2021
DOI: 10.1002/jcsm.12771
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Sarcopenia and major complications in patients undergoing oncologic colon surgery

Abstract: Background Sarcopenia is a surrogate marker for malnutrition and frailty, which has been linked to higher complication rates and prolonged length of stay (LOS) after surgery. The study aim was to assess the correlation between computed tomography (CT)‐based sarcopenia and short‐term clinical outcomes after oncologic colon surgery. Methods This retrospective study included consecutive patients operated between May 2014 and December 2019. Three radiological indices of sarcopenia were measured at the level of the… Show more

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Cited by 22 publications
(14 citation statements)
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“…This could explain the fact that there was no difference in SMRA and IMAT between the two groups compared in this study. A hypothesis could be that the quantity and the quality of the muscle do not necessarily match, as already suggested by other studies [ 31 , 41 , 42 ]. These results contrasted with findings from a recent meta-analysis, where various CT-based sarcopenia indices were evaluated as predictors for the risk of major complications in patients undergoing hepato-pancreato-biliary surgery [ 43 ].…”
Section: Discussionmentioning
confidence: 90%
See 1 more Smart Citation
“…This could explain the fact that there was no difference in SMRA and IMAT between the two groups compared in this study. A hypothesis could be that the quantity and the quality of the muscle do not necessarily match, as already suggested by other studies [ 31 , 41 , 42 ]. These results contrasted with findings from a recent meta-analysis, where various CT-based sarcopenia indices were evaluated as predictors for the risk of major complications in patients undergoing hepato-pancreato-biliary surgery [ 43 ].…”
Section: Discussionmentioning
confidence: 90%
“…Other data acquisition and image reconstruction parameters varied slightly between patients, inherent to the study design and patient referral for liver surgery. Muscle mass and quality were measured on axial CT slices at the mid-pedicle level of the third lumbar vertebra using a semi-automated, deep-learning-based method with a U-Net architecture algorithm [ 29 , 30 , 31 ]. Similar methods have recently been validated on large data sets [ 32 , 33 ].…”
Section: Methodsmentioning
confidence: 99%
“…The present study confirms these findings, given the very low prevalence of about 4% when using this composite clinical screening tool, which may lead to the underdetection of patients at risk. The assessment of body composition through anthropometric measures may be more accurate and indispensable in this setting [ 18 , 19 ]. Furthermore, validated official nutritional screening tools such as the Nutritional Risk Score (NRS-2002), the Malnutrition Universal Screening Tool (MUST) or (GLIM) need to be considered, together with dedicated assessment by nutritional specialists [ 12 , 20 , 21 ].…”
Section: Discussionmentioning
confidence: 99%
“…These methods have been tested and validated on large CT datasets and are proven to be accurate and reliable. 28 , 29 All automated muscle segmentations were secondarily reviewed and corrected by an attending musculoskeletal radiologist (FB), blinded to the patient’s intervention (as the radiologist had at disposal the unique cross-sectional picture at the L3–L4 level extracted for each patient), using a custom free-hand image segmentation tool.…”
Section: Methodsmentioning
confidence: 99%