Predicted estimates of resting energy expenditure have limited clinical utility in patients with cirrhosis.

BACKGROUND & AIMS: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: Prediction equations do not provide useful estimates of REE in patients with cirrhosis. REE should be directly measured. LAY SUMMARY: 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.

Are Predictive Energy Expenditure Equations Accurate in Cirrhosis?

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.

Insufficient Protein Intake Is Associated With Increased Mortality in 630 Patients With Cirrhosis Awaiting Liver Transplantation.

BACKGROUND: For patients awaiting liver transplantation, we aimed to determine the prevalence and predictors of insufficient protein intake as well as to determine whether very low protein intake was an independent predictor of malnutrition and mortality. MATERIALS AND METHODS: Adults with cirrhosis who were activated on our local liver transplant waiting list between January 2000 and October 2009 were included. Estimated protein intake was derived from dietary records. Patients with incomplete dietary records were excluded. Multivariable logistic regression and competing risk analysis were used. RESULTS: Of 742 potential patients, 112 were excluded due to insufficient data, leaving 630 patients for evaluation. Mean protein intake was 1.0 ± 0.36 g/kg/d and only 24% of patients met the expert consensus recommended threshold of > 1.2 g/kg of protein per day. Very low protein intake (< 0.8 g/kg/d) was associated with worse liver disease severity (as measured by Child-Pugh or MELD). Protein intake below 0.8 g/kg/d was an independent predictor both of malnutrition as measured by the subjective global assessment (adjusted odds ratio [95% confidence interval (CI)]: 2.0 [1.3-3.0]) and of transplant waiting list mortality (adjusted hazard ratio [95% CI]: 1.8 [1.2-2.7]). CONCLUSION: In this large cohort of liver transplant waitlisted patients, very low protein intake was prevalent and independently associated with malnutrition and mortality. Unlike many other prognostic factors, protein intake is potentially modifiable. Prospective studies are warranted to evaluate the effect of targeted protein repletion on clinically relevant outcomes such as muscle mass, muscle function, immune function, and mortality.