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Comparison between resting energy expenditure measured by indirect calorimetry and metabolic rate estimate based on Harris-Benedict equation in septic patients

Jiro Kamiyama

Intensive Care Unit, Gunma University Hospital, Japan

E-mail : aa

Tomonori Takazawa

Intensive Care Unit, Gunma University Hospital, Japan

Akihiro Yanagisawa

Intensive Care Unit, Gunma University Hospital, Japan

Masafumi Kanamoto

Intensive Care Unit, Gunma University Hospital, Japan

Masaru Tobe

Intensive Care Unit, Gunma University Hospital, Japan

Hiroshi Hinohara

Intensive Care Unit, Gunma University Hospital, Japan

Fumio Kunimoto

Department of Anesthesiology, Hotakakai Hotaka Hospital, Japan

Shigeru Saito

Intensive Care Unit, Gunma University Hospital, Japan

Department of Anesthesiology, Gunma University Graduate School of Medicine, Japan

DOI: 10.15761/BRCP.1000123

Article
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Abstract

Background: Providing an adequate caloric intake is essential for improving clinical outcomes, because inadequate nutrition induces several problems. Previous studies have shown that energy expenditure calculated by classical prediction equations, such as the Harris-Benedict equation (HBE), is greater than the measured resting energy expenditure (REE). To compensate for this discrepancy, additional factors, such as a stress factor, are often used to rescale the value. However, the numerical value of the stress factor, particularly in septic patients, is unknown. Indirect calorimetry (IC) enables to the real-time measurement of REE at the bedside. We hypothesized that the stress factor could decrease over the time course of recovery in septic patients. To test this hypothesis, we measured the REE of septic patients hospitalized in our ICU throughout their intubation period.

Methods: This single-center retrospective study was conducted to compare resting REE measured by IC and the estimated energy expenditure in adult septic patients. Basal metabolic rate (BMR) was estimated by the HBE. Chronological changes in the ratio of measured REE to BMR were analyzed to estimate the stress factor.

Results: A total of 47 patients with sepsis were included in this study. We found that REE/BMR in the septic patients was in the range of 1.07 to 1.11. Moreover, the estimated stress factor did not change over time during the intubation period. REE/BMR did not depend on the number of sedatives administered. Both sequential organ failure assessment (SOFA) scores and blood concentrations of C-reactive protein (CRP) decreased over time. Respiratory quotient (RQ) on the last intubation day was greater than that on the first day.

Conclusions: The REE measured by IC in sedated septic patients was approximately 1.1 times greater than BMR. The ratio of measured REE to BMR does not change with resolution of the illness. This result was likely caused by the concomitant increase in energy intake and improvement in patient general condition at this time. These findings may contribute to better nutrition control in ICU-admitted septic patients.

Key words

 indirect calorimetry, resting energy expenditure, sepsis, Harris-Benedict equation

Introduction

Providing an adequate caloric intake to hospitalized patients is essential for improving clinical outcomes. Overfeeding, for example, could induce several problems, including hyperglycemia, hypercapnia, azotemia, and immune deficiency [1-3]. Therefore, predicting total energy requirements is important for preventing these complications. To predict energy requirements, numerous mathematical prediction equations, such as Harris-Benedict, Schofield, Ireton-Jones, Penn State, and Swinamer equations, have been developed [4-8]. Although the Harris-Benedict equation (HBE) is the oldest of these equations, published in 1919, due to its simplicity it still plays a major role in nutrition management in clinical settings. The HBE was developed based on data collected from a population of healthy volunteers [4]. To apply the HBE to hospitalized patients, additional factors, such as stress and activity factors, are often incorporated into the equation to account for the elevated energy expenditure due to stress or injury [9,10]. As a stress factor for critically ill patients, for example, a value between 1.2 and 1.6 has been chosen in past studies [11-15]. However, few studies have reported on the number that should be used as the stress factor in septic patients [16,17].

Release of proinflammatory cytokines and stress hormones in septic patients results in several metabolic changes, including an increase in energy requirements. The secreted cytokines and stress hormones catabolize skeletal muscle and body fat, and the resultant catabolites are utilized as endogenous energy substrates. Particularly in the early clinical stage of sepsis, an increase in total energy expenditure (TEE) is expected as a result of increase in endogenous energy supply due to enhanced catabolism [18].

Indirect calorimetry (IC) is currently considered the most accurate method for measuring caloric needs [19,20]. IC measures oxygen consumption and carbon dioxide excretion, which are used to calculate the respiratory quotient (RQ) and resting energy expenditure (REE), using the Weir equation [21]. We hypothesized that the stress factor in septic patients could be calculated by dividing the value of REE by the basal metabolic rate (BMR) that is calculated using prediction equations.

Further, the stress factor that should be adopted for septic patients could change over the course of the patient’s illness, since the total amount of released cytokines and stress hormones depends on the severity of the illness. We hypothesized that the stress factor could become smaller during recovery in septic patients, because REE probably decreases with resolution of the illness. To test this hypothesis, we measured REE in septic patients hospitalized in our ICU and investigated the changes in REE/BMR over the period during which they were intubated.

