In part 1 of Clinical Nutrition in Practice, the metabolism and consequences
of fasting, disease and stress were outlined. It was shown that these
conditions lead to a depletion of body energy stores and protein reserves,
eventually accelerated by a hypermetabolism. Prolonged fasting or hypermetabolism
may lead to a state of malnutrition, which is associated with a decreased
immunocompetence and an increased morbidity and mortality.
Hence, it is important to pay close attention on a possible presence
or development of malnutrition, especially in the hospital setting, since
several studies have proven that malnutrition still represents a significant
problem in the hospital setting.
A number of parameters for the assessment and evaluation of nutritional
status have been developed over the last decades. These parameters are
useful tools in determining body energy and protein reserves. They can
be divided in anthropometric and biochemical parameters. More recently,
newer and more complicated methods and techniques to assess nutritional
status have been developed.
Despite progress in our knowledge on the metabolism in stress and disease
and the development of new techniques to assess nutritional status, assessment
of nutritional status still remains complicated and reliable assessment
always depends on the characterisation of various parameters and never
one isolated parameter.
In the following sections, the various techniques for assessment of
nutritional status and assessment of energy requirements are outlined.
Together, these form the basis for the institution of an adequate nutritional
therapy.
In the past, attempts have been made to correlate nutritional status
with postoperative outcome and complication rate. This resulted in the
definition of the prognostic nutritional index (PNI), a parameter to
prospectively identify the patient at risk of nutritionally based complications
and to permit a quantitative estimate of this risk (Mullen et al., 1979;
Buzby et al., 1980). Of numerous anthropometric and biochemical parameters,
the serum albumin level, triceps skinfold thickness, serum transferrin
level and cutaneous delayed hypersensitivity reactivity appeared to have
a major influence on postoperative outcome. These factors were used to
define the prognostic index, which allows quantification of the risk
of complications and provides a quantitative estimate of operative risk,
thereby permitting rational selection of patients to receive preoperative
nutritional support.
Another index, the prognostic inflammatory and nutritional index (PINI),
combining values of acute-phase reactants (orosomucoid and C-reactive
protein) and visceral proteins (albumin and prealbumin) in a formula
provides a scoring system for the diagnosis and prognosis of stressed
patients (Ingenbleek and Carpentier, 1985).
In another survey of 12 parameters of nutritional status, only preoperative
levels of total serum protein and total iron-binding capacity were independently
related to postoperative sepsis in cancer patients (Bozetti et al., 1985).
Whether these parameters are only non-specific markers of malnutrition
or whether they are directly involved in host defence mechanisms remains
unclear, however.
Indices such as these have been developed to prospectively quantitate
the risk for postoperative infection in order to diminish this risk by
taking appropriate nutritional measures.
From these indices it is clear that only a limited number of anthropometric
and biochemical parameters for malnutrition show a clear correlation
with postoperative outcome.
A large number of these parameters are used today for the assessment
of nutritional status and quantification of the degree of malnutrition.
However, because of the large interindividual variation and the dependence
of these values on disease state, data have to be interpreted with caution.
Therefore, at least as important as these parameters is the clinical
presentation of the patient, because it can identify the patients who
are in a depleted state or are at risk of developing malnutrition.
Clinical assessment, as presented by Jeejeebhoy (1990) may form the
basis for assessment of the nutritional status of the patient. It is
based on the clinical impression of the patient, without exactly defining
or quantifying the degree of malnutrition. It combines a number of clinical
parameters of the nutritional status or, more correctly, forms an index
of sickness rather than of nutritional status. Clinical assessment should
focus on the following points:
-
past nutritional intake;
-
disease process and any operation affecting future
intake of nutrients;
-
catabolic effect of the disease affecting the patient;
-
current physical state in relation to weight loss,
deterioration of functional status, body fat loss and other signs
of malnutrition, such as glossitis, oedema, skin rashes and neuropathy;
-
functional status of the central nervous system, namely
alertness, ability to ambulate and to cough; cardiovascular and renal
function.
Based on features of the clinical history and physical examination,
some diseases and factors of high risk for (development of) malnutrition
can be identified:
-
chronic diseases, like malignancy, kidney and liver
diseases, congestive heart failure;
-
digestive and absorptive abnormalities, like inflammatory
bowel disease, short-bowel syndrome, gastrointestinal fistula, pancreatic
disease, chronic diarrhoea;
-
social and dietary factors, like drug and alcohol
abuse, poverty, poor dentation;
-
other factors leading to increased requirements like
burns, sepsis, surgery, chemotherapy.
