Critical Illness

CI: Best Method to Estimate RMR (2006)

• Assessment
  What is the most accurate method for determination of resting metabolic rate (RMR) in critically ill patients?

  • Conclusion
    Indirect calorimetry is the standard for determination of RMR in critically ill patients. When indirect calorimetry cannot be performed, predictive formulas may be necessary.

     

     

     

     

     

     

     
  • Grade: I
    • Grade I means there is Good/Strong evidence supporting the statement;
    • Grade II is Fair;
    • Grade III is Limited/Weak;
    • Grade IV is Expert Opinion Only;
    • Grade V is Not Assignable.
    • High (A) means we are very confident that the true effect lies close to that of the estimate of the effect;
    • Moderate (B) means we are moderately confident in the effect estimate;
    • Low (C) means our confidence in the effect estimate is limited;
    • Very Low (D) means we have very little confidence in the effect estimate.
    • Ungraded means a grade is not assignable.
  • Evidence Summary: In critically ill patients, what is the relationship between resting metabolic rate (RMR) and RMR predicted by the Fick equation?
    • Detail
    • Quality Rating Summary
      For a summary of the Quality Rating results, click here.
    • Worksheets
      • Brandi LS, Bertolini R, Santini L.  Calculated and measured oxygen consumption in mechanically ventilated surgical patients in the early post-operative period.  Eur J Anaesthesiol 1999;16(1):53-61. 
      • Epstein CD, Peerless JR, Martin JE, Malangoni MA. Comparison of methods of measurements of oxygen consumption in mechanically ventilated patients with multiple trauma: The Fick method vs. indirect calorimetry. Crit Care Med. 2000; 28(5): 1,363-1,369. 
      • 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. 
  • Evidence Summary: In critically ill patients, what is the relationship between resting metabolic rate (RMR) and RMR predicted by the Harris-Benedict equation (with stress and activity factors)?
    • Detail
    • Quality Rating Summary
      For a summary of the Quality Rating results, click here.
    • Worksheets
      • 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. 
  • Evidence Summary: In critically ill patients, what is the relationship between resting metabolic rate (RMR) and RMR predicted by the Harris-Benedict equation (without adjustments)?
    • Detail
    • Quality Rating Summary
      For a summary of the Quality Rating results, click here.
    • Worksheets
      • 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. 
  • Evidence Summary: In critically ill patients, what is the relationship between resting metabolic rate (RMR) and RMR predicted by the Ireton-Jones 1992 equations?
    • Detail
    • Quality Rating Summary
      For a summary of the Quality Rating results, click here.
    • Worksheets
      • 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. 
  • Evidence Summary: In critically ill patients, what is the relationship between resting metabolic rate (RMR) and RMR predicted by the Ireton-Jones 1997 equations?
    • Detail
    • Quality Rating Summary
      For a summary of the Quality Rating results, click here.
    • Worksheets
      • 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.
  • Evidence Summary: In critically ill patients, what is the relationship between resting metabolic rate (RMR) and RMR predicted by the Mifflin-St. Jeor equation?
    • Detail
    • Quality Rating Summary
      For a summary of the Quality Rating results, click here.
    • Worksheets
      • 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. 
  • Evidence Summary: In critically ill patients, what is the relationship between resting metabolic rate (RMR) and RMR predicted by the Penn State equation?
    • Detail
    • Quality Rating Summary
      For a summary of the Quality Rating results, click here.
    • Worksheets
      • 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. 
  • Evidence Summary: In critically ill patients, what is the relationship between resting metabolic rate (RMR) and RMR predicted by the Swinamer equation?
    • Detail
    • Quality Rating Summary
      For a summary of the Quality Rating results, click here.
    • Worksheets
      • MacDonald A, Hildebrandt L.  Comparison of formulaic equations to determine energy expenditure in the critically ill patient.  Nutrition 2003;19(3):233-9. 
  • Evidence Summary: What is the most accurate predictive equation for estimating energy needs in critically ill patients with obesity?
    • Detail
    • Quality Rating Summary
      For a summary of the Quality Rating results, click here.
    • Worksheets
      • 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.
  • Search Plan and Results: CI: Determination of RMR 2006
     
  What is the most accurate predictive equation for estimating energy needs in critically ill patients with obesity?

  • Conclusion
    Six studies including individuals with obesity, studied the application of several predictive equations and the use of actual or adjusted body weight.  One study, based on hospitalized patients, reported that the Harris-Benedict equation using actual weight multiplied by a factor of 1.2 (60% of subjects predicted within 10% of RMR) or an adjusted weight multiplied by a factor of 1.3 (67% of subjects predicted within 10% of RMR) resulted in the most accurate predictions.  A second study, based on critically ill, mechanically ventilated patients, reports that the Penn State 2003a equation predicts within 10% of RMR in 61% of subjects, the Penn State 1998 equation predicts within 10% of RMR in 67% of subjects, and the Ireton-Jones, 1992 equations predict within 10% of RMR in 72% of subjects.  Further research is needed in critically ill patients with obesity.

     
  • Grade: III
    • Grade I means there is Good/Strong evidence supporting the statement;
    • Grade II is Fair;
    • Grade III is Limited/Weak;
    • Grade IV is Expert Opinion Only;
    • Grade V is Not Assignable.
    • High (A) means we are very confident that the true effect lies close to that of the estimate of the effect;
    • Moderate (B) means we are moderately confident in the effect estimate;
    • Low (C) means our confidence in the effect estimate is limited;
    • Very Low (D) means we have very little confidence in the effect estimate.
    • Ungraded means a grade is not assignable.
  • Evidence Summary: What is the most accurate predictive equation for estimating energy needs in critically ill patients with obesity?
    • Detail
    • Quality Rating Summary
      For a summary of the Quality Rating results, click here.
    • Worksheets
      • 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.
  • Search Plan and Results: CI: Determination of RMR 2006