The identification of an optimal body size parameter to adjust skeletal muscle area on chest CT in COVID-19 patients

Copyright: © 2024 Hylonome Publications..

Objectives: The most efficient way to adjust skeletal muscle area (SMA) derived from chest CT to body size remains unclear. We hypothesized that vertebral body area (VBA) measurement would allow such efficient adjustment.

Methods: We conducted a retrospective observational study of chest CT imaging in a cohort of critically ill COVID-19 patients. We measured paravertebral SMA at T5 level and T5 vertebral body anteroposterior length, width, and area. We used linear regression and multivariable modelling to assess the association of VBA with SMA.

Results: In 48 COVID-19 patients in ICU, T5 VBA could be easily derived from simple width and anteroposterior length linear measurements. T5 VBA (measured manually or estimated from width and length) performed similarly to height (R2 of 0.22) as an adjustment variable for SMA, with R2 of 0.23 and 0.22, respectively. Gender had the strongest correlation with SMA (R2 = 0.28). Adding height or age to a model using gender and VBA did not improve correlation.

Conclusions: Gender and estimated VBA from simple linear measurements at T5 level on CT images can be utilized for adjustment of SMA without the need for height. Validation of these findings in larger cohorts of critically ill patients is now needed.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:9

Enthalten in:

Journal of frailty, sarcopenia and falls - 9(2024), 1 vom: 15. März, Seite 16-24

Sprache:

Englisch

Beteiligte Personen:

Kutaiba, Numan [VerfasserIn]
Dobson, Julie [VerfasserIn]
Finnis, Mark [VerfasserIn]
Bellomo, Rinaldo [VerfasserIn]

Links:

Volltext

Themen:

Chest computed tomography
Journal Article
Sarcopenia
Skeletal muscle area

Anmerkungen:

Date Revised 07.03.2024

published: Electronic-eCollection

Citation Status PubMed-not-MEDLINE

doi:

10.22540/JFSF-09-016

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM369343786