Chapter 2. Background
Malnutrition and hypermetabolism in liver cirrhosis
Body composition analysis and malnutrition in liver cirrhosis
The assessment of malnutrition in patients with liver cirrhosis is difficult and malnutrition may be masked by physiological sequelae of liver cirrhosis. Liver cirrhosis is often indolent, asymptomatic and unsuspected until complications of liver disease arise. It is estimated that around 40% of patients with cirrhosis die before the disease is recognised35. As a result, malnutrition is often missed in patients with cirrhosis, particularly in the early stages of disease36.
Malnutrition is assessed by measuring changes in body composition. The study of body composition can be defined as a branch of human biology that studies various body compartments and their quantitative steady-state relationships37. Central to this is developing the methodology for measuring the various compartments in vivo and the influence of various biological factors on these compartments and relationships. The 5 level model proposed by Wang et al provides a structural framework for the study of body composition. The 5 levels (with increasing complexity) are the atomic, molecular, cellular, tissue-system and whole-body levels where each level has specific compartments that comprise body weight. In essence, these levels are a simplified description of the human body. The whole-body level has the highest complexity as it is at this level that the human body is clearly differentiated from any other living organism (e.g. primates or animals).
Measurements at the whole-body level are the easiest to perform and comprise body weight, skinfold and circumference measurements. Accurate testing for compartments at the atomic or molecular levels is less susceptible to error but require specialised and expensive techniques37. The following table summarises some of the common direct measurement techniques currently available for each level.
The accuracy of traditional approaches for assessing malnutrition (based primarily on body weight, skinfold or circumference measurements) may be masked by tissue oedema in patients with liver cirrhosis. Sodium retention and oedema occur early in the course of liver cirrhosis before clinical signs emerge38, 39 and the use of serial body weight or body mass index (BMI) measurements would not be appropriate in this patient population. Upper-arm anthropometric measurements such as mid-arm muscle circumference are a commonly used method but up to 30% of healthy controls would be considered under-nourished according to the reference standards of this method40, 41. Tissue oedema in cirrhotic patients would be expected to contribute further error to measurements42. Similarly, bio-electrical impedance analysis (an indirect whole-body measurement technique) should be used with caution in liver cirrhosis43-45. Bio-electrical impedance was not able to accurately detect the change in total body water following large volume paracentesis of ascites in individual patients with liver cirrhosis46. Lastly, liver synthetic function is impaired in liver cirrhosis and visceral protein markers of nutritional status like albumin and retinol-binding protein should be used with caution47, 48.
Mid-arm muscle circumference and bio-electrical impedance determine the fat and lean body compartments using a 2-compartment model of body composition. 2-compartment models are the earliest and simplest models (at the molecular level) and divide the body into fat mass and fat-free Wai Gin Lee 8 July 2013
mass (FFM) by means of prediction equations. However these models are dependent on the assumption that the ratio of components within FFM remain constant and that the hydration fraction of FFM is constant. In cirrhosis, the assumptions are not necessarily valid and results obtained using 2 – compartment models differed significantly from 4-compartment models that directly measured or estimated total body water, protein and bone minerals49. Both accuracy and precision of measurements were improved using a 4-compartment model50. With the advent of new technology (Table 2-1), more detailed models of body composition that include all 6 compartments of the molecular level have been developed (fat, water, protein, bone mineral content, non-bone mineral and glycogen) and provide the gold standard measurement of body composition (see below).
A 6-compartment model of body composition was developed by Plank et al and allows total body water (TBW) to be calculated using a difference method51. Briefly, TBW is one of six compartments comprising body weight. The other compartments are TBP, total body fat, bone mineral content, glycogen and non-bone mineral content. TBP, total body fat and bone mineral content can be directly measured using contemporary body composition methods. The non-bone mineral and glycogen compartments are small and are estimated from TBP and total mineral content (bone mineral content and non-bone mineral content) respectively using the relative size of these compartments in Reference Man52. Including both these components reduces the systematic error that would otherwise arise in extracting TBW by this method. Nevertheless, measurement of TBW using the difference method is still subject to a small systematic error largely from unmeasured fluctuations in the glycogen compartment but results correlated well with the gold standard tracer dilution method51.
Protein represents a key structural and functional component of the body, and loss of body protein is associated with loss of function53, 54. In vivo neutron activation analysis is the gold standard for measurement of protein depletion. This technique was first used in cirrhotic patients in 1993 and TBP levels expressed as a nitrogen index (ratio of measured TBP over predicted) were significantly reduced compared to healthy controls55. The technique of in vivo neutron activation analysis was subsequently refined for patients with liver cirrhosis using a 6-compartment model by Plank et al to calculate the FFM corrected for abnormal hydration (a common finding in cirrhotic patients)56.
