Identification of “Digital Sarcopenia” Can Aid the Detection of Pancreatic Exocrine Insufficiency and Malnutrition Assessment in Patients with Suspected Pancreatic Pathology

Abstract

Background: Pancreatic exocrine insufficiency (PEI) and subsequent malnutrition can be difficult to diagnose but lead to sarcopenia and increased mortality and morbidity even in benign disease. Digital skeletal muscle analysis has been increasingly recognised as a tool to diagnose sarcopenia. Objective: The aim of the study was to assess the prevalence of sarcopenia in patients with PEI secondary to benign disease using novel skeletal muscle recognition software. Methods: Prospective recruitment of patients referred for endoscopic ultrasound (EUS) with suspected pancreatic pathology. Patients with suspected pancreatic cancer on initial computed tomography (CT) were excluded. The diagnosis of chronic pancreatitis (CP) was based on CT and EUS findings. PEI was assessed with faecal elastase-1. Digital measurement of skeletal muscle mass identified sarcopenia, with demographic and comorbidity data also collected. Results: PEI was identified in 45.1% (46/102) of patients recruited, and 29.4% (30/102) had changes of CP. Sarcopenia was significantly more prevalent in PEI 67.4% (31/46) than no-PEI 37.5% (21/56) (37.5%), regardless of CP changes (p < 0.003). The prevalence of sarcopenia (67% vs. 35%; p = 0.02) and sarcopenic obesity (68.4% vs. 25%; p = 0.003) was significantly higher when PEI was present without a radiological diagnosis of CP. Multivariate analysis identified sarcopenia and diabetes to be independently associated with PEI (odds ratio 4.8 and 13.8, respectively, p < 0.05). Conclusion: Sarcopenia was strongly associated with PEI in patients undergoing assessment for suspected benign pancreatic pathology. Digital skeletal muscle assessment can be used as a tool to aid identification of sarcopenia in patients undergoing CT scan for pancreatic symptoms.