Are Predictive Energy Expenditure Equations Accurate in Cirrhosis?

Nutrients. 2019 Feb 4;11(2):334. doi: 10.3390/nu11020334.

Abstract

Malnutrition is associated with significant morbidity and mortality in cirrhosis. An accurate nutrition prescription is an essential component of care, often estimated using time-efficient predictive equations. Our aim was to compare resting energy expenditure (REE) estimated using predictive equations (predicted REE, pREE) versus REE measured using gold-standard, indirect calorimetry (IC) (measured REE, mREE). We included full-text English language studies in adults with cirrhosis comparing pREE versus mREE. The mean differences across studies were pooled with RevMan 5.3 software. A total of 17 studies (1883 patients) were analyzed. The pooled cohort was comprised of 65% men with a mean age of 53 ± 7 years. Only 45% of predictive equations estimated energy requirements to within 90⁻110% of mREE using IC. Eighty-three percent of predictive equations underestimated and 28% overestimated energy needs by ±10%. When pooled, the mean difference between the mREE and pREE was lowest for the Harris⁻Benedict equation, with an underestimation of 54 (95% CI: 30⁻137) kcal/d. The pooled analysis was associated with significant heterogeneity (I2 = 94%). In conclusion, predictive equations calculating REE have limited accuracy in patients with cirrhosis, most commonly underestimating energy requirements and are associated with wide variations in individual comparative data.

Keywords: cirrhosis; indirect calorimetry; predictive equations; resting energy expenditure.

Publication types

  • Comparative Study
  • Review

MeSH terms

  • Basal Metabolism
  • Calorimetry, Indirect / statistics & numerical data*
  • Cohort Studies
  • Energy Metabolism*
  • Female
  • Humans
  • Liver Cirrhosis / complications
  • Liver Cirrhosis / metabolism
  • Male
  • Malnutrition / diagnosis
  • Malnutrition / etiology
  • Malnutrition / metabolism*
  • Middle Aged
  • Nutrition Assessment*
  • Nutritional Requirements
  • Nutritional Status
  • Predictive Value of Tests