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The TPA score (total psoas muscle area) is the best marker for preoperative measurement of pre-sarcopenia in pancreatic surgery. | LitMetric

Introduction: Pre-sarcopenia, defined by the loss of muscle mass, is significantly associated with an increased risk of postoperative complications in digestive surgery, particularly pancreatic resection. The five predominant markers of sarcopenia are: psoas muscle area (TPA), intramuscular adipose tissue content (IMAC), Average Hounsfield Unit Calculation (HUAC), Skeletal Muscle Mass Index (MMI), and the ratio between visceral adipose tissue area and muscle surface area (VFA/TAMA). No standard reference marker has been determined.

Material And Methods: This retrospective cohort included patients who underwent pancreatic resection at the University Hospital of Angers between January 2008 and June 2017. The goal was to determine the marker that was most significantly associated with morbidity and mortality in pancreatic surgery. The secondary objective was to determine the characteristics of pre-sarcopenic patients.

Results: The TPA score is the most sensitive marker for identifying patients at highest risk for immediate complications (P=0.008), proving far more sensitive than MMI (P=0.02), HUAC (P=0.34), IMAC (P=1), or VFA/TAMA (P=0.42). Postoperative mortality was 3.3% (n=5), morbidity was 63.8% (n=97). Pre-sarcopenic patients, as identified by the TPA index had significantly more immediate complications (71.2% versus 49.5%, P=0.008), in particular, more gastroparesis (P=0.02) and pancreatic fistula (P=0.03).

Conclusion: In patients requiring pancreatic surgery, the prevalence of pre-sarcopenia is high and seems to be associated with a greater risk of immediate postoperative complications. The TPA score seems to be the most sensitive marker for detecting pre-sarcopenia. Evaluation of TPA preoperatively would make it possible to identify priority patients a priori who might benefit from pre-habilitation programs.

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http://dx.doi.org/10.1016/j.jviscsurg.2022.05.009DOI Listing

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