Recommendations Summary
SCI: Assessment: Energy Needs in Acute and Rehabilitation Phases 2009
Click here to see the explanation of recommendation ratings (Strong, Fair, Weak, Consensus, Insufficient Evidence) and labels (Imperative or Conditional). To see more detail on the evidence from which the following recommendations were drawn, use the hyperlinks in the Supporting Evidence Section below.
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Recommendation(s)
SCI: Assessment: Energy Needs in the Acute Phase
If the patient with spinal cord injury is in the acute phase of spinal cord injury, the registered dietitian (RD) should assess energy needs by measuring energy expenditure. Patients with spinal cord injury have reduced metabolic activity due to denervated muscle. Actual energy needs are at least 10% below predicted needs. Indirect calorimetry is more accurate than estimation of energy needs in critically ill patients.
Rating: Strong
ConditionalSCI: Assessment: Energy Needs in the Acute Phase using Predictive Equations
If the patient with spinal cord injury is in the acute phase of spinal cord injury, and indirect calorimetry is not available, the registered dietitian may consider estimating energy needs with the Harris-Benedict formula, using admission weight, an injury factor of 1.2 and an activity factor of 1.1. No research was available to compare Harris-Benedict with other predictive equations in this population.
Rating: Weak
ConditionalSCI: Assessment: Energy Needs in the Rehabilitation Phase
If the patient with spinal cord injury is in the rehabilitation phase, the registered dietitian may estimate energy needs using 22.7kcal per kg body weight for patients with quadriplegia and 27.9kcal per kg for those with paraplegia. Patients with spinal cord injury have reduced metabolic activity due to denervated muscle.
Rating: Weak
Conditional-
Risks/Harms of Implementing This Recommendation
- Use of predictive equations rather than measured energy expenditure may result in under- or overfeeding persons with SCI and may lead to metabolic complications with subsequent poor outcomes such as obesity, pressure ulcer development, decreased ability to perform ADLs and transfers, heart disease and diabetes
- The weight of stabilization devices such as braces and halos should be considered when determining the body weight of persons with spinal cord injury to avoid overfeeding.
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Conditions of Application
Certain predictive equations were designed for application in mechanically ventilated patients.
The AARC Clinical Practice Guidelines (1994) recommend that measurements may be indicated in patients with the following conditions:
- Neuro trauma
- Paralysis
- COPD
- Acute pancreatitis
- Cancer with residual tumor
- Multiple trauma
- Amputations
- Patients with no accurate height or weight
- Long-term acute care (ventilator units)
- Severe sepsis
- Extreme obesity
- Severely hypermetabolic or hypometabolic patients
- Failure to wean.
The AARC Clinical Practice Guidelines (1994) also provide recommendations for hazards and complications, limitations of the procedures and infection control.
Hazards and Complications
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Short-term disconnection of a patient from the ventilator for connection to an indirect calorimetry machine may result in hypoxemia, bradycardia and patient discomfort
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Inappropriate calibration or system setup may result in erroneous results, causing incorrect patient management
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Isolation valves in calorimeters may increase circuit resistance and cause increased work of breathing or dynamic hyperinflation
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Inspiratory reservoirs may cause reduction in alveolar ventilation due to increased compressible volume of the breathing circuit
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Manipulation of the vent circuit may cause leaks that may lower alveolar ventilation.
Limitations of the Procedure
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Leaks in the ventilator circuit, endotracheal tube cuffs or uncuffed tubes, through chest tubes or bronchopleural fistula
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Peritoneal and hemo-dialysis procedures remove CO2 during the treatment and require a few hours after the treatment for acid-base to stabilize. Patients should not be measured during dialysis or for four hours after these dialysis treatments.
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Inaccurate measures may be caused by:
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Unstable O2 delivery, due to vent blender or mixing characteristics
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FIO2 above 60%
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Inability to separate inspired from expired gases, due to bias flow with intermittent mandatory ventilation systems
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Anesthetic gases other than O2, CO2 and nitrogen in the system
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Water vapor presence
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Inappropriate calibration
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Total circuit flow exceeding internal gas flow of calorimeter
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Leaks within the calorimeter
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Inadequate measurement length.
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Measures should be done by personnel trained in and with demonstrated and documented ability to calibrate, operate and maintain the calorimeter, having a general understanding of how mechanical ventilation works and recognizing calorimeter values within the normal physiologic range.
More frequent measures may be needed in patients with rapidly changing clinical course, as recognized by hemodynamic instability, spiking fevers, immediate post-operative status and ventilator weaning.
