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Cited by 97Clinical Nutrition and GastroenterologyBody Composition Measurement TechniquesDietetics, Nutrition, and Education

Predicting Energy Requirements in the Clinical Setting: Are Current Methods Evidence Based?

Reeves, Marina M., Capra, Sandra·2003·Nutrition Reviews
DOI 10.1301/nr.2003.apr.143-151
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Abstract

Estimating energy requirements is necessary in clinical practice when indirect calorimetry is impractical. This paper systematically reviews current methods for estimating energy requirements. Conclusions include: there is discrepancy between the characteristics of populations upon which predictive equations are based and current populations; tools are not well understood; and patient care can be compromised by inappropriate application of the tools. Data comparing tools and methods are presented and issues for practitioners are discussed.

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  • Energy requirements in polymorbid medical inpatients can be estimated using indirect calorimetry, a published prediction equation or a weight-based formula, although the accuracy of prediction equations in this population is low.

    “Energy requirements in polymorbid medical inpatients can be estimated using indirect calorimetry (IC), a published prediction equation or a weight-based formula, although the accuracy of prediction equations in this population is low.”

    From ESPEN guideline on nutritional support for polymorbid medical inpatients (2023) · cites this paper as [65]

    The Introduction describes indirect calorimetry and prediction equations, General Estimates describes weight-based formulas, and Implication for Current Practice says current prediction methods do not determine energy requirements accurately. The review discusses clinical and hospitalized patients, but does not establish the accuracy of prediction equations specifically in polymorbid medical inpatients. Page numbers were not supplied in our copy. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • No single validated method for estimating energy requirements exists, and the evidence-base for all prediction methods currently in use is poor.

    “No single, validated method for estimating requirements exists, and the evidence-base for all prediction methods currently in use is poor [65].”

    From ESPEN guideline on nutritional support for polymorbid medical inpatients (2023) · cites this paper as [65]

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Research works printed but not linked: 52

