Sarcopenia predicts mortality and adverse outcomes after endovascular aneurysm repair and can be used to risk stratify patients.

BACKGROUND

Endovascular aneurysm repair (EVAR) is currently the most common treatment of abdominal aortic aneurysms. Potential predictors of long-term survival after EVAR include physiologic, functional, and cognitive status, but assessments of these conditions have been difficult to standardize. Objective radiographic findings, such as skeletal muscle atrophy, or sarcopenia, may provide an additional means for selection of patients. This study investigates sarcopenia as a method to predict 1-year survival in patients undergoing EVAR.

METHODS

A single-institution retrospective review was conducted of all patients who underwent elective EVAR from September 2002 to June 2014. Patients with an available periprocedural computed tomography (CT) scan and clinical data were included in the analysis. Normalized total psoas cross-sectional area (nTPA) was measured on axial CT images using the area of the bilateral psoas muscle at the third lumbar vertebral level normalized to the square of patient height. A threshold for optimal estimate of sarcopenia based on nTPA was determined using a receiver operating characteristic curve. Sarcopenia was evaluated as an independent risk predictor using univariate, multivariate, and survival analysis.

RESULTS

A total of 272 EVAR-treated patients were evaluated, including 237 men and 35 women with a median age of 72 years and mean body mass index of 28.6 kg/m. There was a significant increase in overall mortality in patients in the lowest quartile of nTPA (Q1, 23.53%; Q2, 13.24%; Q3, 7.35%; Q4, 5.88%; P = .01). The estimated nTPA threshold for increased mortality after EVAR was 500 mm/m. Using this threshold, sarcopenia accounted for 57% of the risk effect in our 1-year survival model.

CONCLUSIONS

Sarcopenia can assist in identifying EVAR candidates who are less likely to benefit from surgery. It can be readily evaluated from preoperative CT scans and may be a useful tool in evaluation of abdominal aortic aneurysm patients with applications in risk evaluation and telemedicine.