• J. Surg. Res. · Sep 2019

    Muscle Mass, Density, and Strength Are Necessary to Diagnose Sarcopenia in Patients With Gastric Cancer.

    • Ji Lin, Weiteng Zhang, Weisheng Chen, Yunshi Huang, Ruisen Wu, Xiaodong Chen, Xian Shen, and Guanbao Zhu.
    • Department of Gastrointestinal Surgery, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China.
    • J. Surg. Res. 2019 Sep 1; 241: 141-148.

    BackgroundAccurate evaluation of muscle strength and function is difficult. Commonly known as sarcopenia, skeletal muscle loss is closely correlated with the prognosis of patients diagnosed with gastric cancer (GC). We wondered the correlation between skeletal muscle measures combined with computed tomography and grip strength (GS) and short-term outcomes after radical gastrectomy (RG) in patients with GC.Materials And MethodsWe analyzed 594 patients with GC who underwent RG. The skeletal muscle index (SMI), skeletal muscle density (Hounsfield unit average calculation [HUAC]), and GS were measured. The skeletal muscle gauge (SMG) was created by multiplying SMI and HUAC. Logistic regression modeling and multivariate analysis were used.ResultsUnivariate analysis showed that low SMI, low HUAC, low GS, and low SMG were predictors of short-term complications after surgery. Compared with other muscle-related factors (AUCHUAC = 0.559, AUCSMI = 0.575, AUCGS = 0.580, AUCSMG = 0.598, AUCSMI+GS = 0.559), low GS plus SMG (AUCGS plus SMG = 0.614, P < 0.01) was a more accurate independent risk factor for postoperative complications. Moreover, the risk model with SMG plus GS for the diagnosis of skeletal muscle loss was superior to the other models (c-index = 0.729).ConclusionsSkeletal muscle measures using computed tomography and GS are closely correlated with short-term outcomes of patients diagnosed with GC after RG. The model contained SMG plus GS could effectively predict for patients with GC after RG at high risk of short-term outcomes. SMG plus GS has the highest accuracy for the several evaluation methods of sarcopenia.Copyright © 2019. Published by Elsevier Inc.

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