Infection Control
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Use standard precautions for contamination of blood and bodily fluids
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Appropriate use of barriers and hand washing
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Tubing to connect expired air from ventilator to indirect calorimetry should be disposed of or cleaned between patients
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Connections in the inspiratory limb of the circuit should be wiped clean between patients and equipment distal to the humidifier should be disposed of
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Bacteria filters may be used to protect equipment in inspire and expired lines.
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Potential Costs Associated with Application
Organizational costs are associated with equipment, maintenance of equipment, time required, staff and staff training required for measurement of energy expenditure in patients with spinal cord injury.
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Recommendation Narrative
Caloric Needs During the Acute Phase
- One neutral-quality narrative review found that indirect calorimetry is more accurate than predicting energy expenditure in acute-phase SCI patients (Houda, 1993)
- One neutral-quality longitudinal study (Barco et al, 2002) found that energy needs predicted by the Harris-Benedict equation, with an activity factor of 1.1 and an injury factor of 1.2, correlated closely with measured energy expenditure
- One neutral-quality longitudinal study (Rodriguez et al, 1997) found that predicting energy needs with the Harris-Benedict equation, with an activity factor of 1.2 and an injury factor of 1.6, resulted in excessive overfeeding.
- One neutral-quality case-control study concluded that a caloric intake of 1, 500kcals per day may be sufficient to prevent nutrition-related complications (Laven et al, 1989).
Caloric Needs During the Rehabilitation Phase
- Two case-control studies (one positive quality and one neutral quality) found that resting energy expenditure is significantly lower in SCI patients than in able-bodied subjects (Monroe et al, 1998; Buchholz et al, 2003)
- One positive-quality cross-sectional study found that caloric requirements generally represented 45% to 90% of caloric needs as predicted by equations. The reduction in energy needs was proportional to the amount of denervated muscle. Using current body weight, stable patients were found to require 23.4kcal per kg per day; quadriplegics required 22.7kcal per kg per day and paraplegics required 27.9kcal per kg per day (Cox et al, 1985).
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Recommendation Strength Rationale
- Lack of generizability across study designs
- Further research is needed to define calorie and protein needs of SCI patients
- Conclusion statements are Grade I and III.
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Minority Opinions
Consensus reached.
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Risks/Harms of Implementing This Recommendation
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Supporting Evidence
The recommendations were created from the evidence analysis on the following questions. To see detail of the evidence analysis, click the blue hyperlinks below (recommendations rated consensus will not have supporting evidence linked).
What are the caloric needs for patients during the acute and rehabilitation phases following spinal cord injury?
What is the most accurate method for determination of resting metabolic rate (RMR) in critically ill patients?-
References
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Buchholz AC, McGillivray CF, Pencharz PB. Physical activity levels are low in free-living adults with chronic paraplegia. Obes Res 2003;11(4):563-570
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Laven GT, Huang CT, DeVivo MJ, Stover SL, Kuhlemeier KV, Fine PR. Nutrition Status During the Acute Stage of Spinal Cord Injury. Arch Phys Med Rehabil 1989; 70: 277-282.
Monroe MB, Tataranni PA, Pratley R, Manore MM, Skinner JS, Ravussin E. Lower Daily Energy Expenditure as Measured by a Respiratory Chamber in Subjects with Spinal Cord Injury Compared with Control Subjects. Am J Clin Nutr, 1998; 68: 1223-1227.
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Flancbaum L, Choban PS, Sambucco S, Verducci J, Burge JC. Comparison of indirect calorimetry, the Fick method, and prediction equations in estimating the energy requirements of critically ill patients. Am J Clin Nutr 1999; 69(3):461-6.
Marson F, Martins MA, Coletto FA, Campos AD, Basile-Filho A. Correlation between oxygen consumption calculated using Fick's method and measured with indirect calorimetry in critically ill patients. Arq Bras Cardiol 2003;81:77-81.
Ogawa AM, Shikora SA, Burke LM, Heetderks-Cox JE, Bergren CT, Muskat PC. The thermodilution technique for measuring resting energy expenditure does not agree with indirect calorimetry for the critically ill patient. JPEN 1998; 22: 347-351.
Alexander E, Susla GM, Burstein AH, Brown DT, Ognibene FP. Retrospective evaluation of commonly used equations to predict energy expenditure in mechanically ventilated, critically ill patients. Pharmacotherapy. 2004; 24(12): 1,659-1,667.
Barak N, Wall-Alonso E, Sitrin MD. Evaluation of stress factors and body weight adjustments currently used to estimate energy expenditure in hospitalized patients. JPEN 2002; 26(4):231-8.
