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Preoperative Body Composition Measured by Bioelectrical Impedance Analysis Can Predict Pancreatic Fistula After Pancreatic Surgery

Overview
Journal Nutr Clin Pract
Publisher Wiley
Date 2024 Jul 16
PMID 39010727
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Abstract

Background: Postoperative pancreatic fistula (POPF) remains one of the most severe complications after pancreatic surgery. The methods for predicting pancreatic fistula are limited. We aimed to investigate the predictive value of body composition parameters measured by preoperative bioelectrical impedance analysis (BIA) on the development of POPF.

Methods: A total of 168 consecutive patients undergoing pancreatic surgery from March 2022 to December 2022 at our institution were included in the study and randomly assigned at a 3:2 ratio to the training group and the validation group. All data, including previously reported risk factors for POPF and parameters measured by BIA, were collected. Risk factors were analyzed by univariable and multivariable logistic regression analysis. A prediction model was established to predict the development of POPF based on these parameters.

Results: POPF occurred in 41 of 168 (24.4%) patients. In the training group of 101 enrolled patients, visceral fat area (VFA) (odds ratio [OR] = 1.077, P = 0.001) and fat mass index (FMI) (OR = 0.628, P = 0.027) were found to be independently associated with POPF according to multivariable analysis. A prediction model including VFA and FMI was established to predict the development of POPF with an area under the receiver operating characteristic curve (AUC) of 0.753. The efficacy of the prediction model was also confirmed in the internal validation group (AUC 0.785, 95% CI 0.659-0.911).

Conclusions: Preoperative assessment of body fat distribution by BIA can predict the risk of POPF after pancreatic surgery.

Citing Articles

Preoperative body composition measured by bioelectrical impedance analysis can predict pancreatic fistula after pancreatic surgery.

Jin Q, Zhang J, Jin J, Zhang J, Fei S, Liu Y Nutr Clin Pract. 2024; 40(1):156-166.

PMID: 39010727 PMC: 11713216. DOI: 10.1002/ncp.11192.

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