Evaluation of Resting Energy Expenditure in Critically Surgical Patients Undergoing Mechanical Ventilation_CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Authors：

CHEN Hong , SUN Jiabang , LI Fei , JIA Jianguo.

Department of General Surgery, Xuanwu Hospital of Capital Medical University, Beijing 100053, China;

Corresponding author：

Keywords：

Energy expenditure; Indirect calorimetry; Mechanical ventilation; Critically ill patient

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ObjectiveTo compare the indirect calorimetry (IC) measured resting energy expenditure (MREE) with adjusted Harris-Benedict formula calculating resting energy expenditure (CREE) in the mechanically ventilated surgical critically ill patients and to evaluate the relationship between the resting energy expenditure (REE) with the severity of illness. MethodsTwenty-one patients undergonging mechanical ventilation for critical illness in the intensive care unit of general surgery between August 2008 and February 2010 were included in this study. Data during the study period of nutrition support were collected for computation of the severity of critical illness by acute physiology and chronic health evaluation Ⅱ scores (APACHE Ⅱ scores) and organ dysfunction scores (Marshall scores). MREE was measured by using IC of the MedGraphics CCM/D System within the first 7 d after nutrition therapy. CREE was calculated by using the HarrisBenedict formula adjusted with correction factors for illness at the same time. According to APACHE Ⅱ scores on admission, the enrolled patients were divided into two groups: APACHEⅡ score ≥20 scores group (n=8) and APACHE Ⅱ score lt;20 scores group (n=13), and the differences between MREE and CREE of patients in two groups were determined. ResultsThe reduction of variation tendency in CREE other than MREE in the enrolled patients within the first week of nutritional support was statistical significance (P lt;0.001). The CREE of patients 〔(1 984.49±461.83) kcal/d〕 was significantly higher than the MREE 〔(1 563.88±496.93) kcal/d〕 during the first week of nutritional support (P lt;0.001). The MREE on the 0, 1, 2, and 4 d after nutrition therapy were statistically significant lower than CREE at the same time interval in these patients (P lt;0.01), and the differences at the other time points were not significant (P gt;0.05). There was a trend towards a reduction in APACHE Ⅱ and Marshall scores within the first week of nutrition therapy that reached statistical significance (P lt;0.001). During the first week of nutrition therapy, APACHEⅡ and Marshall scores of patients in ≥20 scores group were significantly higher than those in lt;20 scores group, respectively (P lt;0.05 or P lt;0.01), and the reductions of APACHE Ⅱ scores and Marshall scores were significant in patients of two groups (P lt;0.001). A significant positive correlation was found between CREE with APACHE Ⅱ scores (r=0.656, P lt;0.001) and Marshall scores (r=0.608，P lt;0.001) in patients within the first week after nutrition support. Although no statistically significant correlation was observed between MREE and APACHEⅡ scores (r=-0.045， P=0.563), a significant positive correlation was observed between MREE and Marshall scores (r=0.263, P=0.001) within the first week after nutrition therapy. There was no correlation between MREE and CREE (r=0.064, P=0.408) in patients at the same time interval. The reduction of MREE of patients in ≥20 scores group other than in lt;20 scores group was statistically significant within the first week after nutrition therapy (P=0.034). In addition, the MREE of patients in ≥20 scores group were not significantly different from those in lt;20 scores group (P gt;0.05), and the mean CREE was not different in two groups patients within the first week of nutritional therapy 〔(1 999.55±372.73) kcal/d vs. (1 918.39±375.27) kcal/d, P=0.887〕. CREE was significantly higher than MREE of patients in ≥20 scores group within the first week except the 3 d and 5 d after nutrition therapy (P lt;0.05), while in lt;20 scores group CREE was significantly higher than MREE in patients only within the first 3 d after nutrition therapy (P lt;0.05 or P lt;0.01). MREE and CREE of patients in ≥20 scores group were not different from those in lt;20 scores group, respectively (P gt;0.05).

Citation： CHEN Hong,SUN Jiabang,LI Fei,JIA Jianguo.. Evaluation of Resting Energy Expenditure in Critically Surgical Patients Undergoing Mechanical Ventilation. CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY, 2011, 18(8): 854-860. doi: Copy

