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Predicting the Exception—CRP and Primary Hip Arthroplasty
Background: While primary hip arthroplasty is the most common operative procedure in orthopedic surgery, a periprosthetic joint infection is its most severe complication. Early detection and prediction are crucial. In this study, we aimed to determine the value of postoperative C-reactive protein (C...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8584609/ https://www.ncbi.nlm.nih.gov/pubmed/34768504 http://dx.doi.org/10.3390/jcm10214985 |
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author | Meier, Marc-Pascal Bauer, Ina Juliana Maheshwari, Arvind K. Husen, Martin Jäckle, Katharina Hubert, Jan Hawellek, Thelonius Lehmann, Wolfgang Saul, Dominik |
author_facet | Meier, Marc-Pascal Bauer, Ina Juliana Maheshwari, Arvind K. Husen, Martin Jäckle, Katharina Hubert, Jan Hawellek, Thelonius Lehmann, Wolfgang Saul, Dominik |
author_sort | Meier, Marc-Pascal |
collection | PubMed |
description | Background: While primary hip arthroplasty is the most common operative procedure in orthopedic surgery, a periprosthetic joint infection is its most severe complication. Early detection and prediction are crucial. In this study, we aimed to determine the value of postoperative C-reactive protein (CRP) and develop a formula to predict this rare, but devastating complication. Methods: We retrospectively evaluated 708 patients with primary hip arthroplasty. CRP, white blood cell count (WBC), and several patient characteristics were assessed for 20 days following the operative procedure. Results: Eight patients suffered an early acute periprosthetic infection. The maximum CRP predicted an infection with a sensitivity and specificity of 75% and 56.9%, respectively, while a binary logistic regression reached values of 75% and 80%. A multinominal logistic regression, however, was able to predict an early infection with a sensitivity and specificity of 87.5% and 78.9%. With a one-phase decay, 71.6% of the postoperative CRP-variance could be predicted. Conclusion: To predict early acute periprosthetic joint infection after primary hip arthroplasty, a multinominal logistic regression is the most promising approach. Including five parameters, an early infection can be predicted on day 5 after the operative procedure with 87.5% sensitivity, while it can be excluded with 78.9% specificity. |
format | Online Article Text |
id | pubmed-8584609 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-85846092021-11-12 Predicting the Exception—CRP and Primary Hip Arthroplasty Meier, Marc-Pascal Bauer, Ina Juliana Maheshwari, Arvind K. Husen, Martin Jäckle, Katharina Hubert, Jan Hawellek, Thelonius Lehmann, Wolfgang Saul, Dominik J Clin Med Article Background: While primary hip arthroplasty is the most common operative procedure in orthopedic surgery, a periprosthetic joint infection is its most severe complication. Early detection and prediction are crucial. In this study, we aimed to determine the value of postoperative C-reactive protein (CRP) and develop a formula to predict this rare, but devastating complication. Methods: We retrospectively evaluated 708 patients with primary hip arthroplasty. CRP, white blood cell count (WBC), and several patient characteristics were assessed for 20 days following the operative procedure. Results: Eight patients suffered an early acute periprosthetic infection. The maximum CRP predicted an infection with a sensitivity and specificity of 75% and 56.9%, respectively, while a binary logistic regression reached values of 75% and 80%. A multinominal logistic regression, however, was able to predict an early infection with a sensitivity and specificity of 87.5% and 78.9%. With a one-phase decay, 71.6% of the postoperative CRP-variance could be predicted. Conclusion: To predict early acute periprosthetic joint infection after primary hip arthroplasty, a multinominal logistic regression is the most promising approach. Including five parameters, an early infection can be predicted on day 5 after the operative procedure with 87.5% sensitivity, while it can be excluded with 78.9% specificity. MDPI 2021-10-27 /pmc/articles/PMC8584609/ /pubmed/34768504 http://dx.doi.org/10.3390/jcm10214985 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Meier, Marc-Pascal Bauer, Ina Juliana Maheshwari, Arvind K. Husen, Martin Jäckle, Katharina Hubert, Jan Hawellek, Thelonius Lehmann, Wolfgang Saul, Dominik Predicting the Exception—CRP and Primary Hip Arthroplasty |
title | Predicting the Exception—CRP and Primary Hip Arthroplasty |
title_full | Predicting the Exception—CRP and Primary Hip Arthroplasty |
title_fullStr | Predicting the Exception—CRP and Primary Hip Arthroplasty |
title_full_unstemmed | Predicting the Exception—CRP and Primary Hip Arthroplasty |
title_short | Predicting the Exception—CRP and Primary Hip Arthroplasty |
title_sort | predicting the exception—crp and primary hip arthroplasty |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8584609/ https://www.ncbi.nlm.nih.gov/pubmed/34768504 http://dx.doi.org/10.3390/jcm10214985 |
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