  1. Coss-Bu JA, Jefferson LS, Walding D, David Y, Smith EO, Klish WJ. Resting energy expenditure in children in a pediatric intensive care unit: compari- son of Harris-Benedict and Talbot predictions with indirect calorimetry values. Am J Clin Nutr. 1998;67: 74 -80.
  2. 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;69:461-466.
  3. Gibney ER. Energy expenditure in disease: time to revisit? Proc Nutr Soc. 2000;59:199 -207.
  4. White MS. The calculation of the energy require- ment of a critically ill child: a dietitians' survey. Aus J Nutr Diet. 1998;55:82-86.
  5. Jequier E, Schutz Y. Long-term measurements of energy expenditure in humans using a respiration chamber. Am J Clin Nutr. 1983;38:989 -998.
  6. Soares MJ, Sheela ML, Kurpad AV, Kulkarni RN, Shetty PS. The in uence of different methods on basal metabolic rate measurements in human sub- jects. Am J Clin Nutr. 1989;50:731-736.
  7. Wong WW, Butte NF, Hergenroeder AC, Hill RB, Stuff JE, Smith EO. Are basal metabolic rate predic- tion equations appropriate for female children and adolescents? J Appl Physiol. 1996;81:2407 -2414.
  8. Ravussin E, Bogardus C. Relationship of genetics, age, and physical tness to daily energy expendi- ture and fuel utilization. Am J Clin Nutr. 1989;49: 968 -975.
  9. Polgar S, Thomas SA, eds. Introduction to Research in the Health Sciences. 3rd ed. Edinburgh: Churchill Livingston; 1995:348.
  10. Franken eld DC, Muth ER, Rowe WA. The Harris- Benedict studies of human basal metabolism: his- tory and limitations. J Am Diet Assoc. 1998;98:439 - 445.
  11. Benedict FG. Basal metabolism data on normal men and women (series II) with some considerations on the use of prediction standards. Am J Physiol. 1928; 85:607-620.
  12. Case KO, Brahler CJ, Heiss C. Resting energy ex- penditures in Asian women measured by indirect calorimetry are lower than expenditures calculated from prediction equations. J Am Diet Assoc. 1997; 97:1288 -1292.
  13. Daly JM, Heyms eld SB, Head CA, et al. Human energy requirements: overestimation by widely used prediction equation. Am J Clin Nutr. 1985;42: 1170 -1174.
  14. Foster GD, Wadden TA, Mullen JL, et al. Resting energy expenditure, body composition, and excess weight in the obese. Metabolism. 1988;37:467-472.
  15. Owen OE, Holup JL, D'Alessio DA, et al. A reap- praisal of the caloric requirements of men. Am J Clin Nutr. 1987;46:875-885.
  16. Owen OE, Kavle E, Owen RS, et al. A reappraisal of caloric requirements in healthy women. Am J Clin Nutr. 1986;44:1-19.
  17. Scho eld WN. Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr. 1985;39:5-41.
  18. Vinken AG, Bathalon GP, Sawaya AL, Dallal GE, Tucker KL, Roberts SB. Equations for predicting the energy requirements of healthy adults aged 18 -81 y. Am J Clin Nutr. 1999;69:920 -926.
  19. Webb P, Sangal S. Sedentary daily expenditure: a base for estimating individual energy requirements. Am J Clin Nutr. 1991;53:606 -611.
  20. Soares MJ, Francis DG, Shetty PS. Predictive equa- tions for basal metabolic rates of Indian males. Eur J Clin Nutr. 1993;47:389 -394.
  21. Toth MJ. Energy expenditure in wasting diseases: current concepts and measurement techniques. Curr Opin Clin Nutr Metab Care. 1999;2:445-451.
  22. Toth MJ, Poehlman ET. Energetic adaptation to chronic disease in the elderly. Nutr Rev. 2000;58: 61-66.
  23. Pi-Sunyer FX. Overnutrition and undernutrition as modi ers of metabolic processes in disease states. Am J Clin Nutr. 2000;72:533S -537S.
  24. Ireton-Jones CS, Turner WW Jr, Liepa GU, Baxter CR. Equations for the estimation of energy expen- ditures in patients with burns with special reference to ventilatory status. J Burn Care Rehabil. 1992;13: 330 -333.
  25. Curreri P. Metabolic and nutritional aspects of ther- mal injury. Burns. 1975;2:16 -21.
  26. Allard J, Pichard C, Hoshino E. Validation of a new formula for calculating the energy requirements of burn patients. JPEN. 1990;14:115-118.
  27. White MS, Shepherd RW, McEniery JA. Energy ex- penditure in 100 ventilated, critically ill children: improving the accuracy of predictive equations. Crit Care Med. 2000;28:2307 -2312.
  28. Swinamer DL, Grace MG, Hamilton SM, Jones RL, Roberts P, King EG. Predictive equation for assess- ing energy expenditure in mechanically ventilated critically ill patients. Crit Care Med. 1990;18:657- 661.
  29. Franken eld DC, Omert LA, Badellino MM, et al. Correlation between measured energy expenditure and clinically obtained variables in trauma and sep- sis patients. JPEN. 1994;18:398 -403.
  30. Duke JH, Jorgensen SB, Broell JR, Long CL, Kinney JM. Contribution of protein to caloric expenditure following injury. Surgery. 1970;68:168 -174.
  31. Long CL. Energy balance and carbohydrate metab- olism in infection and sepsis. Am J Clin Nutr. 1977; 30:1301-1310.
  32. Long CL, Schaffel N, Geiger JW, Schiller WR, Blake- more WS. Metabolic response to injury and illness: estimation of energy and protein needs from indi- rect calorimetry and nitrogen balance. JPEN. 1979; 3:452-456.
  33. Mahan LK, Escott-Stump S, eds. Krause's Food, Nutrition, & Diet Therapy. 10th ed. Philadelphia: W.B. Saunders Company; 2000.
  34. Elia M. Arti cial nutritional support. Med Int. 1990; 82:3392-3396.
  35. Shils ME, Olson JA, Shike M, Ross AC, eds. Modern Nutrition in Health and Disease. 9th ed. Baltimore: Lippincott Williams & Wilkins; 1999.
  36. Thomas B, ed. Manual of Dietetic Practice. 3rd ed. Oxford: Blackwell Science; 2001.
  37. Fleish A. Le metabolisme basal standard et sa de- termination au moyen du 'metabocalculator.' Helv Med Acta. 1951;18:23-44.
  38. A.S.P.E.N. Board of Directors and The Clinical Guidelines Task Force. Guidelines for the use of parenteral and enteral nutrition in adult and pediat- ric patients. JPEN. 2002;26:1-138.
  39. Alpers D, Stenson W, Bier D. Manual of Nutritional Therapeutics. Philadelphia: Lippincott Williams & Wilkins; 2002.
  40. Lawrence M. Predicting energy requirements: is en- ergy expenditure proportional to the BMR or to body weight? An analysis of data collected in rural Gambian women. Eur J Clin Nutr. 1988;42:919 - 927.
  41. Ahmad A, Duerksen DR, Munroe S, Bistrian BR. An evaluation of resting energy expenditure in hospi- talized, severely underweight patients. Nutrition. 1999;15:384 -388.
  42. Hunter DC, Jaksic T, Lewis D, Benotti PN, Black- burn Gl, Bistrian BR. Resting energy expenditure in the critically ill: estimations versus measurement. Br J Surg. 1988;75:875-878.
  43. Matarese LE, Gottschlich MM, eds. Contemporary Nutrition Support Practice: A Clinical Guide. 1st ed. Philadelphia: W.B. Saunders Company; 1998.
  44. Cairney J, Wade TJ. Correlates of body weight in the 1994 National Population Health Survey. Int J Obesity. 1998;22:584 -591.
  45. Kuczmarski RJ, Flegal KM, Campbell SM, Johnson CL. Increasing prevalence of overweight among US adults. The National Health and Nutrition Examina- tion Surveys, 1960 to 1991. JAMA. 1994;272:205 - 211.
  46. Shetty PS, Henry CJ, Black AE, Prentice AM. En- ergy requirements of adults: an update on basal metabolic rates (BMRs) and physical activity levels (PALs). Eur J Clin Nutr. 1996;50:S11-S23.
  47. Warwick PM. Predicting food energy requirements from estimates of energy expenditure. Aust J Nutr Diet. 1989;46:S3-S28.
  48. Glynn CC, Greene GW, Winkler MF, Albina JE. Predictive versus measured energy expenditure us- ing limits-of-agreement analysis in hospitalized, obese patients. JPEN. 1999;23:147-154.
  49. Hirano KM, Heiss CJ, Olson KE, Beerman KA, Brahler CJ. A comparison of calculated and mea- sured resting energy expenditure in obese women. Top Clin Nutr. 2001;16:61-69, 85-88.
  50. Halpern SL, ed. Quick Reference to Clinical Nutri- tion: A Guide for Physicians. 2nd ed. Philadelphia: J.B.Lippincott Company; 1987.
  51. Astrup A, Thorbek G, Lind J, Isaksson B. Prediction of 24-h energy expenditure and its components from physical characteristics and body composition in normal-weight humans. Am J Clin Nutr. 1990;52: 777-783.
  52. Durnin JV. Energy requirements: general principles. Eur J Clin Nutr. 1996;50:S2-S10.