Brandi LS, Santini L, Bertolini R, Malacarne P, Casagli S, Baraglia AM. Energy expenditure and severity of injury and illness indices in multiple trauma patients. Crit Care Med 1999;27(12):2684-9.
Casati A, Colombo S, Leggieri C, Muttini S, Capocasa T, Gallioli G. Measured versus calculated energy expenditure in pressure support ventilated ICU patients. Minerva Anestesiol. 1996; 62 (5): 165-170.
Cheng CH, Chen CH, Wong Y, Lee BJ, Kan MN, Huang YC. Measured versus estimated energy expenditure in mechanically ventilated critically ill patients. Clin Nutr. 2002; 21 (2): 165-172.
Cutts ME, Dowdy RP, Ellersieck MR, Edes TE. Predicting energy needs in ventilator-dependent critically ill patients: effect of adjusting weight for edema or adiposity. Am J Clin Nutr 1997;66:1250-6.
Dickerson RN, Gervasio JM, Riley ML, Murrell JE, Hickerson WL, Kudsk KA, Brown RO. Accuracy of predictive methods to estimate resting energy expenditure of thermally-injured patients. JPEN. 2002; 26 (1): 17-29.
Donaldson-Andersen J, Fitzsimmons L. Metabolic requirements of the critically ill, mechanically ventilated trauma patient: measured versus predicted energy expenditure. Nutr Clin Pract 1998;13(1):25-31.
Faisy C, Guerot E, Diehl JL, Labrousse J, Fagon JY. Assessment of resting energy expenditure in mechanically ventilated patients. Am J Clin Nutr. 2003; 78: 241-249.
Ireton-Jones C, Jones JD. Improved equations for predicting energy expenditure in patients: the Ireton-Jones equations. Nutr Clin Pract 2002;17(1):29-31.
Jansen MMPM, Heymer F, Leusink JA, de Boer A. The quality of nutrition at an intensive care unit. Nutrition Research 2002;22(4):411-422.
MacDonald A, Hildebrandt L. Comparison of formulaic equations to determine energy expenditure in the critically ill patient. Nutrition 2003;19(3):233-9.
O'Leary-Kelley CM, Puntillo KA, Barr J, Stotts N, Douglas MK. Nutritional adequacy in patients receiving mechanical ventilation who are fed enterally. Am J Crit Care 2005; 14(3):222-31.
Ahmad A, Duerksen DR, Munroe S, Bistrian BR. An evaluation of resting energy expenditure in hospitalized, severely underweight patients. Nutrition 1999;15(5):384-8.
Alexander E, Susla GM, Burstein AH, Brown DT, Ognibene FP. Retrospective evaluation of commonly used equations to predict energy expenditure in mechanically ventilated, critically ill patients. Pharmacotherapy. 2004; 24(12): 1,659-1,667.
Brandi LS, Santini L, Bertolini R, Malacarne P, Casagli S, Baraglia AM. Energy expenditure and severity of injury and illness indices in multiple trauma patients. Crit Care Med 1999;27(12):2684-9.
Campbell CG, Zander E, Thorland W. Predicted vs measured energy expenditure in critically ill, underweight patients. Nutr Clin Pract 2005;20(2):276-80.
Cheng CH, Chen CH, Wong Y, Lee BJ, Kan MN, Huang YC. Measured versus estimated energy expenditure in mechanically ventilated critically ill patients. Clin Nutr. 2002; 21 (2): 165-172.
Compher C, Cato R, Bader J, Kinosian B. Harris-Benedict equations do not adequately predict energy requirements in elderly hospitalized African Americans. J National Med Assoc 2004;96(2):209-214.
Dickerson RN, Gervasio JM, Riley ML, Murrell JE, Hickerson WL, Kudsk KA, Brown RO. Accuracy of predictive methods to estimate resting energy expenditure of thermally-injured patients. JPEN. 2002; 26 (1): 17-29.
Donaldson-Andersen J, Fitzsimmons L. Metabolic requirements of the critically ill, mechanically ventilated trauma patient: measured versus predicted energy expenditure. Nutr Clin Pract 1998;13(1):25-31.
Faisy C, Guerot E, Diehl JL, Labrousse J, Fagon JY. Assessment of resting energy expenditure in mechanically ventilated patients. Am J Clin Nutr. 2003; 78: 241-249.
Flancbaum L, Choban PS, Sambucco S, Verducci J, Burge JC. Comparison of indirect calorimetry, the Fick method, and prediction equations in estimating the energy requirements of critically ill patients. Am J Clin Nutr 1999; 69(3):461-6.