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2.	McClave SA. Indirect calorimetry: relevance to patient outcome [J]. Respir Care Clin N Am, 2006, 12(4): 635650, vii.
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7.	McClave SA, Lowen CC, Kleber MJ, et al. Clinical use of the respiratory quotient obtained from indirect calorimetry [J]. J Parenter Enter Nutr, 2003, 27(1): 2126.
8.	Walker RN, Heuberger RA. Predictive equations for energy needs for the critically ill [J]. Respir Care, 2009, 54(4): 509521.
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12.	Frankenfield D, Smith SJ, Cooney RN. Validation of 2 approaches to predicting resting metabolic rate in critically ill patients [J]. J Parenter Enter Nutr, 2004, 28(4): 259264.
13.	Lev S, Cohen J, Singer P. Indirect calorimetry measurements in the ventilated critically ill patient: facts and controversies—the heat is on [J]. Crit Care Clin, 2010, 26(4): e1e9.
14.	Faisy C, Lerolle N, Dachraoui F, et al. Impact of energy deficit calculated by a predictive method on outcome in medical patients requiring prolonged acute mechanical ventilation [J]. Br J Nutr, 2009, 101(7): 10791087.
15.	Brandi LS, Bertolini R, Calafà M. Indirect calorimetry in critically ill patients: clinical applications and practical advice [J]. Nutrition, 1997, 13(4): 349358.
16.	Reid CL, Carlson GL. Indirect calorimetry—a review of recent clinical applications [J]. Curr Opin Clin Nutr Metab Care, 1998, 1(3): 281286.
17.	Frankenfield DC, Sarson Y, Blosser SA, et al. Validation of a 5minute steady state indirect calorimetry protocol for resting EE in critically ill patients [J]. J Am Coll Nutr, 1996, 15(3): 397402.
18.	McClave SA, Spain DA, Skolnick JL, et al. Achievement of steady state optimizes results when performing indirect calorimetry [J]. J Parenter Enter Nutr, 2003, 27(1): 1620.
19.	Reeves MM, Davies PS, Bauer J, et al. Reducing the time period of steady state does not affect the accuracy of energy expenditure measurements by indirect calorimetry [J]. J Appl Physiol, 2004, 97(1): 130134.
20.	Petros S, Engelmann L. Validity of an abbreviated indirect calorimetry protocol for measurement of resting energy expenditure in mechanically ventilated and spontaneously breathing critically ill patients [J]. Intensive Care Medicine, 2001, 27(7): 11641168.
21.	Branson RD, Johannigman JA. The measurement of energy expenditure [J]. Nutr Clin Pract, 2004, 19(5): 622636.
22.	Brandi LS, Bertolini R, Santini L, et al. Effects of ventilator resetting on indirect calorimetry measurement in the critically ill surgical patient [J]. Crit Care Med, 1999, 27(3): 531539.
23.	Haugen HA, Chan LN, Li F. Indirect calorimetry: a practical guide for clinicians [J]. Nutr Clin Pract, 2007, 22(4): 377388.
24.	Compher C, Frankenfield D, Keim N, et al. Best practice methods to apply to measurement of resting metabolic rate in adults: a systematic review [J]. J Am Diet Assoc, 2006, 106(6): 881903.
25.	da Rocha EE, Alves VG, Silva MH, et al. Can measured resting energy expenditure be estimated by formulae in daily clinical nutrition practice?[J]. Curr Opin Clin Nutr Metab Care, 2005, 8(3): 319328.
26.	黎介寿. 临床营养支持策略的变迁 [J]. 中国普外基础与临床杂志, 2009, 16(12): 953955.
27.	秦环龙, 杨俊. 外科营养的现状与展望 [J]. 中国普外基础与临床杂志, 2008, 15(11): 791793.
28.	Hwang TL, Huang SL, Chen MF. The use of indirect calorimetry in critically ill patients—the relationship of measured energy expenditure to Injury Severity Score, Septic Severity Score, and APACHE Ⅱ Score [J]. J Trauma, 1993, 34(2): 247251.
29.	Blackburn GL, Wollner S, Bistrian BR. Nutrition support in the intensive care unit: an evolving science [J]. Arch Surg, 2010, 145(6): 533538.
30.	Burke PA, Young LS, Bistrian BR. Metabolic vs nutrition support: a hypothesis [J]. J Parent Enteral Nutr, 2010, 34(5): 546548.

