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Clinical accuracy of the MedGem™ indirect calorimeter for measuring resting energy expenditure in cancer patients

Abstract

Objective

To compare, in patients with cancer and in healthy subjects, measured resting energy expenditure (REE) from traditional indirect calorimetry to a new portable device (MedGem™) and predicted REE.

Design

Cross-sectional clinical validation study.

Setting

Private radiation oncology centre, Brisbane, Australia.

Subjects

Cancer patients (n=18) and healthy subjects (n=17) aged 37–86 y, with body mass indices ranging from 18 to 42 kg/m2.

Interventions

Oxygen consumption (VO2) and REE were measured by VMax229 (VM) and MedGem (MG) indirect calorimeters in random order after a 12-h fast and 30-min rest. REE was also calculated from the MG without adjustment for nitrogen excretion (MGN) and estimated from Harris–Benedict prediction equations. Data were analysed using the Bland and Altman approach, based on a clinically acceptable difference between methods of 5%.

Results

The mean bias (MGN–VM) was 10% and limits of agreement were –42 to 21% for cancer patients; mean bias −5% with limits of −45 to 35% for healthy subjects. Less than half of the cancer patients (n=7, 46.7%) and only a third (n=5, 33.3%) of healthy subjects had measured REE by MGN within clinically acceptable limits of VM. Predicted REE showed a mean bias (HB–VM) of −5% for cancer patients and 4% for healthy subjects, with limits of agreement of −30 to 20% and −27 to 34%, respectively.

Conclusions

Limits of agreement for the MG and Harris Benedict equations compared to traditional indirect calorimetry were similar but wide, indicating poor clinical accuracy for determining the REE of individual cancer patients and healthy subjects.

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References

  • Barak N, Wall-Alonso E & Sitrin MD (2002): Evaluation of stress factors and body weight adjustments currently used to estimate energy expenditure in hospitalized patients. J. Parenter. Enteral. Nutr. 26, 231–238.

    Article  Google Scholar 

  • Bauer J, Reeves MM & Capra S (2004): The agreement between measured and predicted resting energy expenditure in patients with pancreatic cancer—a pilot study. JOP. J. Pancreas (Online) 5, 32–40.

    Google Scholar 

  • Bland JM & Altman DG (1986): Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1, 307–310.

    Article  CAS  Google Scholar 

  • Branson RD (1990): The measurement of energy expenditure: instrumentation, practical considerations, and clinical application. Respir. Care 35, 640–659.

    Google Scholar 

  • Bursztein S, Saphar P, Singer P & Elwyn DH (1989): A mathematical analysis of indirect calorimetry measurements in acutely ill patients. Am. J. Clin. Nutr. 50, 227–230.

    Article  CAS  Google Scholar 

  • Daly JM, Heymsfield SB, Head CA, Harvey LP, Nixon DW, Katzeff H & Grossman GD (1985): Human energy requirements: overestimation by widely used prediction equation. Am. J. Clin. Nutr. 42, 1170–1174.

    Article  CAS  Google Scholar 

  • Demark-Wahnefried W, Peterson BL, Winer EP, Marks L, Aziz N, Marcom PK, Blackwell K & Rimer BK (2001): Changes in weight, body composition, and factors influencing energy balance among premenopausal breast cancer patients receiving adjuvant chemotherapy. J. Clin. Oncol. 19, 2381–2389.

    Article  CAS  Google Scholar 

  • Falconer JS, Fearon KC, Plester CE, Ross JA & Carter DC (1994): Cytokines, the acute-phase response, and resting energy expenditure in cachectic patients with pancreatic cancer. Ann. Surg. 219, 325–331.

    Article  CAS  Google Scholar 

  • Fearon KC, Hansell DT, Preston T, Plumb JA, Davies J, Shapiro D, Shenkin A, Calman KC & Burns HJ (1988): Influence of whole body protein turnover rate on resting energy expenditure in patients with cancer. Cancer Res. 48, 2590–2595.

    CAS  PubMed  Google Scholar 

  • Feurer ID & Mullen JL (1986): Bedside measurement of resting energy expenditure and respiratory quotient via indirect calorimetry. Nutr. Clin. Pract. 1, 43–49.

    Article  Google Scholar 

  • Flancbaum L, Choban PS, Sambucco S, Verducci J & Burge JC (1999): Comparison of indirect calorimetry, the Fick method, and prediction equations in estimating the energy requirements of critically ill patients. Am. J. Clin. Nutr. 69, 461–466.

    Article  CAS  Google Scholar 

  • Garby L & Lammert O (1984): Within-subjects between-days-and-weeks variation in energy expenditure at rest. Hum. Nutr. Clin. Nutr. 38, 395–397.

    CAS  PubMed  Google Scholar 

  • Glynn CC, Greene GW, Winkler MF & Albina JE (1999): Predictive versus measured energy expenditure using limits-of-agreement analysis in hospitalized, obese patients. J. Parenter. Enteral. Nutr. 23, 147–154.

    Article  CAS  Google Scholar 

  • Hamwi GJ (1964): Therapy: changing dietary concepts. In: Diabetes Mellitus: Diagnosis and Treatment, ed. Danowski TS, Vol. 1, pp 73–78. New York, American Diabetes Association.