Clinical assessment can identify those patients that are at risk for
malnutrition. In an attempt to define the patient´s risk of nutritionally
related complications, the SGA (subjective global assessment) grading
scale has been introduced by Detsky et al. (1987). This assessment is
based on the following features of the patient´s condition: weight
change, dietary intake, gastrointestinal symptoms, functional capacity,
stress and physical signs. On the basis of these features, patients are
scaled into SGA grade A to C, depending on their nutritional status;
this grading helps to identify those patients who are at risk of nutritionally
mediated complications.
Since malnutrition causes variable modifications of the various body
compartments, it is worthwhile to distinguish the lean body mass, which
comprises the masses of the cells, extracellular fluid and skeleton,
from the fatty mass, i.e. the adipose tissue. For a reference adult of
70 kg, the cellular mass is 28 kg (40%), extracellular fluid mass 17.5
kg (25%), the skeletal mass 7 kg (10%) and the adipose tissue mass 17.5
kg (25%) (Blackburn et al., 1979).
Patients identified at risk of protein-energy malnutrition are to undergo
evaluation to determine the severity and type of malnutrition present.
These examinations include the following tests:
1. Assessment of body weight and (recent) weight loss.
2. Assessment of static caloric reserve (fat store).
3. Assessment of static protein reserve (muscle store).
4. Assessment of circulating protein status.
5. Assessment of immune status.
6. Body composition measurement.
Below, a description of the generally used indices to evaluate nutritional
status is given.
Tab. 1: Parameters for the assessment of nutritional
state
Anthropometry is widely used because it is inexpensive, can easily be
applied at the bedside and is reproducible if performed by experienced
investigators. The reliability can be enhanced by successive measurements.
Anthropometric indices are fairly constant and do not change rapidly and
are therefore not measured on a daily basis but rather at large intervals.
2.2.1 Assessment of body weight and (recent)
weight loss
Optimal body weight
When interpreting body weight, allowance must be made for the clinical
judgement in function of the accuracy of the history, the underlying
disease, and variations in hydration or oedemas. Parameters worth recording
are the weight expressed as a percentage of the ideal weight and as
a percentage of the usual weight, as well as the recent percentage
loss in weight in the course of the disease. A weight amounting to
80% of the ideal weight may be interpreted as minor denutrition, 70
to 80% as moderate malnutrition and less than 70% of the ideal weight
as severe malnutrition. The ideal weight is defined as the weight relative
to height associated with the lowest mortality. If the usual weight,
i.e. the premorbid weight, differs greatly from the ideal weight, the
usual weight should be used as a reference. In the case of kwashiorkor,
the weight loss can be less pronounced, because of the oedemas frequently
observed.
Often, a recent history of weight loss is an indication of severe nutritional
depletion. Weight loss can be evaluated according to the guidelines in
Tab. 2.
Tab. 2: Evaluation of weight loss#
Body mass index
The body mass index provides a relation between body weight and body
height and is defined as follows:
BMI = body weight in kg/(body height in m)2
The BMI is usually calculated for a clinical assessment of overweight
and obesity. Limit values are dependent on the age (< or >=35 years)
of the patient. The curvilinear plot of BMI and overall mortality risk
results in a U-shaped curve. In general, a good weight can be defined
as a BMI between 20 and 25 kg/m2 ; overweight is a BMI > 25
kg/m2 and a BMI > 30 kg/m2 strongly indicates signs
of obesity with increased risk (Bray, 1992). Conversely, BMI values lower
than 19 are indicative of malnutrition and thus increased mortality risk.
Moderate undernutrition can be defined as a BMI between 16 and 18 kg/m2 ;
a BMI < 16 kg/m2 indicates severe malnutrition. In critically
ill patients it is often difficult to measure body height and body weight,
while body weight may be influenced by fluid shifts.
Subcutaneous fat forms a valid index for body fat. The measurement
of skinfold thickness is a simple and rapid method for determining body
fat stores. The triceps skinfold thickness (TST) is very informative
about total body fat store. To determine body fat, the skinfold thickness
is measured at the triceps, the thorax and the abdomen. Reference values
are given in Table 3.
