Clinical transplantation · 2026
Alternative Measures of Body Composition and Outcomes Following Heart Transplant.
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Lanier Ana, Siddiqi Umar, Siddiqi Usmaan, Lee Linda, Saffari Seyed Ehsan, Belkin Mark, Grinstein Jonathan, Kanelidis Anthony, Gozdecki Leo, Swat Stanley, Kalantari Sara, Sarswat Nitasha, Chung Bow Ben, Kim Gene, Salerno Chris, Jeevanandam Valluvan, Kanwar Manreet, Nguyen Ann
Аннотация
Current guidelines for heart transplant (HT) listing support body mass index (BMI) < 35 kg/m2, though data supporting this recommendation is mixed. It is unclear if other more specific measurements of body composition are better predictors of outcomes post-HT. This retrospective study included patients who underwent HT between 2014 and 2019 and underwent an abdominal CT scan within 3 months of HT. Tissue characterization was performed using Slice-O-Matic software to derive measurements including BMI, fat mass index (FMI), visceral adipose tissue to subcutaneous adipose tissue ratio (VAT/SAT), fat free mass index (FFMI), and skeletal muscle index (SMI). Univariate and multivariate logistic regression analyses were used to investigate association of body composition variables by tertiles to 1 year mortality, readmission, primary graft dysfunction, length of stay, infection, and renal failure. Of the 104 patients, 80% were male and 56% were Caucasian. Highest and lowest BMI tertiles were significantly associated with an increased risk of hospital readmission within 1 year post HT (OR 3.4, [95%CI 1.1-11.4]; OR 5.9, [95% CI 1.7-25.1]; p = 0.01) as well as an increased risk of infections requiring hospitalization (OR 3.2, [95% CI 1.2-9.0]; OR 3.9, [95%CI 1.4-11.7]; p = 0.02). FMI, VAT/SAT, FFMI, and SMI were not associated with outcomes 1-year post-HT. Highest and lowest BMI tertiles were associated with increased rates of hospital readmission and infection in the first-year post HT, while other measurements of body composition were not associated with any poor outcomes post-HT. Although BMI does not predict mortality post-HT, it can differentiate risk better than all other metrics.