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Objectives <p>This study aimed to develop a risk prediction model for mortality and unplanned readmission incorporating preoperative CT-based assessments of muscle and bone status in patients undergoing cardiac surgery.</p> Methods <p>This single-center retrospective study included consecutive patients aged ≥ 65&#xa0;years who underwent cardiac surgery between November 2016 and August 2023 (n = 221). The primary endpoint was a composite of all-cause mortality and unplanned readmission within 2&#xa0;years after discharge. Psoas muscle index (PMI), psoas muscle density (PMD), and bone mineral density (BMD) on preoperative CT images were used as indicators of skeletal muscle and bone status. Predictors were identified using Cox proportional hazards analyses. A risk score was created from regression coefficients and internally validated with 1,000 bootstrap samples.</p> Results <p>Of 221 eligible patients, 184 were included. The primary endpoint occurred in 43 patients (23.4%). Multivariable analysis identified chronic kidney disease (hazard ratio [HR] 2.69; 95% confidence interval [CI] 1.18–6.16), PMD (HR 0.93; 95% CI 0.89–0.97), and BMD (HR 0.99; 95% CI 0.98–0.99) as independent predictors. Based on regression coefficients, a risk score was assigned: 1 point for chronic kidney disease, 1 point for low PMD, and 1 point for low BMD, totalling 3 points. Internal validation demonstrated good discriminative ability, with an area under the receiver operating characteristic curve of 0.82, and good calibration, with a Hosmer–Lemeshow goodness-of-fit test <i>p</i> = 0.365.</p> Conclusions <p>The risk model using these three factors demonstrated good discrimination and calibration, suggesting potential utility for early preoperative risk stratification.</p>

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A risk prediction model using preoperative CT-based muscle and bone status for mortality and readmission after cardiac surgery in older patients

  • 期刊论文

  • 发表日期：

    2026年3月31日

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  • Hirokazu Sugiura,
  • Masahiro Takahashi,
  • Junichi Sakata,
  • Yosuke Yanase,
  • Yuka Matsuda,
  • Masanori Nakamura

摘要

Objectives

This study aimed to develop a risk prediction model for mortality and unplanned readmission incorporating preoperative CT-based assessments of muscle and bone status in patients undergoing cardiac surgery.

Methods

This single-center retrospective study included consecutive patients aged ≥ 65 years who underwent cardiac surgery between November 2016 and August 2023 (n = 221). The primary endpoint was a composite of all-cause mortality and unplanned readmission within 2 years after discharge. Psoas muscle index (PMI), psoas muscle density (PMD), and bone mineral density (BMD) on preoperative CT images were used as indicators of skeletal muscle and bone status. Predictors were identified using Cox proportional hazards analyses. A risk score was created from regression coefficients and internally validated with 1,000 bootstrap samples.

Results

Of 221 eligible patients, 184 were included. The primary endpoint occurred in 43 patients (23.4%). Multivariable analysis identified chronic kidney disease (hazard ratio [HR] 2.69; 95% confidence interval [CI] 1.18–6.16), PMD (HR 0.93; 95% CI 0.89–0.97), and BMD (HR 0.99; 95% CI 0.98–0.99) as independent predictors. Based on regression coefficients, a risk score was assigned: 1 point for chronic kidney disease, 1 point for low PMD, and 1 point for low BMD, totalling 3 points. Internal validation demonstrated good discriminative ability, with an area under the receiver operating characteristic curve of 0.82, and good calibration, with a Hosmer–Lemeshow goodness-of-fit test p = 0.365.

Conclusions

The risk model using these three factors demonstrated good discrimination and calibration, suggesting potential utility for early preoperative risk stratification.