Furthermore, anthropometric measurements of the arm provide an indirect
evaluation of the other body compartments. The muscle is representative
of the lean mass, while the adipose tissue is an index of the energy
reserves. From the measurement of the mid upper arm circumference and
the triceps skinfold, the arm muscle circumference and the values of
the muscle compartment and adipose compartment can be calculated (see
Table 1). Although these measurements are not sufficiently sensitive
to allow precise determination of the body composition in a particular
patient, repeated measurements appear to be useful in assessing the effect
of nutritional therapy.
One has to realise, however, that changes in muscle mass are changes
in volume; the corresponding change in circumference is therefore more
difficult to detect. Furthermore, the muscle mass is exaggerated by this
method (15 - 25%). Additionally, in acute disease muscle tissue
is characterized by a relative increase in water content, which makes
it difficult to detect a loss in tissue. Changes in energy and nitrogen
in the short term can not be detected by anthropometry, although it may
detect large shifts in body compartments over months or years. Therefore,
one can conclude that anthropometric measurements can only give an indication
of depletion.
Creatinine Creatinine is a metabolite of creatine; the amount of creatine in
an individual is constant and creatine is only contained in the muscle
tissue. Creatinine can not be reutilized and its excretion in urine is
proportional to the muscle creatine content and therefore to the total
body muscle mass. Creatinine excretion is practically independent of
protein intake and therefore the 24 h creatinine excretion represents
a parameter for the muscle tissue metabolism, as one mole of creatinine
correlates to 17-20 kg of muscle tissue. In physical efforts and
acute illness the creatinine excretion is enhanced and is therefore not
a good index for assessment of malnutrition under these circumstances.
3-Methylhistidine is another biochemical parameter for estimating body
protein mass. This amino acid is located almost exclusively in myofibrillar
protein and is released when this protein is degraded; it cannot be recycled
and is excreted in the urine. Collection of 3-methylhistidine in the
urine therefore reflects the amount of muscle protein broken down. The
interpretation of 3-methylhistidine excretion is complicated, however,
by the fact that other factors than muscle mass, such as age, dietary
intake and stress influence 3-methylhistidine excretion.
Creatinine/height index
As the muscle tissue is dominated by the height of the patient, the creatinine/height
index has been introduced (24 h urine creatinine divided by the length)
to correlate creatinine excretion to muscle tissue. The values observed
have to be compared to reference values of creatinine excretion for
a normal adult of the same sex and length. It is assumed that a reduction
in muscle mass produces a proportional reduction in creatinine/height
index.
Nitrogen Balance
Since the protein mass appears to be the limiting factor governing survival,
dynamic assessment of nitrogen balance is of prime importance. There
are several methods for assessing protein and nitrogen metabolism.
The oldest and most widely used method for evaluating changes in body
nitrogen is the nitrogen balance method. However, there are other methods,
like determining arteriovenous differences in amino acids, reflecting
amino acid metabolism, or methods using radioactive labelled amino
acids.
As body proteins contain virtually all the nitrogen in the organism,
measurement of nitrogen balance reflects protein balance. Metabolites
of protein breakdown appear mainly in the urine. Protein is also lost
in the stool, in the renewal of the skin and in the growth of hair and
nails. In hospital, there are further losses, e.g. in wounds and fistulae.
By measuring the quantities of nitrogen given as protein and the quantities
lost by various routes, one can arrive at a nitrogen balance: Nbal =
Nin - Nout
However, the nitrogen balance only defines the difference between nitrogen
entering and exiting the body. It should be pointed out that nitrogen
losses are routinely underestimated because of incomplete collections
of urine and faeces and insensible losses (e.g. through skin and sweat),
while nitrogen intake can easily be overestimated because of food not
consumed.
The nitrogen balance is an indirect, but nevertheless reliable measure
of protein conservation. A negative nitrogen balance, for example, shows
that protein losses are greater than protein intake, indicating catabolic
state.