Methods

Study design

This retrospective observational study was conducted at the intensive care unit (ICU) of Gunma University Hospital. This study was approved by the institutional ethics committee of our facility. Moreover, information was published on the web page of our hospital to inform patients about the study protocol, and give them a chance to refuse inclusion in the study. Adult patients (≥18 years of age) admitted to the ICU with a diagnosis of sepsis between April 2010 and March 2015 and who were mechanically ventilated for over three days were included. All the patients included in the study fulfilled the diagnostic criteria for severe sepsis [22,23]. Mechanically ventilated patients who met one or more of the following criteria were excluded: fraction of inspired oxygen (FiO₂) ≥ 0.6, positive end expiratory pressure (PEEP) >12 cmH2O, respiratory rate >35 breaths/min, and presence of a chest drain with leakage. In addition, patients on hemodialysis or continuous renal replacement therapy were excluded.

Data collection

We measured REE using a mechanical ventilator with an in-built IC (Engström Carestation®, GE Healthcare Japan). This ventilator automatically calculated REE using the Weir equation.

Weir equation [21]

REE (kcal/day) = (3.94 × VO₂ + 1.10 × VCO₂) × 1.44 − (2.17 × UN*)

VO₂: oxygen consumption (mL/min), VCO₂: carbon dioxide production (mL/min), UN: urinary nitrogen excretion (g). * In the Engström Carestation®, the value of UN is fixed at 13 g/day.

RQ (Respiratory quotient) = VCO₂/VO₂, was also assessed.

The ventilator with its data migration system enables continuous monitoring of REE. We selected the data measured at 2 a.m. on the first, second, and last days of the intubation period. The protocol required (1) that patients be inactive and undisturbed for 30 minutes before testing and for the 15-minute duration of data collection, (2) an interval of at least 30 minutes between changes in ventilator settings and measurements, and (3) an interval of at least 4 hours between changes in the feeding method and measurements. When the RQ was less than 0.67 or greater than 1.3, we discarded the values and instead incorporated the data obtained as close to 2 a.m. as possible [24-28]. We used any one or more of the following sedatives, as required: propofol, dexmedetomidine, midazolam, and fentanyl (Supplemental Table S1). Predicted BMR was calculated by either the Harris-Benedict or Schofield equation using actual body weight and height on ICU admission.

Table S1. Demographic data of patients, resting energy expenditure, calculated energy expenditure, APACHE II score, blood concentration of CRP, SOFA score, respiratory quotient, energy intake, and sedative usage in the study subjects.

number

age
(years)

sex

disease

intubated
days

height
(cm)

weight
(kg)

BMI
(kg/m²)

HBE
(kcal) 

Schofield
(kcal)

REE
1st intubated day (kcal)

REE
2nd intubated day (kcal)

REE
last intubated day (kcal)

APACHEⅡ score
on ICU admission

CRP
1st intubated day (mg/dL)

CRP
2nd intubated day (mg/dL)

CRP
last intubated day (mg/dL)

SOFA
1st intubated day

SOFA
2nd intubated day

SOFA
last intubated day

RQ
1st intubated day

RQ
2nd intubated day

RQ
last intubated day

energy intake
1st intubated day (kcal)

energy intake
2nd intubated day (kcal)

energy intake
last intubated day (kcal)

sedatives
1st intubated day (mg/hr)

sedatives
2nd intubated day (mg/hr)

sedatives
last intubated day (mg/hr)

