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Predictors of muscle necrosis in patients with acute compartment syndrome

PURPOSE: The predictors of muscle necrosis after acute compartment syndrome (ACS) remain debated. This study aimed to investigate the predictors for muscle necrosis in ACS patients. METHODS: We collected data on ACS patients following fractures from January 2010 to November 2022. Patients were divid...

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Autores principales: Wang, Tao, Yang, Shuo, Guo, Junfei, Long, Yubin, Hou, Zhiyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9885051/
https://www.ncbi.nlm.nih.gov/pubmed/36715712
http://dx.doi.org/10.1007/s00264-023-05699-9
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author Wang, Tao
Yang, Shuo
Guo, Junfei
Long, Yubin
Hou, Zhiyong
author_facet Wang, Tao
Yang, Shuo
Guo, Junfei
Long, Yubin
Hou, Zhiyong
author_sort Wang, Tao
collection PubMed
description PURPOSE: The predictors of muscle necrosis after acute compartment syndrome (ACS) remain debated. This study aimed to investigate the predictors for muscle necrosis in ACS patients. METHODS: We collected data on ACS patients following fractures from January 2010 to November 2022. Patients were divided into the muscle necrosis group (MG) and the non-muscle necrosis group (NG). The demographics, comorbidities, and admission laboratory indicators were computed by univariate analysis, logistic regression analysis, and receiver-operating characteristic (ROC) curve analysis. RESULTS: In our study, the rate of MN was 37.6% (83 of 221). Univariate analysis showed that numerous factors were associated with muscle necrosis following ACS. Logistic regression analysis indicated that crush injury (p = 0.007), neutrophil (NEU, p = 0.001), creatine kinase myocardial band (CKMB, p = 0.047), and prothrombin time (PT, p = 0.031) were risk factors. Additionally, ROC curve analysis identified 11.415 10(9)/L, 116.825 U/L, and 12.51 s as the cut-off values for NEU, CKMB, and PT to predict muscle necrosis, respectively. Furthermore, the combination of NEU, CKMB, and PT had the highest diagnostic accuracy. CONCLUSIONS: Our findings showed that crush injury and the level of NEU, CKMB, and PT were risk factors for muscle necrosis after ACS. Additionally, we also identified the cut-off values of NEU, CKMB, and PT and found the combination of crush injury, PT, and NEU with the highest diagnostic accuracy, helping us individualize the assessment risk of muscle necrosis to manage early targeted interventions.
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spelling pubmed-98850512023-01-30 Predictors of muscle necrosis in patients with acute compartment syndrome Wang, Tao Yang, Shuo Guo, Junfei Long, Yubin Hou, Zhiyong Int Orthop Original Paper PURPOSE: The predictors of muscle necrosis after acute compartment syndrome (ACS) remain debated. This study aimed to investigate the predictors for muscle necrosis in ACS patients. METHODS: We collected data on ACS patients following fractures from January 2010 to November 2022. Patients were divided into the muscle necrosis group (MG) and the non-muscle necrosis group (NG). The demographics, comorbidities, and admission laboratory indicators were computed by univariate analysis, logistic regression analysis, and receiver-operating characteristic (ROC) curve analysis. RESULTS: In our study, the rate of MN was 37.6% (83 of 221). Univariate analysis showed that numerous factors were associated with muscle necrosis following ACS. Logistic regression analysis indicated that crush injury (p = 0.007), neutrophil (NEU, p = 0.001), creatine kinase myocardial band (CKMB, p = 0.047), and prothrombin time (PT, p = 0.031) were risk factors. Additionally, ROC curve analysis identified 11.415 10(9)/L, 116.825 U/L, and 12.51 s as the cut-off values for NEU, CKMB, and PT to predict muscle necrosis, respectively. Furthermore, the combination of NEU, CKMB, and PT had the highest diagnostic accuracy. CONCLUSIONS: Our findings showed that crush injury and the level of NEU, CKMB, and PT were risk factors for muscle necrosis after ACS. Additionally, we also identified the cut-off values of NEU, CKMB, and PT and found the combination of crush injury, PT, and NEU with the highest diagnostic accuracy, helping us individualize the assessment risk of muscle necrosis to manage early targeted interventions. Springer Berlin Heidelberg 2023-01-30 2023-04 /pmc/articles/PMC9885051/ /pubmed/36715712 http://dx.doi.org/10.1007/s00264-023-05699-9 Text en © The Author(s) under exclusive licence to SICOT aisbl 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Paper
Wang, Tao
Yang, Shuo
Guo, Junfei
Long, Yubin
Hou, Zhiyong
Predictors of muscle necrosis in patients with acute compartment syndrome
title Predictors of muscle necrosis in patients with acute compartment syndrome
title_full Predictors of muscle necrosis in patients with acute compartment syndrome
title_fullStr Predictors of muscle necrosis in patients with acute compartment syndrome
title_full_unstemmed Predictors of muscle necrosis in patients with acute compartment syndrome
title_short Predictors of muscle necrosis in patients with acute compartment syndrome
title_sort predictors of muscle necrosis in patients with acute compartment syndrome
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9885051/
https://www.ncbi.nlm.nih.gov/pubmed/36715712
http://dx.doi.org/10.1007/s00264-023-05699-9
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