Quantification of Sarcopenia using Chest Computed Tomography of the Pectoralis Major Muscle as a Prognostic Tool for Cardiac Surgery Outcomes
Nezafati, Pouya, Saxena, Pankaj, Raman, Jaishankar, Hebbard, Lionel, Draper, Narelle, and McFarlane, Craig (2026) Quantification of Sarcopenia using Chest Computed Tomography of the Pectoralis Major Muscle as a Prognostic Tool for Cardiac Surgery Outcomes. Heart, Lung and Circulation. (In Press)
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Abstract
Background and Aim Cardiac surgery is increasingly performed on elderly, frail patients, making objective frailty markers critical for predicting outcomes. Sarcopenia, as defined by the progressive loss of muscle mass and strength, is linked to poorer outcomes after surgery. The pectoralis major (PM) muscle cross-sectional area from chest computed tomography (CT) may offer a novel quantitative method for assessing sarcopenia in cardiac surgery patients. Methods This study includes data from 237 individuals, who had preoperative chest CT scans and underwent cardiac surgery involving sternotomy from 2019 to 2023 at the Townsville University Hospital, Queensland, Australia. PM muscle area, density, and thickness were measured using chest CT scans. Sarcopenia was defined by the lowest sex-specific quartile in PM area. Demographic data, intraoperative, and postoperative outcomes up to 30 days were collected. Logistic regression analysis assessed the association of sarcopenia with postoperative outcomes. Receiver operating characteristic (ROC) analysis evaluated the clinical value of PM thickness and density in predicting sarcopenia. Results Cut-off values for PM area were 1,045 mm2 for males and 609 mm2 for females, with 59 individuals (25.1%) meeting the criteria for sarcopenia. Sarcopenic patients were significantly older than non-sarcopenic patients (p<0.001) and had a lower body mass index (p=0.008). Logistic regression showed sarcopenia significantly increased the risk of extended hospital stays (Odds ratio; OR=5.08), longer intensive care unit (ICU) stays (OR=3.16), and prolonged intubation times (OR=2.49; all p<0.05). ROC analysis showed high accuracy for muscle thickness (area under the curve; AUC=0.85) in distinguishing sarcopenia, with cut-off values of 12.2 mm for males and 8.1 mm for females. Muscle density had moderate accuracy (AUC=0.64). Conclusions Our study demonstrates that defining sarcopenia based on the PM cross-sectional area measured from chest CT scans provides a significant predictor of postoperative outcomes in cardiac surgery patients. The established sex-specific cut-off values for muscle area, density and thickness effectively identified sarcopenia, which is associated with prolonged hospitalisation, extended ICU stay, longer intubation time, and an increased risk of postoperative complications.
| Item ID: | 91947 |
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| Item Type: | Article (Research - C1) |
| ISSN: | 1444-2892 |
| Keywords: | Sarcopenia; Frailty; Cardiac surgery; Computed tomography; Pectoralis major |
| Copyright Information: | © 2026 The Author(s). Published by Elsevier B.V. on behalf of Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
| Funders: | Townsville Hospital and Health Services Study Education and Research Trust Fund (THHS) |
| Projects and Grants: | THHS Study, Education and Research Trust Account (SERTA) Research Project Grant 2021–14 |
| Date Deposited: | 19 May 2026 00:09 |
| FoR Codes: | 32 BIOMEDICAL AND CLINICAL SCIENCES > 3201 Cardiovascular medicine and haematology > 320101 Cardiology (incl. cardiovascular diseases) @ 60% 32 BIOMEDICAL AND CLINICAL SCIENCES > 3202 Clinical sciences > 320206 Diagnostic radiography @ 30% 32 BIOMEDICAL AND CLINICAL SCIENCES > 3202 Clinical sciences > 320220 Pathology (excl. oral pathology) @ 10% |
| SEO Codes: | 20 HEALTH > 2001 Clinical health > 200101 Diagnosis of human diseases and conditions @ 60% 20 HEALTH > 2001 Clinical health > 200104 Prevention of human diseases and conditions @ 40% |
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