Enteral Energy and Macronutrients in End‐Stage Liver Disease

Protein‐energy malnutrition is the most common comorbidity affecting adults and children with end‐stage liver disease. Despite clear evidence linking malnutrition to poor outcomes before and after liver transplantation, nutrition rehabilitation is often inadequately emphasized in the clinical management of these patients. The primary aim of this review is to synthesize the available evidence supporting the current clinical guidelines on enteral nutrition support and, more important, to highlight the lack of evidence behind much of what is considered “standard of care” for the nutrition management of patients with cirrhosis. In addition, the mechanisms of malnutrition are reviewed, the limitations of tools used to assess body composition in this setting are discussed, and the differences in macronutrient metabolism between healthy subjects and patients with end‐stage liver disease are explained. A summary of recommendations is provided.     

Microvessel density as a prognostic factor in non-small-cell lung carcinoma: a meta-analysis of individual patient data

BACKGROUND: Angiogenesis is a potential prognostic factor that has been investigated in patients with non-small-cell lung carcinoma. However, published studies of the role of angiogenesis as a prognostic factor are inconclusive. We aimed to collect individual patient data to assess microvessel-density counts (ie, a measure of angiogenesis) as a prognostic factor in non-small-cell lung carcinoma. METHODS: We obtained published and unpublished datasets and extracted appropriate data, taking particular care to ensure data quality. Detailed information was obtained for the laboratory methods used by every research centre that generated the data. The outcome of interest was overall survival. We did a meta-analysis to estimate the prognostic role of microvessel density by combining separately estimated hazard ratios (HR) from every study, which were adjusted for tumour stage and age. Analyses were done separately for studies that used the Chalkley method or for those that counted all microvessels. FINDINGS: 17 centres provided data for 3200 patients, 2719 of which were included in the analysis. All but three centres (datasets 9, 10, and 13-367 cases) had already published their findings, and six had updated follow-up information (datasets 1, 2, 3, 6, 7, and 8-1273 cases). For all but three centres (datasets 4, 11, and 13) some data corrections were necessary. For microvessel density counts obtained by the Chalkley method, the HR for death per extra microvessel was 1.05 (95% CI 1.01-1.09, p=0.03) when analysed as a continuous variable. For microvessel density counts obtained by the all vessels method, the HR for death per ten extra microvessels was 1.03 (0.97-1.09, p=0.3) when analysed as a continuous variable. INTERPRETATION: Microvessel density does not seem to be a prognostic factor in patients with non-metastatic surgically treated non-small-cell lung carcinoma. This conclusion contradicts the results of a meta-analysis of published data only. Therefore, the methodology used to assess prognostic factors should be assessed carefully.     

Resting Energy Expenditure of Children and Adolescents With Nonalcoholic Fatty Liver Disease

Background:The mainstay of treatment for pediatric nonalcoholic fatty liver disease (NAFLD) is lifestyle modification, which includes dietary changes that lead to slow but sustained weight loss or weight stabilization in growing children. Accurate estimation of energy requirements is necessary to achieve this goal. The objective of this study was to assess the accuracy of the most commonly used equations in predicting the resting energy expenditure (REE) of children with NAFLD. Methods: This was a retrospective study performed in a single institution. The predictive accuracy of various equations was assessed by comparing their estimates against the measured REE obtained with indirect calorimetry. Accuracy was defined as an estimate within 10% of measured REE. Results: Fifty‐six children (70% male; 52% white and 36% Asian) with a median age of 13 years were included. The median measured REE was 1829 kcal/d. Of the equations studied, the Schofield had the smallest average bias (–32 kcal/d; confidence interval, –121 to 56). The Schofield and Molnar equations were the most accurate, providing REE estimates within 10% of measured in 59% of cases. The remaining equations had lower and variable predictive accuracy. The use of adjusted body weight in predictive equations did not improve the predictive accuracy. Conclusion: In a cohort of children and adolescents with NAFLD, the Schofield and Molnar equations performed best in predicting energy expenditure. However, predictive equations were often inaccurate, suggesting that clinicians should interpret their results with caution and consider using indirect calorimetry when available.     

Overweight,central obesity,and cardiometabolic risk factors in pediatric liver transplantation

PTMS describes the presence of ≥3 cardiometabolic risk factors that include obesity, hypertension, dyslipidemia, and IR. The prevalence of the clustering of ≥3 cardiometabolic risk factors or central obesity has not been studied in pediatric LT recipients. Single‐center, cross‐sectional study. Inclusion criteria: LT recipients 2–18 yr‐old, at least one yr post‐LT. Exclusion criteria: recipients of liver retransplants or multivisceral transplants. Eighty‐seven patients were identified. Median age was 9.8 yr (range 2–18), median time since LT was 6.9 yr (range 1–17). The most common indication for LT was biliary atresia (56%), and the most frequently used immunosuppressant was tacrolimus (80%). The prevalence of overweight and obesity was 21% and 5%, respectively. Central obesity affected 14%, hypertension 44%, IR 27%, low HDL 20%, and hypertriglyceridemia 39% of patients. The prevalence of ≥3 cardiometabolic risk factors was 19%. Fifty percent of the overweight/obese patients had ≥3 risk factors. Time since transplant, immunosuppression and renal function were not different between those with <3 or ≥3 risk factors. Clustering of cardiometabolic risk factors is prevalent in pediatric LT recipients, suggesting an increased risk of future CV events.