Malnutrition is associated with adverse clinical outcomes in patients with cirrhosis. Accurate assessment of energy requirements is needed to optimize dietary intake. Resting energy expenditure (REE), the major component of total energy expenditure, can be measured using indirect calorimetry (mREE) or estimated using prediction equations (pREE). This study assessed the usefulness of predicted estimates of REE in this patient population. Individual mREE data were available for 900 patients with cirrhosis (mean [±1 SD] age 55.7±11.6 years-old; 70% men; 52% south-east Asian) and 282 healthy controls (mean age 36.0±12.8 years-old; 52% men; 18% south-east Asian). Metabolic status was classified using thresholds based on the mean ± 1 SD of the mREE in the healthy controls. Comparisons were made between mREE and pREE estimates obtained using the Harris-Benedict, Mifflin, Schofield and Henry equations. Stepwise regression was used to build 3 new prediction models which included sex, ethnicity, body composition measures, and model for end-stage liver disease scores. The mean mREE was significantly higher in patients than controls when referenced to dry body weight (22.4±3.8 cf. 20.8±2.6 kcal/kg/24 hr; p <0.001); there were no significant sex differences. The mean mREE was significantly higher in Caucasian than Asian patients (23.1±4.4 cf. 21.7±2.9 kcal/kg/24 hr; p <0.001). Overall, 37.1% of Caucasian and 25.3% of Asian patients were classified as hypermetabolic. The differences between mREE and pREE were both statistically and clinically relevant; in the total patient population, pREE estimates ranged from 501 kcal/24 hr less to 548 kcal/24 hr more than the mREE. Newly derived prediction equations provided better estimates of mREE but still had limited clinical utility. Prediction equations do not provide useful estimates of REE in patients with cirrhosis. REE should be directly measured. People with cirrhosis are often malnourished and this has a detrimental effect on outcome. Provision of an adequate diet is very important and is best achieved by measuring daily energy requirements and adjusting dietary intake accordingly. Prediction equations, which use information on age, sex, weight, and height can be used to estimate energy requirements; however, the results they provide are not accurate enough for clinical use, particularly as they vary according to sex and ethnicity.
Read full abstract