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

ABSTRACT Background 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. Methods 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. Results Among 377 recipients, 108 (28.6%) achieved textbook outcome. Increased skeletal muscle area was associated with increased odds of achieving textbook outcome (OR per 50cm 2 : 1.808 [1.061–3.119]) and decreased odds of 1‐year mortality (OR per 50cm 2 : 0.423 [0.195–0.890]). Subcutaneous fat area, visceral fat area, and BMI were not significantly associated with outcomes. Conclusion 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.