Frankenfield D, Smith JS, Cooney RN. Validation of 2 approaches to predicting resting metabolic rate in critically ill patients. JPEN 2004;28(4):259-64.
Ireton-Jones C. Comparison of the metabolic response to burn injury in obese and nonobese patients. J Burn Care Rehabil 1997;18(1 Pt 1):82-5.
MacDonald A, Hildebrandt L. Comparison of formulaic equations to determine energy expenditure in the critically ill patient. Nutrition 2003;19(3):233-9.
Campbell CG, Zander E, Thorland W. Predicted vs measured energy expenditure in critically ill, underweight patients. Nutr Clin Pract 2005;20(2):276-80.
Cheng CH, Chen CH, Wong Y, Lee BJ, Kan MN, Huang YC. Measured versus estimated energy expenditure in mechanically ventilated critically ill patients. Clin Nutr. 2002; 21 (2): 165-172.
Dickerson RN, Gervasio JM, Riley ML, Murrell JE, Hickerson WL, Kudsk KA, Brown RO. Accuracy of predictive methods to estimate resting energy expenditure of thermally-injured patients. JPEN. 2002; 26 (1): 17-29.
Flancbaum L, Choban PS, Sambucco S, Verducci J, Burge JC. Comparison of indirect calorimetry, the Fick method, and prediction equations in estimating the energy requirements of critically ill patients. Am J Clin Nutr 1999; 69(3):461-6.
Frankenfield D, Smith JS, Cooney RN. Validation of 2 approaches to predicting resting metabolic rate in critically ill patients. JPEN 2004;28(4):259-64.
Ireton-Jones C. Comparison of the metabolic response to burn injury in obese and nonobese patients. J Burn Care Rehabil 1997;18(1 Pt 1):82-5.
MacDonald A, Hildebrandt L. Comparison of formulaic equations to determine energy expenditure in the critically ill patient. Nutrition 2003;19(3):233-9.
Alexander E, Susla GM, Burstein AH, Brown DT, Ognibene FP. Retrospective evaluation of commonly used equations to predict energy expenditure in mechanically ventilated, critically ill patients. Pharmacotherapy. 2004; 24(12): 1,659-1,667.
Frankenfield D, Smith JS, Cooney RN. Validation of 2 approaches to predicting resting metabolic rate in critically ill patients. JPEN 2004;28(4):259-64.
Ireton-Jones C, Jones JD. Improved equations for predicting energy expenditure in patients: the Ireton-Jones equations. Nutr Clin Pract 2002;17(1):29-31.
Frankenfield D, Smith JS, Cooney RN. Validation of 2 approaches to predicting resting metabolic rate in critically ill patients. JPEN 2004;28(4):259-64.
Barak N, Wall-Alonso E, Sitrin MD. Evaluation of stress factors and body weight adjustments currently used to estimate energy expenditure in hospitalized patients. JPEN 2002; 26(4):231-8.
Cutts ME, Dowdy RP, Ellersieck MR, Edes TE. Predicting energy needs in ventilator-dependent critically ill patients: effect of adjusting weight for edema or adiposity. Am J Clin Nutr 1997;66:1250-6.
Frankenfield D, Smith JS, Cooney RN. Validation of 2 approaches to predicting resting metabolic rate in critically ill patients. JPEN 2004;28(4):259-64.
Glynn CC, Greene GW, Winkler MF, Albina JE. Predictive versus measured energy expenditure using limits-of agreement analysis in hospitalized, obese patients. JPEN 1999;23:147-154.
Ireton-Jones C. Comparison of the metabolic response to burn injury in obese and nonobese patients. J Burn Care Rehabil 1997;18(1 Pt 1):82-5.
Ireton-Jones C, Jones JD. Improved equations for predicting energy expenditure in patients: the Ireton-Jones equations. Nutr Clin Pract 2002;17(1):29-31.
Frankenfield D, Smith JS, Cooney RN. Validation of 2 approaches to predicting resting metabolic rate in critically ill patients. JPEN 2004;28(4):259-64.
MacDonald A, Hildebrandt L. Comparison of formulaic equations to determine energy expenditure in the critically ill patient. Nutrition 2003;19(3):233-9.
MacDonald A, Hildebrandt L. Comparison of formulaic equations to determine energy expenditure in the critically ill patient. Nutrition 2003;19(3):233-9. -
References not graded in Academy of Nutrition and Dietetics Evidence Analysis Process
None.
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References