In hospital, the measurement of an exact nitrogen balance is hardly
practicable. Even the equipment for measurement of total nitrogen in
urine is often not available. One may, however, make use of the following
approximation:
Nbal (g/24h)
=
Nin - [UNN + 4 + (BUNe - BUNs/100
x BW x F)]
Nin
=
nitrogen intake (g/24h)
UUN
=
urinary urea nitrogen (g/24h)
BUN
=
blood urea nitrogen (mg/dl) (s = at start, e = at end of
24h)
BW
=
body weight (kg)
F
=
body water factor (male: F = 0.60, female: F = 0.55)
This equation takes account for the fact that the majority of the nitrogen
losses in urine (80 - 90%) are in the form of urea; this fraction
may rise in catabolic situations, but is never below this value. Losses
in the urine other than as urea are reckoned to amount to 2 g and the
skin and faecal losses also to 2 g (hence the 4 in the equation). Finally,
a correction is made for urea that is produced, but does not appear immediately
in urine, accumulating instead in the blood (BUN). Losses from the drainage
of wounds and fistulae have to be taken into account by measurement.
To calculate nitrogen balance, a 24 h urine collection is required in
order to determine urea nitrogen (1 g of nitrogen = 2.2 g of urea) or
total urinary nitrogen, to which is added the undetermined nitrogen losses
(skin, faeces) estimated at 2 - 4 g of nitrogen. Urinary nitrogen
losses vary from an obligatory minimum of about 2 g/day to more than
30 g/day in massive protein catabolism. The nitrogen balance is negative
when nutritional intake is less than the sum of urinary nitrogen and
undetermined losses. The daily nitrogen losses depend on many factors.
These are increased by immobility, by reduction of the caloric intake
with a constant nitrogen intake, and by stress-related increases in protein
oxidation. The latter can produce dramatic increases in nitrogen losses.
Tab. 4: Daily nitrogen losses in adults in various
states
One must remember that nitrogen losses are tantamount to protein losses.
Nitrogen losses therefore are always associated with a loss of functional
capability, and lead to a higher incidence of complications, wound dehiscence,
increased susceptibility to infection, decreased organ function (liver,
gut, heart, lung) and in the extreme case to death from nitrogen deficiency.
Nitrogen losses furthermore lead to substantial losses in body weight
according to the equation:
Plasma protein concentrations are used routinely for assessment of nutritional
status and the effect of nutritional therapy, but these are not highly
specific. Numerous factors may modify the serum protein levels, particularly
the state of hydration or the presence of oedema.
Serum albumin is an index often used, although many factors other than
energy intake influence the metabolism of albumin and its distribution
in the intra- and extravascular fluids. Albumin is the main protein synthesized
and secreted by the liver (15 g per day) with a half-life of approximately
18 days. Measurement of albumin will not always give a correct indication,
as for example in acute illness (especially sepsis) when the extravascular
distribution of albumin rises, resulting in a lowered serum albumin,
without a lowered store. Overhydration is another cause of a low albumin
concentration not indicative of undernutrition. Albumin may serve as
a parameter of chronic protein deficiency because of its relatively long
half-life, which makes it a poor indicator of acute protein-energy deficiency.
Transferrin, which has a half-life of 8-10 days, may be a more sensitive
index than albumin, but possesses low specificity. Serum concentrations
are influenced by lack of iron, acute hepatitis and acute and chronic
disease, without the necessary implication of loss of protein.
Other proteins with an even shorter half-life have been assessed. These
are the retinol-binding protein (RBP), and the thyroxin-binding prealbumin
(TBPA), which have half-lives of 12 and 48 h respectively. These parameters
function as an indicator of acute protein alterations. C-reactive protein
(CRP) is an acute phase protein, very low in normal healthy subjects,
but exponentially rising with the onset of infection and returning very
rapidly to normal or near normal values after the stimulus is removed.
This makes it a helpful marker in the care of patients who are at high
risk for post-operative infection.
The well-established interaction between malnutrition and infection
may be due to modifications of the immunological defence observed in
protein-energy malnutrition. Malnutrition decreases the synthesis of
acute phase proteins that can help in the survival during stress, infection
and injury. Besides that, cellular immunity is generally impaired in
malnutrition (Chandra, 1983). Assessment is carried out on the total
lymphocyte count in blood and by using tests for skin hypersensitivity
to various antigens. From the extent of the cutaneous reaction, an immune
score can be established. In general, a lowered immune score indicative
of anergy is associated with an increased incidence of infectious complications.
Interpretation of the immune response is nevertheless limited by the
numerous variables which may affect it, such as certain drugs, surgical
stress and the reliability of reference values. In undernourished patients,
lowered, normal or raised serum immunoglobulin levels are observed, so
that the effect of malnutrition on the humoral response has yet to be
defined. Other major components of defence against infections are diminished
in malnutrition, such as complement factors or leukocyte bactericidal
capacity (Chandra, 1983).
