1. Assessment of Computed Tomography (CT)-Defined Muscle and Adipose Tissue Features in Relation to Short-Term Outcomes After Elective Surgery for Colorectal Cancer: A Multicenter Approach
- Author
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Leah Gramlich, Georgios Malietzis, Lisa Martin, Jessica Hopkins, Vickie E. Baracos, Gregg Nelson, Ron Brisebois, Michael B. Sawyer, Anthony MacLean, and John T. Jenkins
- Subjects
Male ,medicine.medical_specialty ,Sarcopenia ,030230 surgery ,Rate ratio ,Logistic regression ,Patient Readmission ,Cohort Studies ,03 medical and health sciences ,0302 clinical medicine ,Postoperative Complications ,Risk Factors ,Internal medicine ,medicine ,Humans ,Muscle, Skeletal ,Survival rate ,Aged ,business.industry ,Odds ratio ,medicine.disease ,Prognosis ,Confidence interval ,Survival Rate ,Oncology ,Adipose Tissue ,Elective Surgical Procedures ,030220 oncology & carcinogenesis ,Cohort ,Body Composition ,Surgery ,Female ,business ,Colorectal Neoplasms ,Tomography, X-Ray Computed ,Cohort study ,Follow-Up Studies - Abstract
Sarcopenia, visceral obesity (VO), and reduced muscle radiodensity (myosteatosis) are suggested risk factors for postoperative morbidity in colorectal cancer (CRC), but usually are not concurrently assessed. Published thresholds used to define these features are not CRC-specific and are defined in relation to mortality, not postoperative outcomes. This study aimed to evaluate body composition in relation to length of hospital stay (LOS) and postoperative outcomes. Pre-surgical computed tomography (CT) images were assessed for total area and radiodensity of skeletal muscle and visceral adipose tissue in a pooled Canadian and UK cohort (n = 2100). Sex- and age-specific values for these features were calculated. For 1139 of 2100 patients, LOS data were available, and sex- and age-specific thresholds for sarcopenia, myosteatosis, and VO were defined on the basis of LOS. Association of CT-defined features with LOS and readmissions was explored using negative binomial and logistic regression models, respectively. In the multivariable analysis, the predictors of LOS (P
- Published
- 2018