CI: Best Method to Estimate RMR (2010)
Predictive Equation Formulas Used in Critically Ill Adults
Brandi Equation
HBE(0.96) + HR(7) + VE(48) – 702
VE = expired minute ventilation
Faisy Equation
W (8)+H (14)+VE (32)+T (94)-4,834
Equation uses weight (W) in kilograms (kg) and height (H) in centimeters (cm). VE is expired minute ventilation and T is body temperature in degrees centigrade.
Fick Equation
RMR=CO x Hb(SaO2-SvO2)95.18
Equation uses cardiac output (CO) in liters per minute (L/min), hemoglobin concentration (Hb) in mg/L, oxygen saturation of arterial blood (SaO2) and oxygen saturation of mixed venous blood (SvO2).
Harris-Benedict Equations (HBE)
Men: RMR = 66.47 + 13.75 (W) + 5 (H) - 6.76 (A)
Women: RMR = 655.1 + 9.56 (W) + 1.7 (H) - 4.7 (A)
Equation uses weight (W) in kilograms (kg), height (H) in centimeters (cm), and age (A) in years.
Ireton-Jones, 1992 Equations
Spontaneously breathing IJEE (s) = 629 - 11 (A) + 25 (W) - 609 (O)
Ventilator dependent IJEE (v) = 1925 - 10 (A) + 5 (W) + 281 (S) + 292 (T) + 851 (B)
Equations use age (A) in years, body weight (W) in kilograms (kg), sex (S, male = 1, female = 0), diagnosis of trauma (T, present = 1, absent = 0), diagnosis of burn (B, present = 1, absent = 0), obesity >30% above initial body weight from 1,959 Metropolitan Life Insurance tables or body mass index (BMI) more than 27kg/m2 (present = 1, absent = 0).
Ireton-Jones, 1997 Equations
Spontaneously breathing IJEE (s) = 629 - 11 (A) + 25 (W) - 609 (O)
Ventilator dependent IJEE (v) = 1784 - 11 (A) + 5 (W) + 244 (S) + 239 (T) + 804 (B)
Equations use age (A) in years, body weight (W) in kilograms (kg), sex (S, male=1, female=0), diagnosis of trauma (T, present=1, absent=0), diagnosis of burn (B, present=1, absent=0), obesity more than 30% above initial body weight from 1959 Metropolitan Life Insurance tables or BMI higher than 27kg/m2 (present=1, absent=0).
Penn State Equations (PSU)
- PSU(1998) - Invalidated in 2009
RMR = HBE(1.1) + VE (32) + Tmax (140) - 5340
[use adjusted body weight in HBE for patients with BMI>30kg/m2]
RMR = HBE(0.85) + VE (33) + Tmax (175) - 6433
[use actual weight in all patients]
RMR = Mifflin(0.96) + VE (31) + Tmax (167) - 6212
RMR = Mifflin(0.71) + VE (64) + Tmax(85) - 3085
Mifflin-St. Jeor Equation (MSJE)
Men: RMR = (9.99 X weight) + (6.25 X height) – (4.92 X age) + 5
Women: RMR = (9.99 X weight) + (6.25 X height) – (4.92 X age) – 161
Equations use weight in kilograms (kg), height in centimeters (cm).
Swinamer Equation
EE = 945 (BSA) - 6.4 (age) + 108 (T) + 24.2 (breaths per minute) + 81.7 (VT) - 4,349
Equation uses body surface area (BSA) in squared meters (m2), temperature (T) in degrees Celsius, and tidal volume (VT) in liters per minute (L per minute).
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Assessment
If indirect calorimetry is unavailable or impractical, what is the best way to estimate resting metabolic rate (RMR) in non-obese adult critically ill patients?
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Conclusion
Twenty-two papers (17 positive and five neutral research quality studies) evaluating nine predictive equations were reviewed for this evidence analysis question. Four equations were precise and unbiased in the non-obese patients. These equations and their accuracy rates in patients younger 60 years and those 60 years or older, respectively, were: PSU(2003b) (69%, 77%); Brandi equation (61%, 61%), MSJE x 1.25 (54%, 54%) and Faisy equation (65%, 37%).
Click here to see all Predictive Equation Formulas.
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Grade: II
- 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.
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Evidence Summary: If indirect calorimetry is unavailable or impractical, what is the best way to estimate resting metabolic rate (RMR) in non-obese adult critically ill patients?
- 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.
- Boullata J, Williams J, Cottrell F, Hudson L, Compher C. Accurate determination of energy needs in hospitalized patients. J Am Diet Assoc. 2007; 107: 393-401.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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 DC, Coleman A, Alam S, Cooney R. Analysis of estimation methods for resting metabolic rate in critically ill adults. J Parenter Enteral Nutr. 2009; 33: 27.
- 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.
- 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.
- 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.
- 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.
- 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.
- Savard JF. Faisy C. Lerolle N. Guerot E. Diehl JL. Fagon JY. Validation of a predictive method for an accurate assessment of resting energy expenditure in medical mechanically ventilated patients. Critical Care Medicine. 2008; 36(4): 1,175-1,183.
- Stucky CC, Moncure M, Hise M, Gossage CM, Northrop D. How accurate are resting energy expenditure prediction equations in obese trauma and burn patients? J Parenter Enteral Nutr. 2008 Jul-Aug; 32(4): 420-426.
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Search Plan and Results: CI: Determination of RMR 2009
If indirect calorimetry is unavailable or impractical, what is the best way to estimate resting metabolic rate (RMR) in obese adult critically ill patients?
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Conclusion
Eight studies (five positive quality and three neutral quality) compared measured resting metabolic rate (RMR) with RMR predicted by several equations in critically ill patients with obesity. The Penn State equation [PSU(2003b)] worked best and predicted RMR with 70% accuracy in obese patients. For a subset of obese critically ill patients ≥60 years old, a modified Penn State equation [PSU(2010)] predicted RMR with 74% accuracy. All other predictive equations tested had lower accuracy rates.
Click here to see all Predictive Equation Formulas.
-
Grade: II
- 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: If indirect calorimetry is unavailable or impractical, what is the best way to estimate resting metabolic rate (RMR) in obese adult critically ill patients?
- Detail
- Quality Rating Summary
For a summary of the Quality Rating results,
click here.
- Worksheets
- Anderegg BA, Worrall C, Barbour E, Simpson KN, Delegge M. Comparison of resting energy expenditure prediction methods with measured resting energy expenditure in obese, hospitalized adults. J Parenter Enteral Nutr. 2009 Mar-Apr; 33(2): 168-175.
- Boullata J, Williams J, Cottrell F, Hudson L, Compher C. Accurate determination of energy needs in hospitalized patients. J Am Diet Assoc. 2007; 107: 393-401.
- 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 David. Validation of an equation for resting metabolic rate in older obese critically ill patients. JPEN. 2010 (in press).
- Frankenfield DC, Coleman A, Alam S, Cooney R. Analysis of estimation methods for resting metabolic rate in critically ill adults. J Parenter Enteral Nutr. 2009; 33: 27.
- 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, Jones JD. Improved equations for predicting energy expenditure in patients: the Ireton-Jones equations. Nutr Clin Pract 2002;17(1):29-31.
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Search Plan and Results: CI: Determination of RMR 2009