Effects of Abdominal Fat Distribution Parameters on Severity of Acute Pancreatitis

O'Leary, D.; O'Neill, D.; McLaughlin, P.; O'Neill, S.; Myers, E.; Maher, M.; Redmond, H.
July 2012
World Journal of Surgery;Jul2012, Vol. 36 Issue 7, p1679
Academic Journal
Background: Obesity is a well-established risk factor for acute pancreatitis. Increased visceral fat has been shown to exacerbate the pro-inflammatory milieu experienced by patients. This study aimed to investigate the relationship between the severity of acute pancreatitis and abdominal fat distribution parameters measured on computed tomography (CT) scan. Methods: Consecutive patients admitted to Cork University Hospital with acute pancreatitis between January 2005 and December 2010 were evaluated for inclusion in the study. An open source image analysis software (Osirix, v 3.9) was used to calculate individual abdominal fat distribution parameters from CT scans by segmentation of abdominal tissues. Results: A total of 214 patients were admitted with pancreatitis between January 2005 and December 2010. Sixty-two of these patients underwent a CT scan and were thus eligible for inclusion. Visceral fat volume was the volumetric fat parameter that had the most significant association with severe acute pancreatitis ( P = 0.003). There was a significant association between visceral fat volume and subsequent development of systemic complications of severe acute pancreatitis ( P = 0.003). There was a strong association between mortality and visceral fat volume ( P = 0.019). Multivariate regression analysis, adjusted for gender, did not identify any individual abdominal fat distribution index as an independent risk factor for severe acute pancreatitis. Conclusions: Overall, estimation of abdominal fat distribution parameters from CT scans performed on patients with acute pancreatitis indicates a strong association between visceral fat, severe acute pancreatitis, and the subsequent development of systemic complications. These data suggest that visceral fat volume should be incorporated into future predictive scoring systems.


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