Computed tomography-derived body composition parameters as potential predictors of severity and adverse outcomes in viral pneumonia: a retrospective study.

Background: Following the COVID-19 pandemic, co-infections with multiple respiratory viruses have become increasingly common, complicating the accurate prediction of disease progression and prognosis. This study assessed the use of computed tomography (CT)-derived body composition parameters combined with clinical risk factors to predict the severity and short-term adverse outcomes of viral pneumonia. Methods: A total of 140 hospitalized patients with viral pneumonia who had undergone chest CT were retrospectively included and stratified into severe and non-severe groups. Body composition, including visceral and subcutaneous adipose volumes (VAV and SAV) and erector spinae volume (ESV), was measured at T4, T8, and T12 costovertebral joint levels and the corresponding whole-vertebral level using 3D-Slicer. Serological indicators and 30-day adverse outcomes were recorded. Clinical, imaging, and integrated models were developed to distinguish patients' severity and outcome. Results: The median age was 77 years (IQR: 68-85), with 91 (65%) patients being male. Sixty-five (46.4%) patients were severe patients and 26 (18.6%) had adverse outcomes within 30 days. Lower T12-ESV and higher T12-VAV were associated with viral pneumonia severity after adjusting for confounders ( Conclusion: Decreased ESV and increased VAV at T12 level are independent predictors of severe viral pneumonia, while reduced SAV correlates well with adverse 30-day outcomes. CT-derived body composition parameters can predict the progression and short-term prognosis of viral pneumonia, thereby aiding clinical decision-making.