To date, new and more precise methods for assessing changes in body
composition, as occurring in protein-energy malnutrition, have been developed.
Each type of protein-energy malnutrition is characterized by specific
changes in body composition.
Tab. 5: Characteristic changes in body composition
that occur in association with each of the three types of protein-energy
malnutrition
Marasmic patients have marked deficits of total body fat and protein.
Marasmic kwashiorkor is also characterized by deficits in total body
fat and protein and a marked relative increase in extracellular water.
Patients with kwashiorkor are characterized by raised amounts of total
body water, extracellular water and the proportion of extracellular water
in the fat-free body.
In order to overcome the shortcomings of determining body composition
by indirect anthropometric and biochemical measurements, body composition
analysis by isotope dilution techniques and neutron activation analysis,
bioelectrical impedance analysis and magnetic resonance spectroscopy
techniques have been developed.
In isotope dilution assays, radioactive isotopes (22Na and 3H)
are used to assess total exchangeable sodium, total exchangeable potassium
and total body water. As sodium is diluted primarily in the extracelullar
water compartment and potassium in the intracellular water compartment,
the body cell mass, body fat mass, lean body mass, extracellular mass
and the ratio of extracellular water to intracellular water can be determined.
Malnutrition leads to a reduction of the body cell mass, while the extracellular
mass and extracellular water rise, leading to a net change in the ratio
of Nae/Ke (e = exchangeable). This ratio appears
to be a marker for malnutrition; it approximates unity in well-nourished
subjects and is greater than 1.22 in malnourished subjects (Forse and
Shizgal, 1980).
Isotope dilution technique allows definition of the body cell mass,
which is however greatly influenced by changes in intracellular water
and determination by the isotope dilution technique may therefore result
in an over- or underestimation of the protein mass.
Reaction activation analysis allows direct measurement of a number of
elements, including nitrogen. The patient is radiated with high energy
neutrons and afterwards moved to a whole body radiation counter. The
radiation emitted by radionucleides induced by the neutrons is specific
for various elements in the body. The complex spectrum from the patient
is measured and analysed to give counting rates due to nitrogen (protein),
hydrogen, carbon, chorine and in some systems calcium, phosphorus and
sodium. From these data, the total body content for these elements can
be calculated.
For this reason, neutron activation analysis is a reliable and direct
method, although the equipment required is expensive. Compared to the
isotope dilution technique, it is preferable in patients with fluxes
in body water.
Efficient utilisation of nitrogen-calorie substrates can only occur
in the presence of physiological concentrations of a multitude of micronutrients:
electrolytes, minerals, vitamins and trace elements. These nutrients
are essential in minute quantities for the maintenance of normal metabolic
functions. Micronutrient deficiencies may be the consequence of inadequate
intake, defective absorption or utilisation, or they may supervene as
a result of increased requirements. Diagnosis of micronutrient deficiencies
attempts to identify the infraclinical or asymptomatic stages rather
than to describe manifest organic alterations.
Tab. 6: Assessment of vitamin and trace element
deficiencies
Assessment of the nutritional status of a patient is relatively difficult.
Ideally, the identification of protein-energy malnutrition should conform
to the following criteria (Buzby and Mullen, 1984):
1. It should specifically identify protein-calorie malnutrition and
2. be negative in patients without protein-calorie malnutrition.
3. It should be unaffected by non-nutritional factors.
4. It should demonstrate normalisation with adequate nutritional support.
From the preceding, it is clear that a number of methods and parameters
are available for assessment of the nutritional status of patients and
for evaluating the response to clinical nutrition. Some of these parameters
are specific and sensitive, while others are not. Problems with the interpretation
of anthropometric parameters are that these parameters are subject to
observer errors and are influenced by changes in tissue composition induced
by non-nutritional factors. For example, the administration of intravenous
fluids or blood products, or the extensive loss of fluids or blood, or
the excessive loss of fluid or protein through diarrhoea, fistulae etc.
may invalidate anthropometric and serum protein measurements. Disease
states like hepatic disease and nephrosis may reduce serum levels of
albumin and transferrin in patients undergoing nutritional assessment.
Infection and trauma may interfere with delayed cutaneous hypersensitivity
test. The prolonged half-lives of serum albumin and transferrin cause
delayed responses in both nutritional depletion and repletion. Other
tests like body composition measurements are not generally used.
