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Computed tomography‐defined body composition as prognostic markers for unfavourable outcomes and in‐hospital mortality in coronavirus disease 2019

BACKGROUND: Low skeletal muscle mass (LSMM) and visceral fat areas can be assessed by cross‐sectional images. These parameters are associated with several clinically relevant factors in various disorders with predictive and prognostic implications. Our aim was to establish the effect of computed tom...

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Autores principales: Meyer, Hans‐Jonas, Wienke, Andreas, Surov, Alexey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818651/
https://www.ncbi.nlm.nih.gov/pubmed/35018725
http://dx.doi.org/10.1002/jcsm.12868
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author Meyer, Hans‐Jonas
Wienke, Andreas
Surov, Alexey
author_facet Meyer, Hans‐Jonas
Wienke, Andreas
Surov, Alexey
author_sort Meyer, Hans‐Jonas
collection PubMed
description BACKGROUND: Low skeletal muscle mass (LSMM) and visceral fat areas can be assessed by cross‐sectional images. These parameters are associated with several clinically relevant factors in various disorders with predictive and prognostic implications. Our aim was to establish the effect of computed tomography (CT)‐defined LSMM and fat areas on unfavourable outcomes and in‐hospital mortality in coronavirus disease 2019 (COVID‐19) patients based on a large patient sample. METHODS: MEDLINE library, Cochrane, and Scopus databases were screened for the associations between CT‐defined LSMM as well as fat areas and in‐hospital mortality in COVID‐19 patients up to September 2021. In total, six studies were suitable for the analysis and included into the present analysis. RESULTS: The included studies comprised 1059 patients, 591 men (55.8%) and 468 women (44.2%), with a mean age of 60.1 years ranging from 48 to 66 years. The pooled prevalence of LSMM was 33.6%. The pooled odds ratio for the effect of LSMM on in‐hospital mortality in univariate analysis was 5.84 [95% confidence interval (CI) 1.07–31.83]. It was 2.73 (95% CI 0.54–13.70) in multivariate analysis. The pooled odds ratio of high visceral fat area on unfavourable outcome in univariate analysis was 2.65 (95% CI 1.57–4.47). CONCLUSIONS: Computed tomography‐defined LSMM and high visceral fat area have a relevant association with in‐hospital mortality in COVID‐19 patients and should be included as relevant prognostic biomarkers into clinical routine.
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spelling pubmed-88186512022-02-09 Computed tomography‐defined body composition as prognostic markers for unfavourable outcomes and in‐hospital mortality in coronavirus disease 2019 Meyer, Hans‐Jonas Wienke, Andreas Surov, Alexey J Cachexia Sarcopenia Muscle Original Articles: Clinical BACKGROUND: Low skeletal muscle mass (LSMM) and visceral fat areas can be assessed by cross‐sectional images. These parameters are associated with several clinically relevant factors in various disorders with predictive and prognostic implications. Our aim was to establish the effect of computed tomography (CT)‐defined LSMM and fat areas on unfavourable outcomes and in‐hospital mortality in coronavirus disease 2019 (COVID‐19) patients based on a large patient sample. METHODS: MEDLINE library, Cochrane, and Scopus databases were screened for the associations between CT‐defined LSMM as well as fat areas and in‐hospital mortality in COVID‐19 patients up to September 2021. In total, six studies were suitable for the analysis and included into the present analysis. RESULTS: The included studies comprised 1059 patients, 591 men (55.8%) and 468 women (44.2%), with a mean age of 60.1 years ranging from 48 to 66 years. The pooled prevalence of LSMM was 33.6%. The pooled odds ratio for the effect of LSMM on in‐hospital mortality in univariate analysis was 5.84 [95% confidence interval (CI) 1.07–31.83]. It was 2.73 (95% CI 0.54–13.70) in multivariate analysis. The pooled odds ratio of high visceral fat area on unfavourable outcome in univariate analysis was 2.65 (95% CI 1.57–4.47). CONCLUSIONS: Computed tomography‐defined LSMM and high visceral fat area have a relevant association with in‐hospital mortality in COVID‐19 patients and should be included as relevant prognostic biomarkers into clinical routine. John Wiley and Sons Inc. 2022-01-12 2022-02 /pmc/articles/PMC8818651/ /pubmed/35018725 http://dx.doi.org/10.1002/jcsm.12868 Text en © 2021 The Authors. Journal of Cachexia, Sarcopenia and Muscle published by John Wiley & Sons Ltd on behalf of Society on Sarcopenia, Cachexia and Wasting Disorders. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles: Clinical
Meyer, Hans‐Jonas
Wienke, Andreas
Surov, Alexey
Computed tomography‐defined body composition as prognostic markers for unfavourable outcomes and in‐hospital mortality in coronavirus disease 2019
title Computed tomography‐defined body composition as prognostic markers for unfavourable outcomes and in‐hospital mortality in coronavirus disease 2019
title_full Computed tomography‐defined body composition as prognostic markers for unfavourable outcomes and in‐hospital mortality in coronavirus disease 2019
title_fullStr Computed tomography‐defined body composition as prognostic markers for unfavourable outcomes and in‐hospital mortality in coronavirus disease 2019
title_full_unstemmed Computed tomography‐defined body composition as prognostic markers for unfavourable outcomes and in‐hospital mortality in coronavirus disease 2019
title_short Computed tomography‐defined body composition as prognostic markers for unfavourable outcomes and in‐hospital mortality in coronavirus disease 2019
title_sort computed tomography‐defined body composition as prognostic markers for unfavourable outcomes and in‐hospital mortality in coronavirus disease 2019
topic Original Articles: Clinical
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818651/
https://www.ncbi.nlm.nih.gov/pubmed/35018725
http://dx.doi.org/10.1002/jcsm.12868
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