Analytic morphomics, core muscle size, and surgical outcomes.

OBJECTIVE: Assess the relationship between lean core muscle size, measured on preoperative cross-sectional images, and surgical outcomes. BACKGROUND: Novel measures of preoperative risk are needed. Analytic morphomic analysis of cross-sectional diagnostic images may elucidate vast amounts of patient-specific data, which are never assessed by clinicians. METHODS: The study population included all patients within the Michigan Surgical Quality Collaborative database with a computerized tomography(CT) scan before major, elective general or vascular surgery (N = 1453). The lean core muscle size was calculated using analytic morphomic techniques. The primary outcome measure was survival, whereas secondary outcomes included surgical complications and costs. Covariate adjusted outcomes were assessed using Kaplan-Meier analysis, multivariate cox regression, multivariate logistic regression, and generalized estimating equation methods. RESULTS: The mean follow-up was 2.3 years and 214 patients died during the observation period. The covariate-adjusted hazard ratio for lean core muscle area was 1.45 (P = 0.028), indicating that mortality increased by 45% per 1000 mm(2) decrease in lean core muscle area. When stratified into tertiles of core muscle size, the 1-year survival was 87% versus 95% for the smallest versus largest tertile, whereas the 3-year survival was 75% versus 91%, respectively (P < 0.003 for both comparisons). The estimated average risk of complications significantly differed and was 20.9%, 15.0%, and 12.3% in the lower, middle, and upper tertiles of lean core muscle area, respectively. Covariate-adjusted cost increased significantly by an estimated $10,110 per 1000 mm(2) decrease in core muscle size (P = 0.003). CONCLUSIONS: Core muscle size is an independent and potentially important preoperative risk factor. The techniques used to assess preoperative CT scans, namely analytic morphomics, may represent a novel approach to better understanding patient risk.

Duke Scholars

Author Jay S Lee Surgical Oncology