushik Wilkinson, Matthew Letson, Hayley J Orthop Surg Res Research Article BACKGROUND: No validated pre-operative cardiac risk stratification tool exists that is specific for total hip and total knee arthroplasty (THA and TKA, respectively). To reduce the risk of post-operative cardiac complication, surgeons need clear guidance on which patients are likely to benefit from pre-operative cardiac optimisation. This is particularly important for asymptomatic patients, where the need is harder to determine. METHODS: Primary THA and TKA performed between January 1, 2010, and December 31, 2017, were identified from a single orthopaedic practice. Over 25 risk factors were evaluated as predictors for patients requiring additional cardiac investigation beyond an ECG and echocardiogram, and for cardiac abnormality detected upon additional investigation. A multivariate logistic regression was conducted using significant predictor variables identified from inferential statistics. A series of predictive scores were constructed and weighted to identify the influence of each variable on the ability to predict the detection of cardiac abnormality pre-operatively. RESULTS: Three hundred seventy-four patients were eligible for inclusion. Increasing age (p < 0.001), history of cerebrovascular accident (p = 0.018), family history of cardiovascular disease (FHx of CVD) (p < 0.001) and decreased ejection fraction (EF) (p < 0.001) were significant predictors of additional cardiac investigation being required. Increasing age (p = 0.003), male gender (p = 0.042), FHx of CVD (p = 0.001) and a reduced EF (p < 0.001) were significantly predictive for the detection of cardiac abnormality upon additional cardiac investigation. CONCLUSIONS: Increasing age, male gender, FHx of CVD and decreased ejection fraction are important risk factors to consider for pre-operative cardiac optimisation in THA and TKA patients. These findings can be applied towards future predictive models, to determine which asymptomatic patients are likely to benefit from pre-operative cardiac referral. BioMed Central 2020-11-10 /pmc/articles/PMC7654604/ /pubmed/33168074 http://dx.doi.org/10.1186/s13018-020-02042-5 Text en © The Author(s) 2020 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/. The Creative Commons Public Domain Dedication waiver (http://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
Elsiwy, Yassin
Symonds, Tristan
Doma, Kenji
Hazratwala, Kaushik
Wilkinson, Matthew
Letson, Hayley
Pre-operative clinical predictors for cardiology referral prior to total joint arthroplasty: the ‘asymptomatic’ patient
title Pre-operative clinical predictors for cardiology referral prior to total joint arthroplasty: the ‘asymptomatic’ patient
title_full Pre-operative clinical predictors for cardiology referral prior to total joint arthroplasty: the ‘asymptomatic’ patient
title_fullStr Pre-operative clinical predictors for cardiology referral prior to total joint arthroplasty: the ‘asymptomatic’ patient
title_full_unstemmed Pre-operative clinical predictors for cardiology referral prior to total joint arthroplasty: the ‘asymptomatic’ patient
title_short Pre-operative clinical predictors for cardiology referral prior to total joint arthroplasty: the ‘asymptomatic’ patient
title_sort pre-operative clinical predictors for cardiology referral prior to total joint arthroplasty: the ‘asymptomatic’ patient
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654604/
https://www.ncbi.nlm.nih.gov/pubmed/33168074
http://dx.doi.org/10.1186/s13018-020-02042-5
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