Computed Tomography-Based Body Composition Metrics as a Predictor of Textbook Outcome in Lung Transplant Patients

Lung transplantation is a complex therapy for end stage lung disease with variable postoperative outcomes. Textbook outcomes, defined by freedom from perioperative morbidity and mortality, have emerged as a comprehensive measure of surgical success. Body mass index (BMI) is commonly used to assess nutritional status but does not distinguish between skeletal muscle and adipose tissue. CT-based body composition analysis can differentiate these tissues and may provide a more precise assessment of physiologic reserve in lung transplantation.

We performed a retrospective cohort study of 377 adults undergoing single or bilateral lung transplantation at a single academic institution (2019-2023). Preoperative abdominal CT scans were used to quantify skeletal muscle, subcutaneous fat, and visceral fat areas. A composite textbook outcome was defined as freedom from intraoperative complications; postoperative reintervention; readmission, acute rejection, and dialysis within 30 days; 90-day mortality; primary graft dysfunction; ECMO at 72 h; tracheostomy within 7 days; reintubation; and extubation >48 h. Multivariable logistic regression assessed associations between body composition metrics and lung transplant outcomes after adjusting for potential confounders.

Among 377 recipients, 108 (28.6%) achieved textbook outcome. Increased skeletal muscle area was associated with increased odds of achieving textbook outcome (OR per 50cm²: 1.808 [1.061-3.119]) and decreased odds of 1-year mortality (OR per 50cm²: 0.423 [0.195-0.890]). Subcutaneous fat area, visceral fat area, and BMI were not significantly associated with outcomes.

CT-based skeletal muscle was associated with textbook outcome and 1-year mortality, whereas BMI was not. CT-based body composition analysis may be a promising tool for lung transplant risk stratification.