Prognostic Value of Chest CT-Derived Pectoralis Muscle Metrics for In-Hospital Mortality and Invasive Mechanical Ventilation in AECOPD.

PURPOSE: The clinical significance of pectoralis muscle depletion during acute exacerbations of chronic obstructive pulmonary disease (AECOPD) remains unclear. This study investigated the independent prognostic value of computed tomography (CT)-derived pectoralis muscle metrics for in-hospital mortality and invasive mechanical ventilation (IMV) in AECOPD.

PATIENTS AND METHODS: This retrospective study included 464 consecutive AECOPD patients who underwent chest CT within 48 hours of admission. Pectoralis muscle area and muscle density (PMD) were quantified from CT. The pectoralis muscle index (PMI) was calculated by normalizing muscle area to height squared. Multivariable Cox regression models evaluated associations between these indices and adverse outcomes. The incremental predictive value of adding muscle indices to DECAF and BAP-65 scores was assessed using the area under the curve (AUC).

RESULTS: Among 464 patients, 44 (9.5%) died and 86 (18.5%) required IMV during hospitalization. Both PMI and PMD were significantly lower in non-survivors and IMV patients (all P<0.001). In fully adjusted models, each 1 cm2/m2 increase in PMI was associated with reduced risks of in-hospital mortality (HR 0.68, 95% CI 0.58-0.78) and IMV (HR 0.72, 95% CI 0.64-0.81). Each 5 HU increase in PMD independently predicted lower in-hospital mortality (HR 0.77, 95% CI 0.66-0.90) and IMV (HR 0.59, 95% CI 0.50-0.70). Incorporation of both PMI and PMD into the DECAF and BAP-65 scores substantially increased the predictive AUCs for in-hospital mortality (AUC: 0.70 to 0.89 for DECAF; 0.71 to 0.89 for BAP-65) and for IMV (AUC: 0.61 to 0.78 for DECAF; 0.69 to 0.81 for BAP-65).

CONCLUSION: CT-derived pectoralis muscle mass and quality are independent and incremental predictors of in-hospital mortality and IMV in AECOPD. Opportunistic muscle assessment from routine chest CT may enhance early risk stratification and inform clinical decision-making.