Dietary Composition Independent of Weight Loss in the Management of Non-Alcoholic Fatty Liver Disease

Poor dietary composition is an important factor in the progression of non-alcoholic fatty liver disease (NAFLD). The majority of NAFLD patients follow diets with overconsumption of simple carbohydrates, total and saturated fat, with reduced intake of dietary fiber and omega-3 rich foods. Although lifestyle modifications including weight loss and exercise remain the keystone of NAFLD management, modifying dietary composition with or without a calorie-restricted diet may also be a feasible and sustainable strategy for NAFLD treatment. In the present review article, we highlight the potential therapeutic role of a “high quality healthy diet” to improve hepatic steatosis and metabolic dysfunction in patients with NAFLD, independent of caloric restriction and weight loss. We provide a literature review evaluating the evidence behind dietary components including fiber-, meat- and omega-3-rich diets and, pending further evidence, we concur with the EASL-EASD-EASO Clinical Guidelines recommendation of the Mediterranean diet as the diet of choice in these patients

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

Predicted estimates of resting energy expenditure have limited clinical utility in patients with cirrhosis: an individual patient data analysis

© 2022 Published by Elsevier B.V. on behalf of European Association for the Study of the Liver. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1016/j.jhep.2022.01.005Background & Aim: 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 [±1SD] age 55.7±11.6 yr; 70% men; 52% south-east Asian) and 282 healthy controls (mean age 36.0±12.8 yr; 52% men; 18% south-east Asian). Metabolic status was classified using thresholds based on the mean±1SD 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 three new prediction models which included sex, ethnicity, body composition measures, and MELD scores.  Results: The mean mREE was significantly higher in patients than controls when referenced to dry body weight (22.43.8 cf. 20.82.6 kcal/kg/24hr; 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/24hr; p<0.001). Overall, 37.1% of Caucasians and 25.3% of Asians 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/24hr less to 548 kcal/24hr 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.Peer reviewe

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

BACKGROUND & AIM: 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 [±1SD] age 55.7±11.6 yr; 70% men; 52% south-east Asian) and 282 healthy controls (mean age 36.0±12.8 yr; 52% men; 18% south-east Asian). Metabolic status was classified using thresholds based on the mean±1SD 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 three new prediction models which included sex, ethnicity, body composition measures, and MELD 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/24hr; 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/24hr; p<0.001). Overall, 37.1% of Caucasians and 25.3% of Asians 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/24hr less to 548 kcal/24hr 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