Clinically Practical Approach for Screening of Low Muscularity Using Electronic Linear Measures on Computed Tomography Images in Critically Ill Patients. Issue 5 (6th December 2017)

• Record Type: Journal Article
• Authors: Avrutin, Egor; Moisey, Lesley L.; Zhang, Roselyn; Khattab, Jenna; Todd, Emma; Premji, Tahira; Kozar, Rosemary; Heyland, Daren K.; Mourtzakis, Marina
• Is Part Of: JPEN, Journal of parenteral and enteral nutrition. Volume 42:Issue 5(2018)
• Page Start: 885
• Page End: 891
• Publication Date: 2017-12-06
• Subjects: intensive care unit -- ICU -- skeletal muscle -- low muscle mass -- body composition; Parenteral feeding -- Periodicals; Enteral feeding -- Periodicals; 615.85484
• DOI: 10.1002/jpen.1019
• Languages: English
• ISSNs: 0148-6071

Abstract

Abstract: Background: Computed tomography (CT) scans performed during routine hospital care offer the opportunity to quantify skeletal muscle and predict mortality and morbidity in intensive care unit (ICU) patients. Existing methods of muscle cross‐sectional area (CSA) quantification require specialized software, training, and time commitment that may not be feasible in a clinical setting. In this article, we explore a new screening method to identify patients with low muscle mass. Methods: We analyzed 145 scans of elderly ICU patients (≥65 years old) using a combination of measures obtained with a digital ruler, commonly found on hospital radiological software. The psoas and paraspinal muscle groups at the level of the third lumbar vertebra (L3) were evaluated by using 2 linear measures each and compared with an established method of CT image analysis of total muscle CSA in the L3 region. Results: There was a strong association between linear measures of psoas and paraspinal muscle groups and total L3 muscle CSA ( R 2 = 0.745, P < 0.001). Linear measures, age, and sex were included as covariates in a multiple logistic regression to predict those with low muscle mass; receiver operating characteristic (ROC) area under the curve (AUC) of the combined psoas and paraspinal linear index model was 0.920. Intraclass correlation coefficients (ICCs) were used to evaluate intrarater and interrater reliability, resulting in scores of 0.979 (95% CI: 0.940–0.992) and 0.937 (95% CI: 0.828–0.978), respectively. Conclusions: A digital ruler can reliably predict L3 muscle CSA, and these linear measures may be used to identify critically ill patients with low muscularity who are at risk for worse clinical outcomes.