Furthermore, one must remember that these nutritional parameters have
wide confidence limits and therefore are in general more suited for use
in epidemiological surveys than in individual patients. The problem is
that none of these parameters is suited as the sole parameter to assess
nutritional status.
Therefore, clinical evaluation forms the basis in identifying those
patients who are at risk of malnutrition and nutritionally related complications.
On the basis of this clinical evaluation, patients that are malnourished
can be further evaluated using anthropometry and biochemical markers.
Further, these techniques are a helpful tool in assessment of the effect
of nutritional support.
As already discussed, some investigators have tried to asses the nutritional
status by combining several parameters into a prognostic index. The relative
value of these scoring systems has been demonstrated in clinical studies
(Vehe et al., 1991) and further trials are needed to confirm the performance
of such indices as a prognostic tool.
Applying the mentioned methods and limits for assessing the nutritional
status, one can arrive at the following definitions about the nutritional
status of the patient:
1. Normal nutritional status exists when all parameters are within the
reference range.
2. Adipositas (obesity) exists when body weight, BMI and skinfold thickness
are supranormal and all other parameters are in the normal range.
3. Protein malnutrition exists when body weight, BMI and skinfold thickness
are within the normal range and arm-muscle circumference and creatine
excretion are diminished; plasma protein levels are depressed.
4. Protein-calorie malnutrition exists when weight, BMI, skinfold thickness
(energy component), arm- muscle circumference and creatine excretion
(protein component) are decreased, indicating that functional proteins
are depressed.
Baker JP, Detsky AS, Wesson DE et al.:
Nutritional assessment. A comparison of clinical judgement and objective
measurements.
N Engl J Med 1982; 306: 969 - 72.
Bistrian BR.:
Nutritional assessment and therapy of protein-calorie malnutrition in
the hospital.
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Therapeutic index of nutritional depletion in hospitalised patients.
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Blackburn GL, Benotti PN, Bistrian BR, Maini BS, Schlamm HT, Smith MF.:
Nutritional assessment and treatment and treatment of hospital malnutrition.
Infusionstherapie 1979; 6: 238 - 50.
Bozetti F, Migliavacci S, Gallus G et al.:
"Nutritional" markers as prognostic indicators of postoperative sepsis in cancer
patients.
JPEN 1985; 9: 464 - 70.
Bray GA.:
Pathophysiology of obesity.
Am J Clin Nutr 1992; 55: 48S - 94S.
Detsky AS, McLaughlin JR, Baker JP et al.:
What is subjective global assessment of nutritional status?
JPEN 1987; 11: 8 - 13.
Forse RA, Shizgal HM. The Nae/Ke ratio: a predictor of malnutrition.
Surg Forum 1980; 31: 89 - 92.
Frisancho AR.:
New norms of upper limb fat and muscle areas for assessment of nutritional
status
Am J Clin Nutr 1981; 34: 2540 - 5.
Goldstein SA, Elwyn DH.:
The effects of injury and sepsis on fuel utilisation.
Annu Rev Nutr 1989; 9: 445 - 73.
O´Gorman RB, Feliciano DV, Matthews KS et al.:
Correlation of immunologic and nutritional status with infectious complications
after major abdominal trauma.
Surgery 1986; 99: 549 - 55.
Grande F, Keys A.:
Body weight, body composition and caloric status. In: Goodhart RS, Shils
ME, eds. Modern nutrition in health and disease, 6th ed. Philadephia:
Lea & Febiger, 1980: x - 34.
Grant JP, Custer PB, Thurlow J.:
Current techniques of nutritional assessment.
Surg Clin North Am 1981; 61: 437 - 63.
Hackl JM, Germann R.:
Guide to parenteral nutrition. München: W Zuckschwerdt Verlag, 1994:
126 - 32.
Heymsfield SB, Casper K.:
Anthropometric assessment of the adult hospitalised patient.
JPEN 1987; 11 (suppl): 36S - 41S.
Hill GL.:
Body composition research: implications for the practice of clinical
nutrition.
JPEN 1992; 16: 197-218.
Ingenbleek Y, Carpentier YA.:
A prognostic inflammatory and nutritional index scoring critically ill
patients.
Internat J Vit Nutr Res 1985; 55: 91-101.
