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Background <p>This study aimed to determine whether the cross-sectional area of subcutaneous adipose tissue (SAT) at the 12th thoracic vertebra (T12) vertebral level on routine preoperative chest CT is associated with post-transplant outcomes.</p> Methods <p>We retrospectively analyzed lung transplant recipients who underwent routine pretransplant chest CT imaging. The SAT area at the T12 level, which serves as a reliable and consistently visible surrogate for whole-body adiposity on routine chest CT, was measured on axial CT slices using standardized tissue attenuation thresholds. Primary outcome was a 1-year composite of all-cause mortality, chronic lung allograft dysfunction and severe infections requiring hospitalization. Secondary outcomes included length of stay, ventilator support, grade III primary graft dysfunction and acute rejection. Associations between T12 SAT and outcomes were evaluated using univariable and multivariable Cox regression models to identify predictors. To assess the incremental predictive value of SAT, we compared nested prediction models that combined SAT with clinical variables. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI).</p> Results <p>Of 280 patients, 29 (10.4%) experienced the primary composite outcome, and 75 (26.8%) developed secondary outcomes. Kaplan–Meier analysis showed worse survival in recipients with SAT area above the optimal cutoff of 30.05&#xa0;cm² (log-rank <i>P</i> &lt; 0.01), and SAT area remained an independent predictor of the primary outcome. Adding SAT and SAT<sub>BMI</sub> to the baseline model improved discrimination for the primary outcome, with AUC increasing from 0.65(95%CI:0.43–0.85) to 0.75(95%CI:0.63–0.85), with sensitivity of 76% and specificity of 62% (NRI = 0.83, <i>P</i> &lt; 0.01). For secondary outcomes, adding SAT<sub>BMI</sub> increased the AUC from 0.60(95%CI:0.33–0.86) to 0.85(95%CI:0.71–0.97), with sensitivity of 81% and specificity of 88% (NRI = 0.39, <i>P</i> = 0.01).</p> Conclusions <p>Preoperative SAT quantification at the T12 level may serve as a useful imaging marker for predicting adverse outcomes in lung transplant recipients, potentially improving risk stratification.</p>

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The prognostic role of preoperative subcutaneous adipose tissue measurement in lung transplantation

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月20日

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  • Shuangxiang Lin,
  • Fei Zeng,
  • Peipei Gu,
  • Xiaodan Feng,
  • Jiani Shi,
  • Meijuan Lan,
  • Xinhong Wang

摘要

Background

This study aimed to determine whether the cross-sectional area of subcutaneous adipose tissue (SAT) at the 12th thoracic vertebra (T12) vertebral level on routine preoperative chest CT is associated with post-transplant outcomes.

Methods

We retrospectively analyzed lung transplant recipients who underwent routine pretransplant chest CT imaging. The SAT area at the T12 level, which serves as a reliable and consistently visible surrogate for whole-body adiposity on routine chest CT, was measured on axial CT slices using standardized tissue attenuation thresholds. Primary outcome was a 1-year composite of all-cause mortality, chronic lung allograft dysfunction and severe infections requiring hospitalization. Secondary outcomes included length of stay, ventilator support, grade III primary graft dysfunction and acute rejection. Associations between T12 SAT and outcomes were evaluated using univariable and multivariable Cox regression models to identify predictors. To assess the incremental predictive value of SAT, we compared nested prediction models that combined SAT with clinical variables. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI).

Results

Of 280 patients, 29 (10.4%) experienced the primary composite outcome, and 75 (26.8%) developed secondary outcomes. Kaplan–Meier analysis showed worse survival in recipients with SAT area above the optimal cutoff of 30.05 cm² (log-rank P < 0.01), and SAT area remained an independent predictor of the primary outcome. Adding SAT and SATBMI to the baseline model improved discrimination for the primary outcome, with AUC increasing from 0.65(95%CI:0.43–0.85) to 0.75(95%CI:0.63–0.85), with sensitivity of 76% and specificity of 62% (NRI = 0.83, P < 0.01). For secondary outcomes, adding SATBMI increased the AUC from 0.60(95%CI:0.33–0.86) to 0.85(95%CI:0.71–0.97), with sensitivity of 81% and specificity of 88% (NRI = 0.39, P = 0.01).

Conclusions

Preoperative SAT quantification at the T12 level may serve as a useful imaging marker for predicting adverse outcomes in lung transplant recipients, potentially improving risk stratification.