Sarcopenia, defined as a decrease in skeletal muscle mass and strength, is an important risk factor in clinical medicine associated with frailty, mortality, and worse surgical and nonsurgical outcomes. Conventional measures of sarcopenia rely on the subjective “eyeball test” and do not adequately describe risk. Computed tomography (CT) imaging studies may be used to objectively measure sarcopenia and may be used for surgical risk stratification and identification of patients for inclusion in a novel clinical remediation program.Methods:
We describe results observed in the general, vascular, and liver transplant surgery populations determined by analytic morphomics—an analysis of CT scans in a semiautomated process using MATLAB v13.0. A perioperative optimization program has been implemented with the objective of remediating sarcopenia through improvement of patient mental and physical status prior to surgery.Results:
Using analytic morphomics, we have noted significantly higher cost and increased rates of mortality and surgical complications among sarcopenic patients. The training program shows initial success, and among participating patients, we have observed reductions in payer and hospital costs and a decrease in length of hospital stay for patients following surgery.Conclusions:
Through analytic morphomics, we are able to quantify markers of sarcopenia and identify patients at risk for increased mortality and poor surgical outcomes. Early identification of patients offers us the opportunity to remediate sarcopenia through perioperative training and support. Participating patients spend less time in the hospital and have lower healthcare costs. This program has the potential to improve the perioperative patient experience and ease financial burdens.