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. 2015 May;111(6):771-5.
doi: 10.1002/jso.23862. Epub 2014 Dec 29.

Sarcopenia is an independent predictor of complications following pancreatectomy for adenocarcinoma

Affiliations

Sarcopenia is an independent predictor of complications following pancreatectomy for adenocarcinoma

Savita Joglekar et al. J Surg Oncol. 2015 May.

Abstract

Background and objectives: Sarcopenia, which is subclinical loss of skeletal muscle mass, is commonly observed in patients with malignancy. The objective of this study is to determine the correlation between sarcopenia and operative complications following pancreatectomy for cancer.

Methods: A retrospective review of a pancreatectomy database was performed. The Hounsfield Unit Average Calculation (HUAC) of the psoas muscle, a marker of muscle density and fatty infiltration, was measured from preoperative CT scans. Complications were graded and multivariate logistic regression analysis was performed.

Results: One hundred eighteen patients met criteria for analysis; the overall morbidity rate was 78.8% (n = 93). There were 31 (26.3%) patients who met criteria for sarcopenia using the HUAC. When analyzed as a continuous variable, sarcopenia was an independent predictor of major grade III complications, length of stay, intensive care unit admission, delayed gastric emptying, and infectious, gastrointestinal, pulmonary, and cardiac complications.

Conclusions: These data suggest that sarcopenia as measured with the HUAC, a value that can be obtained from a preoperative CT scan, is a significant independent predictor of surgical outcome and can be used to improve patient selection and informed consent prior to pancreatectomy in patients with cancer.

Keywords: complications; pancreatectomy; pancreatic cancer; sarcopenia.

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Figures

Fig. 1
Fig. 1
Gender-specific distribution of BMI and sarcopenia endpoints in patients with resected pancreatic ductal adenocarcinoma. Note that the Hounsfield Unit Average Calculation correlated more with BMI distribution than with that of the Total Psoas Index.

Comment in

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