Cited by

Sorted by citations

Authors
Reeves, M. M., & Capra, S.
Affiliations
Queensland University of Technology (AU)
ORCID
Venue
Nutrition Reviews
Publisher
Oxford University Press (OUP)
Published
2003-04-01
Volume
61
Issue
4
Pages
143-151
ISSN
  • 0029-6643 (ISSN-L)
  • 1753-4887
DOI
10.1301/nr.2003.apr.143-151
OpenAlex
W2167722121
Cited by
97
References
4
Citations by year
2026: 1 · 2025: 1 · 2024: 1 · 2023: 2 · 2022: 2 · 2021: 3 · 2020: 5 · 2019: 3 · 2018: 4 · 2017: 6 · 2016: 2 · 2015: 8 · 2014: 5 · 2013: 5 · 2012: 6
FWCI
0.67
Type
journal article
Language
en
Open access
closed
Locations
  • Nutrition Reviews (publishedVersion)
  • PubMed (publishedVersion)
Funders
British Dietetic Association
Topics
  • Health Sciences › Nursing › Nutrition and Dietetics › Clinical Nutrition and Gastroenterology
  • Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
  • Health Sciences › Health Professions › Health Information Management › Dietetics, Nutrition, and Education
Keywords
energy requirements, load forecasting, prediction equations, clinical nutrition, indirect calorimetry, evidence-based practice, energy expenditure estimation
MeSH terms
Adult, Basal Metabolism, Female, Humans, Male, Predictive Value of Tests, Evidence-Based Medicine

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