McMahon MM, Bistrian BR.:
The physiology of nutritional assessment and therapy in protein-calorie
malnutrition.
DM 1990; 36: 378 - 417.
Mullen JL.:
Consequences of malnutrition in the surgical patient.
Surg Clin North Am 1981; 61: 465 - 87.
Mullen JL, Buzby GP, Waldman MT, Gertner MH, Hobbs CL, Rosato EF.:
Prediction of operative morbidity and mortality by preoperative nutritional
assessment.
Surg Forum 1979; 30: 80 - 2.
Pettigrew RA, Charlesworth PM, Farmilo RW, Hill GL.:
Assessment of nutritional depletion and immune competence: a comparison
of clinical examination and objective measurements.
JPEN 1984; 8: 21 - 4.
Shizgal HM.:
Nutritional assessment with body composition measurements.
JPEN 1987; 11 (suppl): 42S - 7S.
Shizgal HM, Forse RA.:
Protein and caloric requirements with total parenteral nutrition.
Ann Surg 1980; 192: 562 - 9.
Tuten MB, Wogt S, Dasse F, Leider Z.:
Utilisation of prealbumin as a nutritional marker.
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The prognostic inflammatory and nutritional index in traumatized patients
receiving enteral nutrition support.
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3. Calculation and measurement of energy requirements
Energy is generated in the human body by the burning of food components.
Depending on their nature, food components yield a specific energy content
(calorific value), which is determined empirically. Different substrates
yield different values, even within one substance group. The energy content
is therefore expressed as a mean value in order to simplify matters by
rounding figures.
Tab. 7: Energy content of food components
The energy content of these substances is expressed in units of kilocalories
(kcal) or kiloJoules (kJ). The conversion factor from kcal to the SI
unit kJ is 4.1868.
For the assessment of the energy requirement of the hospitalized patient,
several methods are available. These methods are either based on the
technological assessment of the energy requirement by direct or indirect
calorimetry or on empirical approximate equations.
The human body converts about 45% of the energy content of the food
intake into work and about 55% into heat. As far as work is concerned,
a distinction is drawn between internal work (respiration, cell pumps,
synthetic processes, etc.) and external work (muscular work in moving).
Since internal work is finally also converted to heat, one can estimate
the body´s energy requirement by measuring the heat given off at rest.
Therefore, one measures the heat production by the temperature change
produced in a medium.
This method of estimation is called direct calorimetry and is extraordinarily
complicated. The equipment required for the measurements is large, immobile
and expensive; during the measurements, the patient is placed in a chamber
and is not readily accessible. For these reasons, direct calorimetry
is rarely used in the clinical setting.
Energy expenditure may also be determined by indirect calorimetry. Indirect
calorimetry measures gas exchange via oxygen consumption and carbondioxide
production. It allows the heat produced by oxidative processes to be
determined and relies on the fact that oxidation of particular food components
is associated with a specific oxygen consumption and carbondioxide production;
urinary nitrogen excretion is determined as a function of protein degradation.
Besides thermogenesis and activity, indirect calorimetry takes into
account all the factors of the patient´s illness, including temperature,
sepsis and catabolic processes.
In the open-circuit method, the expired air is collected for volumetric
measurements and is analysed for its oxygen and carbondioxide content
and corrected to standard conditions. These figures are then used to
calculate oxygen consumption and carbondioxide production. In the closed-circuit
method, the patient is isolated from the outside air and breathes from
a reservoir that contains pure oxygen. As gas is expired by the patient,
carbondioxide is removed. The decrease in gas volume is directly related
to the rate of oxygen consumption and therefore can be used to calculate
the metabolic rate. The values obtained by indirect calorimetry reflect
the actual energy requirements and the utilisation of the individual
substrates.
From a technical point of view it is simpler than direct calorimetry.
Indirect refers to the heat production calculation from oxygen consumption
and carbondioxide production, rather than from direct measurements. If
the two figures are related for a given time period, one can come to
a factor named the respiratory coefficient (RQ).
RQ
=
VCO2 / VO2
VCO2
=
expired CO2 volume per unit of time
VO2
=
consumed O2 volume per unit of time
Tab. 8: O2 consumption, CO2 production,
respiratory energy equivalent and RQ of various food components
Starting from the measured O2 consumption and CO2 production,
the metabolic rate (MR) can be calculated from various equations. The
simplest is to assign a mean value to the respiratory energy equivalent
for oxygen consumption of 4.83 kcal/ l 02.