    Google Scholar 

  • Hansell DT, Davies JW & Burns HJ (1986): The relationship between resting energy expenditure and weight loss in benign and malignant disease. Ann. Surg. 203, 240–245.

    Article  CAS  Google Scholar 

  • Harris JA & Benedict FG (1919): A Biometric Study of Basal Metabolism in Man. Washington DC: Carnegie Institution of Washington.

    Google Scholar 

  • HealtheTech (2002): MedGem:Operator's Manual. Golden, CO: HealtheTech Inc.

  • Henry CJ, Hayter J & Rees DG (1989): The constancy of basal metabolic rate in free-living male subjects. Eur. J. Clin. Nutr. 43, 727–731.

    CAS  PubMed  Google Scholar 

  • Heymsfield SB (2002): Heat and life: the ongoing scientific odyssey. J. Parenter. Enteral. Nutr. 26, 319–332.

    Article  Google Scholar 

  • Jequier E & Schutz Y (1983): Long-term measurements of energy expenditure in humans using a respiration chamber. Am. J. Clin. Nutr. 38, 989–998.

    Article  CAS  Google Scholar 

  • Leenders KL (1994): PET: blood flow and oxygen consumption in brain tumors. J. Neurooncol. 22, 269–273.

    Article  CAS  Google Scholar 

  • McClave SA, Lowen CC, Kleber MJ, McConnell JW, Jung LY & Goldsmith LJ (2003a): Clinical use of the respiratory quotient obtained from indirect calorimetry. J. Parenter. Enteral. Nutr. 27, 21–26.

    Article  Google Scholar 

  • McClave SA, Spain DA, Skolnick JL, Lowen CC, Kieber MJ, Wickerham PS, Vogt JR & Looney SW (2003b): Achievement of steady state optimizes results when performing indirect calorimetry. J. Parenter. Enteral. Nutr. 27, 16–20.

    Article  Google Scholar 

  • McLean JA & Tobin G (1987): Animal and Human Calorimetry. Cambridge: Cambridge University Press.

    Google Scholar 

  • Nieman DC, Trone GA & Austin MD (2003): A new handheld device for measuring resting metabolic rate and oxygen consumption. J. Am. Dietet. Assoc. 103, 588–592.

    Article  Google Scholar 

  • Platz EA (2002): Energy imbalance and prostate cancer. J. Nutr. 132, 3471S–3481S.

    Article  CAS  Google Scholar 

  • Reeves MM & Capra S (2003): Predicting energy requirements in the clinical setting: are current methods evidence based? Nutr. Rev. 61, 143–151.

    Article  Google Scholar 

  • Reeves MM, Davies PSW, Bauer J & Battistutta D (2004): Reducing the time period of steady state does not affect the accuracy of energy expenditure measurements by indirect calorimetry. J. Appl. Physiol. 97, 130–134.

    Article  Google Scholar 

  • Segal K (1987): Comparison of indirect calorimetric measurements of resting energy expenditure with a ventilated hood, face mask, and mouthpiece. Am. J. Clin. Nutr. 45, 1420–1423.

    Article  CAS  Google Scholar 

  • Siervo M, Boschi V & Falconi C (2003): Which REE prediction equation should we use in normal-weight, overweight and obese women? Clin. Nutr. 22, 193–204.

    Article  CAS  Google Scholar 

  • Soares MJ, Sheela ML, Kurpad AV, Kulkarni RN & Shetty PS (1989): The influence of different methods on basal metabolic rate measurements in human subjects. Am. J. Clin. Nutr. 50, 731–736.

    Article  CAS  Google Scholar 

  • Soares MJ & Shetty PS (1986): Intra-individual variations in resting metabolic rates of human subjects. Hum. Nutr. Clin. Nutr. 40, 365–369.

    CAS  PubMed  Google Scholar 

  • Taaffe DR, Thompson J, Butterfield G & Marcus R (1995): Accuracy of equations to predict basal metabolic rate in older women. J. Am. Diet. Assoc. 95, 1387–1392.

    Article  CAS  Google Scholar 

  • Toth MJ (1999): Energy expenditure in wasting diseases: current concepts and measurement techniques. Curr. Opin. Clin. Nutr. Metab. Care. 2, 445–451.

    Article  CAS  Google Scholar 

  • Weir JB DeV (1949): New methods for calculating metabolic rate with special reference to protein metabolism. J. Physiol. 109, 1–9.

    Article  Google Scholar 

  • Weissman C, Askanazi J, Milic-Emili J & Kinney JM (1984): Effect of respiratory apparatus on respiration. J. Appl. Physiol. 57, 475–480.

    Article  CAS  Google Scholar 

Download references

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Correspondence to M M Reeves.

Additional information

Guarantor: M Reeves.

Contributors: MMR was responsible for writing the manuscript, initiated and designed the study, carried out data collection, data analysis, interpretation and discussion of results. SC initiated the study and assisted in the design of the study. JB contributed to the study design and assisted with data collection. PSWD and DB contributed to the study design, data analysis, interpretation and discussion of results and manuscript preparation.

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Reeves, M., Capra, S., Bauer, J. et al. Clinical accuracy of the MedGem™ indirect calorimeter for measuring resting energy expenditure in cancer patients. Eur J Clin Nutr 59, 603–610 (2005). https://doi.org/10.1038/sj.ejcn.1602114

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