Computed Tomography-Based Body Composition Assessment for Preoperative Cardiovascular Risk Prediction: A Prospective...

Area of Science:

• Cardiology
• Radiology
• Surgical Risk Assessment

Background:

• Current preoperative cardiovascular risk prediction methods are insufficient.
• CT-derived body composition offers potential objective cardiometabolic health markers.
• The predictive value of these metrics for postoperative cardiovascular events is not well-established.

Purpose of the Study:

• To investigate the predictive value of CT-derived body composition metrics for postoperative cardiovascular events.
• To determine if body composition metrics improve risk prediction beyond established clinical guidelines.

Main Methods:

• Prospective, multicenter study (PREVENGE-CB cohort) including patients undergoing major noncardiac surgery.
• Preoperative CT scans analyzed for skeletal muscle and adipose tissue area and radiodensity.
• Logistic regression used to assess added predictive value of body composition metrics over clinical predictors.

Main Results:

• 1594 patients included; 13.2% experienced primary outcome (30-day cardiovascular events).
• Skeletal muscle area and adipose area associated with lower risk; adipose radiodensity and muscle radiodensity associated with higher risk.
• An optimal subset of three metrics (skeletal muscle area, muscle radiodensity, subcutaneous fat radiodensity) significantly improved prediction over existing risk indices in validation cohorts.

Conclusions:

• CT-derived body composition metrics enhance the prediction of postoperative cardiovascular events.
• These metrics provide valuable information beyond conventional clinical predictors.
• Body composition analysis via CT may refine risk stratification for patients undergoing surgery.