1. Bistrian BR. Comment on ‘Guidelines for the provision and assessment of nutrition support therapy in the adult critically ill patient’ [J]. J Parent Enteral Nutr, 2010, 34(3): 348349.
2. McClave SA. Indirect calorimetry: relevance to patient outcome [J]. Respir Care Clin N Am, 2006, 12(4): 635650, vii.
3. Scurlock CS, Raikhelkar J, Mechanick JI. Intensive metabolic support: evolution and revolution [J]. Endocr Pract, 2008, 14(8): 10471054.
4. Alberda C, Gramlich L, Jones N, et al. The relationship between nutritional intake and clinical outcomes in critically ill patients: results of an international multicenter observational study [J]. Intensive Care Med, 2009, 35(10): 17281737.
5. Smyrnios NA, Curley FJ, Shaker KG. Accuracy of 30minute indirect calorimetry studies in predicting 24hour energy expenditure in mechanically ventilated, critically ill patients [J]. J Parenter Enteral Nutr, 1997, 21(3): 168174.
6. Rocha EEM. Determination of caloric expenditure in critically ill patients [J]. Clin Bras Terap Intens, 2001, 11(1): 123.
7. McClave SA, Lowen CC, Kleber MJ, et al. Clinical use of the respiratory quotient obtained from indirect calorimetry [J]. J Parenter Enter Nutr, 2003, 27(1): 2126.
8. Walker RN, Heuberger RA. Predictive equations for energy needs for the critically ill [J]. Respir Care, 2009, 54(4): 509521.
9. da Rocha EE, Alves VG, da Fonseca RB. Indirect calorimetry: methodology, instruments and clinical application [J]. Curr Opin Clin Nutr Metab Care, 2006, 9(3): 247256.
10. Elizabeth Weekes C. Controversies in the determination of energy requirements [J]. Proc Nutr Soc, 2007, 66(3): 367377.
11. Wooley JA. Indirect calorimetry: applications in practice [J]. Respir Care Clin N Am, 2006, 12(4): 619633.
12. Frankenfield D, Smith SJ, Cooney RN. Validation of 2 approaches to predicting resting metabolic rate in critically ill patients [J]. J Parenter Enter Nutr, 2004, 28(4): 259264.
13. Lev S, Cohen J, Singer P. Indirect calorimetry measurements in the ventilated critically ill patient: facts and controversies—the heat is on [J]. Crit Care Clin, 2010, 26(4): e1e9.
14. Faisy C, Lerolle N, Dachraoui F, et al. Impact of energy deficit calculated by a predictive method on outcome in medical patients requiring prolonged acute mechanical ventilation [J]. Br J Nutr, 2009, 101(7): 10791087.
15. Brandi LS, Bertolini R, Calafà M. Indirect calorimetry in critically ill patients: clinical applications and practical advice [J]. Nutrition, 1997, 13(4): 349358.
16. Reid CL, Carlson GL. Indirect calorimetry—a review of recent clinical applications [J]. Curr Opin Clin Nutr Metab Care, 1998, 1(3): 281286.
17. Frankenfield DC, Sarson Y, Blosser SA, et al. Validation of a 5minute steady state indirect calorimetry protocol for resting EE in critically ill patients [J]. J Am Coll Nutr, 1996, 15(3): 397402.
18. McClave SA, Spain DA, Skolnick JL, et al. Achievement of steady state optimizes results when performing indirect calorimetry [J]. J Parenter Enter Nutr, 2003, 27(1): 1620.
19. Reeves MM, Davies PS, Bauer J, et al. Reducing the time period of steady state does not affect the accuracy of energy expenditure measurements by indirect calorimetry [J]. J Appl Physiol, 2004, 97(1): 130134.
20. Petros S, Engelmann L. Validity of an abbreviated indirect calorimetry protocol for measurement of resting energy expenditure in mechanically ventilated and spontaneously breathing critically ill patients [J]. Intensive Care Medicine, 2001, 27(7): 11641168.
21. Branson RD, Johannigman JA. The measurement of energy expenditure [J]. Nutr Clin Pract, 2004, 19(5): 622636.
22. Brandi LS, Bertolini R, Santini L, et al. Effects of ventilator resetting on indirect calorimetry measurement in the critically ill surgical patient [J]. Crit Care Med, 1999, 27(3): 531539.
23. Haugen HA, Chan LN, Li F. Indirect calorimetry: a practical guide for clinicians [J]. Nutr Clin Pract, 2007, 22(4): 377388.
24. Compher C, Frankenfield D, Keim N, et al. Best practice methods to apply to measurement of resting metabolic rate in adults: a systematic review [J]. J Am Diet Assoc, 2006, 106(6): 881903.
25. da Rocha EE, Alves VG, Silva MH, et al. Can measured resting energy expenditure be estimated by formulae in daily clinical nutrition practice?[J]. Curr Opin Clin Nutr Metab Care, 2005, 8(3): 319328.
26. 黎介寿. 临床营养支持策略的变迁 [J]. 中国普外基础与临床杂志, 2009, 16(12): 953955.
27. 秦环龙, 杨俊. 外科营养的现状与展望 [J]. 中国普外基础与临床杂志, 2008, 15(11): 791793.
28. Hwang TL, Huang SL, Chen MF. The use of indirect calorimetry in critically ill patients—the relationship of measured energy expenditure to Injury Severity Score, Septic Severity Score, and APACHE Ⅱ Score [J]. J Trauma, 1993, 34(2): 247251.
29. Blackburn GL, Wollner S, Bistrian BR. Nutrition support in the intensive care unit: an evolving science [J]. Arch Surg, 2010, 145(6): 533538.
30. Burke PA, Young LS, Bistrian BR. Metabolic vs nutrition support: a hypothesis [J]. J Parent Enteral Nutr, 2010, 34(5): 546548.

CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Evaluation of Resting Energy Expenditure in Critically Surgical Patients Undergoing Mechanical Ventilation

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