Development of an opportunistic chest CT-based nomogram for identifying low muscle mass in hospitalized patients with...

Low muscle mass is common in patients with chronic obstructive pulmonary disease (COPD) and is associated with adverse clinical outcomes, yet its recognition in routine inpatient care remains limited. We aimed to develop a practical model for identifying hospitalized patients with COPD who were likely to have computed tomography (CT)-defined low muscle mass using routinely available clinical variables and opportunistic chest CT-derived skeletal muscle density (SMD).

This retrospective single-center study included 265 consecutively hospitalized patients with COPD. Low muscle mass was defined according to sex-specific mean T12 skeletal muscle index (SMI) values derived from the study cohort. Candidate variables were screened using least absolute shrinkage and selection operator (LASSO) regression, and independent factors associated with low muscle mass were identified using multivariable logistic regression. A nomogram was then developed to estimate the probability of low muscle mass. Model performance was assessed by discrimination, calibration, and decision curve analysis (DCA). Internal validation was performed using bootstrap resampling.

The mean age of the cohort was 70.52 years, and 67.6% of patients were male. Five variables were independently associated with low muscle mass: older age, lower body mass index (BMI), higher blood urea nitrogen-to-creatinine ratio (BUN/Cr), lower forced expiratory volume in the first second/forced vital capacity (FEV1/FVC), and lower SMD. The nomogram incorporating these variables showed good discrimination, with an area under the receiver operating characteristic curve (AUC) of 0.823. Calibration analysis showed good agreement between predicted and observed probabilities, and DCA suggested potential net benefit across a clinically relevant range of threshold probabilities.

In this retrospective cohort of hospitalized patients with COPD, a nomogram integrating routine clinical variables and opportunistic chest CT-derived SMD showed promising performance for identifying CT-defined low muscle mass. The model may support early risk stratification and help identify patients who warrant further nutritional, functional, or rehabilitation assessment. External validation is required before clinical implementation.