The same group proceeded to comprehensively assess body composition in a cross-section of well-characterised and clinically stable cirrhotic patients using the 6-compartment model (Peng et al8). In this study of 268 cirrhotic patients, 51% of patients were protein depleted compared to 386 healthy volunteers with over twice as many men protein depleted compared to women (63% and 28% respectively, p < 0.0001). Over-hydration was seen in 65% of patients and both protein depletion and over-hydration worsened with increasing severity of cirrhosis (as measured by the Child-Pugh score3). Patients with established protein depletion were more likely to be over-hydrated and to have ascites.
The sex difference in muscle depletion may have been related to higher fat stores in women slowing the catabolism associated with cirrhosis because men actually had a higher energy intake as a proportion of REE compared to women57. The percentage body fat in women was 35.7 ± 1.0% compared to 23.5 ± 0.6% in men. Percentage body fat was reduced in Child’s C cirrhotic patients compared to Child’s A patients but there was no difference between patients with or without protein depletion.
Resting energy expenditure and hypermetabolism in liver cirrhosis
The study by Peng et al also examined energy metabolism in the same cross-section of cirrhotic patients. Hypermetabolism was defined as the ratio of measured REE over predicted greater than 1.22 (which represents 2 standard deviations above the mean of the distribution in healthy volunteers). Forty one of the 268 patients were hypermetabolic (15%) and hypermetabolism was not associated with sex, severity of disease, aetiology of cirrhosis, protein depletion or the presence of ascites8. This compares to a reported prevalence of hypermetabolism of between 18% and 34.5% of cirrhotic patients from several other heterogeneous studies6, 12, 13, 16, 58-61. The presence of ascites was associated with an increased REE in a small study of patients with primarily alcoholic cirrhosis62. An increased REE is also associated with a reduction in insulin sensitivity in patients with liver cirrhosis60.
Many approaches have been used to define hypermetabolism which makes direct comparison between studies difficult63. All studies defined hypermetabolism as the ratio of measured REE (using indirect calorimetry) over predicted REE but the method for predicting REE was not the same between studies. Most studies predicted REE using the equations of Harris and Benedict64.
Variables in equations 1.1 and 1.2 are easily measured but significant discrepancies between the measured REE and predicted REE using the Harris-Benedict equation (greater than 10%) have been reported even in healthy volunteers65-68. In liver cirrhosis, over-hydration and loss of FFM would result in a further deviation from the predicted value as FFM is the major determinant of REE65, 69. For these reasons, the use of the Harris-Benedict equation for predicting REE in the research setting should be discouraged because greater accuracy is generally required.
Prediction formulae for REE have been proposed that attempt to overcome the confounding effects of progressive over-hydration and loss of FFM in liver cirrhosis. Measurements were taken from 80 healthy volunteers and a prediction formula for REE was derived using the corrected FFM for abnormal hydration (FFMC)56
Chapter 1. Introduction
1.1. Liver cirrhosis is a common cause of morbidity and mortality
1.2. Detrimental nutritional and metabolic changes in liver cirrhosis
1.3. β-blockade may reduce REE and the prevalence of hypermetabolism
1.4. -blockade reduces insulin sensitivity and glucose tolerance
1.5. Patients with liver cirrhosis have reduced insulin sensitivity and glucose tolerance
1.6. Little is known about β-cell function in patients with liver cirrhosis
1.7. Thesis outline
Chapter 2. Background
2.1. Malnutrition and Hypermetabolism in Liver Cirrhosis
2.2. The Role of -blockade in Hypermetabolism
2.3. Glucose Tolerance in Liver Cirrhosis
2.4. Patients with liver cirrhosis have reduced insulin sensitivity
2.5. Methods for measurement of insulin sensitivity in liver cirrhosis
2.6. Mechanisms for the reduction of insulin sensitivity and glucose tolerance in liver cirrhosis
2.7. β-cell function in liver cirrhosis and methods for measurement
2.8. The clinical significance of deranged glucose metabolism in liver cirrhosis
2.9. The effect of -blockade on glucose tolerance
Chapter 3. Prevalence of diabetes in liver cirrhosis– a systematic review
Chapter 4. Oral β-blockade may reduce energy expenditure in patients with liver cirrhosis: a doubleblind, randomised cross-over trial
Chapter 5. Nadolol reduces insulin sensitivity in liver cirrhosis: a double-blind, randomised cross-over trial
Chapter 6. Nadolol impairs pancreatic glucose sensitivity in patients with liver cirrhosis
Chapter 7. Conclusions
7.1. Appendix 1 – Example of Search Strategy: Medline (OVID)
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