Resting energy expenditure in patients with liver cirrhosis: Indirect calorimetry vs. predictive equations.

Abstract

Background and objectives: The objective of our study was to explore the accuracy of previously published prediction equations in predicting resting energy expenditure (REE) in patients with liver cirrhosis (LC). We also aimed to develop a novel equation to estimate REE for Chinese patients with LC.

Methods and study design: In 90 patients with LC, the agreement between REE measured by Indirect calorimetry (IC) and predictive equations was quantified using paired T-test and visualized using a Bland-Altman Plot. Pearson correlation coefficient (R) was used to measure a linear correlation between REE measured by IC and different predictive equations. Stepwise multiple regression analysis was used to create a new REE equation.

Results: The estimated REEs of previous equations were underestimated against REE measured by IC (1610 ± 334 kcal). Lean body mass (LBM) was positively correlated with REE measured by IC (r = 0.723, p < 0.01). The newly derived estimation equation for REE (kcal) was 1274.3 - 209.0 * sex - 5.73 * age + 3.69 * waist circumference + 22.89 * LBM. The newly derived estimation equation was found to have a Pearson-r value of 0.765 compared with REE measured by IC.

Conclusions: REE in liver cirrhosis was underestimated by using predictive equations. The new predictive equation developed by using age, sex, waist circumference, and LBM may help estimate REE in Chinese patients with LC accurately and easily.