MR (kcal/h) = 4.83 x VO2
The resulting equation has a maximum error of 8%.
If CO2 production is also considered, the equation becomes:
MR (kcal/h) = 3.9 x VO2 + 1.1 x VCO2
The oxidation of protein is associated with the excretion of nitrogen
in urine. One gram of nitrogen in urine is equivalent to an oxygen consumption
of 5.94 l and a CO2 production of 4.76 l. If one measures the total urinary
nitrogen (UN) per unit of time, the metabolism can be corrected for the
fraction of oxidised protein. In Weir´s equation this (v. Weir, 1949)fraction
is estimated at 12.5%:
MR (kcal/h) = 3.941 x VO2 + 1.106
x VCO2 - 2.17 x UN
The fraction of the various foodstuffs used as an energy source can
be calculated from the total urinary nitrogen (UN in g), the oxygen consumption
(VO2 in l) and CO2 production (VCO2 in
l) by the following equations (Wilmore, 1977):
Protein oxidation (g)
=
6.25 x UN
Carbohydrate oxidation (g)
=
-(2.56 x UN) - (2.91 ( VO2)
+ (4.12 x VCO2)
Fat oxidation (g)
=
-(1.94 x UN) + (1.69 ( VO2)
- (1.65 x VCO2)
The fraction for each foodstuff depends on the metabolic situation and
on the diet. Average values are 15 - 17% for protein, 50 - 55%
for carbohydrate and 30 - 35% for fat oxidation.
The measured metabolic rate at rest depends on circumstantial factors.
A minimum results with measurement after 12 - 14 h fasting
under conditions of complete bodily rest, mental relaxation and in a
thermoneutral environment. 24 hours' energy consumption under these circumstances
is called basal metabolic rate (BMR). In hospitals less standardized
conditions prevail and energy consumption at rest is approximately 10%
higher and referred to as resting energy expenditure (REE)
Basal metabolic rate (BMR) is defined as the quantity of energy required
to satisfy the requirements of the body at rest. Basal metabolic rate
can be estimated from empirical approximate equations.
The most used formula for the calculation of the basal metabolic rate,
based on indirect calorimetry, is the Harris & Benedict formula (Harris
and Benedict, 1919):
BMR = 66 + (13.7 x BW) + (5 x ( H) - (6.8 x A) (male)
BMR = 655 + (9.6 x BW) + (1.73( H) - (4.7 x A) (female)
in which BW = body weight in kg, H = height in cm, A = age in years.
The BMR can also be estimated from the Fleisch standard metabolic rates
(Fleisch, 1951), based on the body surface. The body surface can be estimated
from standard normograms on the relation between body surface area, weight
and height.
Tab. 9: Standard metabolic rates
The actual energy expenditure (AEE) will normally be higher than the
BMR). Only in prolonged fasting is energy expenditure reduced by 10 - 15%.
Energy requirement increases for example with fever (12% per 10° C),
with all kinds of stress (+5% to +100%), with food intake (specific dynamic
action: +12% for protein, +6% for carbohydrate, +2% for fat, +6% for
mixed diets) and with physiological activity. AEE can therefore be estimated
using calculated BMR and factors to correct for increases in energy requirements.
Despite the fact that estimating the AEE from calculation of the BMR
is very widely used and represents a simple and quick method, it is not
always accurate because of the large range of thermogenic responses to
injury, trauma and infection.
Tab. 10: Equations and factors to estimate actual
energy expenditure (AEE)
Kinney JM.:
The application of indirect calorimetry to clinical studies. In: Kinney
JM, ed. Assessment of energy metabolism in health and disease. Columbus,
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Kinney JM.:
Indirect calorimetry in malnutrition: nutritional assessment or therapeutic
reference?
JPEN 1987; 11 (suppl): 90S - 4S.
Kinney JM, Duke JH Jr, Long CL, Gump FE.:
Tissue fuel and weight loss after injury.
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van Weir JBde, New methods for calcnlating metabolic rate with special
reference to protein metabolism. J. Physiol 1949; 109: 4-9.
Weissman C, Kemper M, Elwyn DH, Askanazi J, Hyman AI, Kinney JM.:
The energy expenditure of the mechanically ventilated critically ill
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An analysis. Chest 1986; 89: 254 - 9.
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