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The association of radiologic body composition parameters with clinical outcomes in level-1 trauma patients
PURPOSE: The present study aims to assess whether CT-derived muscle mass, muscle density, and visceral fat mass are associated with in-hospital complications and clinical outcome in level-1 trauma patients. METHODS: A retrospective cohort study was conducted on adult patients admitted to the Univers...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10449658/ https://www.ncbi.nlm.nih.gov/pubmed/36862245 http://dx.doi.org/10.1007/s00068-023-02252-6 |
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author | Sweet, Arthur A. R. Kobes, Tim Houwert, Roderick M. Groenwold, Rolf H. H. Moeskops, Pim Leenen, Luke P. H. de Jong, Pim A. Veldhuis, Wouter B. van Baal, Mark C. P. M. |
author_facet | Sweet, Arthur A. R. Kobes, Tim Houwert, Roderick M. Groenwold, Rolf H. H. Moeskops, Pim Leenen, Luke P. H. de Jong, Pim A. Veldhuis, Wouter B. van Baal, Mark C. P. M. |
author_sort | Sweet, Arthur A. R. |
collection | PubMed |
description | PURPOSE: The present study aims to assess whether CT-derived muscle mass, muscle density, and visceral fat mass are associated with in-hospital complications and clinical outcome in level-1 trauma patients. METHODS: A retrospective cohort study was conducted on adult patients admitted to the University Medical Center Utrecht following a trauma between January 1 and December 31, 2017. Trauma patients aged 16 years or older without severe neurological injuries, who underwent a CT that included the abdomen within 7 days of admission, were included. An artificial intelligence (AI) algorithm was used to retrieve muscle areas to calculate the psoas muscle index and to retrieve psoas muscle radiation attenuation and visceral fat (VF) area from axial CT images. Multivariable logistic and linear regression analyses were performed to assess associations between body composition parameters and outcomes. RESULTS: A total of 404 patients were included for analysis. The median age was 49 years (interquartile range [IQR] 30–64), and 66.6% were male. Severe comorbidities (ASA 3–4) were seen in 10.9%, and the median ISS was 9 (IQR 5–14). Psoas muscle index was not independently associated with complications, but it was associated with ICU admission (odds ratio [OR] 0.79, 95% confidence interval [CI] 0.65–0.95), and an unfavorable Glasgow Outcome Scale (GOS) score at discharge (OR 0.62, 95% CI 0.45–0.85). Psoas muscle radiation attenuation was independently associated with the development of any complication (OR 0.60, 95% CI 0.42–0.85), pneumonia (OR 0.63, 95% CI 0.41–0.96), and delirium (OR 0.49, 95% CI 0.28–0.87). VF was associated with developing a delirium (OR 1.95, 95% CI 1.12–3.41). CONCLUSION: In level-1 trauma patients without severe neurological injuries, automatically derived body composition parameters are able to independently predict an increased risk of specific complications and other poor outcomes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00068-023-02252-6. |
format | Online Article Text |
id | pubmed-10449658 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-104496582023-08-26 The association of radiologic body composition parameters with clinical outcomes in level-1 trauma patients Sweet, Arthur A. R. Kobes, Tim Houwert, Roderick M. Groenwold, Rolf H. H. Moeskops, Pim Leenen, Luke P. H. de Jong, Pim A. Veldhuis, Wouter B. van Baal, Mark C. P. M. Eur J Trauma Emerg Surg Original Article PURPOSE: The present study aims to assess whether CT-derived muscle mass, muscle density, and visceral fat mass are associated with in-hospital complications and clinical outcome in level-1 trauma patients. METHODS: A retrospective cohort study was conducted on adult patients admitted to the University Medical Center Utrecht following a trauma between January 1 and December 31, 2017. Trauma patients aged 16 years or older without severe neurological injuries, who underwent a CT that included the abdomen within 7 days of admission, were included. An artificial intelligence (AI) algorithm was used to retrieve muscle areas to calculate the psoas muscle index and to retrieve psoas muscle radiation attenuation and visceral fat (VF) area from axial CT images. Multivariable logistic and linear regression analyses were performed to assess associations between body composition parameters and outcomes. RESULTS: A total of 404 patients were included for analysis. The median age was 49 years (interquartile range [IQR] 30–64), and 66.6% were male. Severe comorbidities (ASA 3–4) were seen in 10.9%, and the median ISS was 9 (IQR 5–14). Psoas muscle index was not independently associated with complications, but it was associated with ICU admission (odds ratio [OR] 0.79, 95% confidence interval [CI] 0.65–0.95), and an unfavorable Glasgow Outcome Scale (GOS) score at discharge (OR 0.62, 95% CI 0.45–0.85). Psoas muscle radiation attenuation was independently associated with the development of any complication (OR 0.60, 95% CI 0.42–0.85), pneumonia (OR 0.63, 95% CI 0.41–0.96), and delirium (OR 0.49, 95% CI 0.28–0.87). VF was associated with developing a delirium (OR 1.95, 95% CI 1.12–3.41). CONCLUSION: In level-1 trauma patients without severe neurological injuries, automatically derived body composition parameters are able to independently predict an increased risk of specific complications and other poor outcomes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00068-023-02252-6. Springer Berlin Heidelberg 2023-03-02 2023 /pmc/articles/PMC10449658/ /pubmed/36862245 http://dx.doi.org/10.1007/s00068-023-02252-6 Text en © The Author(s) 2023 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/) . |
spellingShingle | Original Article Sweet, Arthur A. R. Kobes, Tim Houwert, Roderick M. Groenwold, Rolf H. H. Moeskops, Pim Leenen, Luke P. H. de Jong, Pim A. Veldhuis, Wouter B. van Baal, Mark C. P. M. The association of radiologic body composition parameters with clinical outcomes in level-1 trauma patients |
title | The association of radiologic body composition parameters with clinical outcomes in level-1 trauma patients |
title_full | The association of radiologic body composition parameters with clinical outcomes in level-1 trauma patients |
title_fullStr | The association of radiologic body composition parameters with clinical outcomes in level-1 trauma patients |
title_full_unstemmed | The association of radiologic body composition parameters with clinical outcomes in level-1 trauma patients |
title_short | The association of radiologic body composition parameters with clinical outcomes in level-1 trauma patients |
title_sort | association of radiologic body composition parameters with clinical outcomes in level-1 trauma patients |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10449658/ https://www.ncbi.nlm.nih.gov/pubmed/36862245 http://dx.doi.org/10.1007/s00068-023-02252-6 |
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