1

45

female

miliary tuberculosis

22

159

31

11.2

1027

1097

1239

1043

1263

32

21

18

1.1

13

10

8

0.69

0.78

0.74

500

690

1440

propofol 80 / fentanyl 0.05

propofol 100 / fentanyl 0.025

fentanyl 0.05

2

63

female

pneumonia

12

145

39

18.5

994

1012

1183

1137

1040

33

33.9

32

6.2

12

14

7

0.88

0.81

0.81

680

680

1250

propofol 50 / fentanyl 0.05

propofol 50 / fentanyl 0.05

fentanyl 0.05

3

76

male

pneumonia

20

178

70

18.8

1406

1407

1604

1544

1307

20

30.1

28

3

9

8

4

0.64

0.8

0.78

480

960

1520

dexmedetomidine 0.032 / fentanyl 0.05

dexmedetomidine 0.032 / fentanyl 0.075

fentanyl 0.05

4

60

male

necrotising fasciitis

22

174

69

22.4

1478

1395

1640

1762

1637

17

22

22.8

2

5

7

3

0.74

0.85

0.97

240

680

2080

propofol 100 / fentanyl 0.05

dexmedetomidine 0.024 / fentanyl 0.05

0

5

49

male

renal abcess

6

157

56

22.8

1292

1515

1682

1551

1424

22

11.2

12

5.9

14

14

3

0.73

0.74

0.81

540

970

1180

propofol 100

propofol 60

propofol 60

6

38

male

phlegmone

6

174

86

28.3

1864

1859

2268

2148

2240

22

25.5

23.3

9.4

9

8

4

0.72

0.76

0.69

560

560

1540

propofol 150 / fentanyl 0.05

propofol 150 / fentanyl 0.05

fentanyl 0.05

7

42

female

cholangitis

4

162

81

31

1530

1503

1696

1592

1480

31

13.8

9.3

6.2

16

14

11

0.69

0.71

0.77

400

1080

1080

0

0

0

8

42

male

gastrointestinal perforation

3

174

111

36.5

2176

2145

1894

1772

2175

26

9.4

15.9

28.7

9

4

2

0.78

0.85

0.75

390

760

760

propofol 100 / fentanyl 0.05

propofol 150 / fentanyl 0.05

propofol 150 / fentanyl 0.05

9

77

female

candidemia

16

138

38

20

906

1003

1225

1100

1297

32

11.8

9.2

6.1

15

12

8

0.77

0.95

0.73

840

840

1060

dexmedetomidine 0.024 / fentanyl 0.05

dexmedetomidine 0.024 / fentanyl 0.05

dexmedetomidine 0.032 / fentanyl 0.05

10

72

male

pneumonia

4

165

40

14.6

950

1056

1072

1144

1018

20

3.7

5.6

7.2

9

9

6

0.68

1

0.76

1760

1760

1790

propofol 50

propofol 50

propofol 60 / fentanyl 0.05

11

68

female

pseudomembranous colitis

20

150

35

15.6

941

976

1015

1142

1228

32

22.6

27

4

10

11

6

0.77

0.78

1.06

300

820

1640

0

0

0

12

21

female

phlegmone

14

140

35

17.9

1144

1005

902

1109

1194

13

26.2

13.9

3.1

7

7

4

0.63

0.86

0.81

580

1060

1580

propofol 120 / fentanyl 0.025

propofol 120 / fentanyl 0.05

propofol 120 / fentanyl 0.05

13

73

female

extremity gangrene

4

147

30

13.9

865

930

1132

1122

1158

22

1

2.3

1

8

7

4

0.72

0.8

0.76

630

630

630

0

0

0

14

69

male

cholangitis

3

158

64

25.8

1275

1340

994

1172

1195

23

3.1

3

7.5

10

8

2

0.68

0.74

0.79

520

520

400

propofol 50 / dexmedetomidine 0.02 / fentanyl 0.05

propofol 50 / dexmedetomidine 0.024 / fentanyl 0.075

dexmedetomidine 0.024 / fentanyl 0.075

15

55

female

necrotising fasciitis

8

165

65

23.9

1318

1373

1349

1248

1337

25

44.8

45.4

4.6

11

12

3

0.69

0.78

0.84

630

1230

1540

propofol 50 / dexmedetomidine 0.024 / fentanyl 0.075

propofol 50 / dexmedetomidine 0.024 / fentanyl 0.075

fentanyl 0.05

16

60

female

pneumonia

6

159

84

33.2

1468

1421

1813

1696

1852

17

2.9

25.1

8.1

17

15

12

0.86

0.73

0.72

200

680

1580

propofol 80 / dexmedetomidine 0.032 / fentanyl 0.075

propofol 80 / dexmedetomidine 0.4 / fentanyl 0.075

propofol 60 / dexmedetomidine 0.4 / fentanyl 0.05

17

82

male

pneumonia

25

152

47

20.3

916

1138

1158

1367

1161

22

28.7

27

2.1

12

13

9

0.72

0.68

0.73

870

870

1480

dexmedetomidine 0.024 / fentanyl 0.075

dexmedetomidine 0.024 / fentanyl 0.05

fentanyl 0.025

18

50

male

pelvic abscess

6

160

72

28.1

1523

1698

1634

1582

1692

25

16.5

20.8

20.1

19

19

14

1

0.7

0.74

430

620

940

propofol 120 / fentanyl 0.05

propofol 80 / fentanyl 0.05

propofol 120 / dexmedetomidine 0.32 / fentanyl 0.05

19

37

male

extremity gangrene

4

165

58

21.3

1443

1538

1665

1514

1535

25

25.2

25

22.1

16

15

12

0.79

0.85

0.81

200

1000

1240

dexmedetomidine 0.032 / fentanyl 0.05

dexmedetomidine 0.04 / fentanyl 0.05

dexmedetomidine 0.04 / fentanyl 0.05

20

37

male

pneumonia

3

172

51

17.2

1372

1457

1221

1081

1131

16

10.8

18.1

17.7

8

9

7

0.79

0.8

0.85

560

1240

1240

propofol 70

propofol 50 / midazolam 10

propofol 50 / midazolam 10

21

78

male

septic arthritis

7

152

69

29.9

1254

1395

1652

1294

1698

24

27.8

27.5

8.9

15

15

12

0.68

0.87

0.79

300

630

1240

dexmedetomidine 0.024 / fentanyl 0.05

dexmedetomidine 0.024 / fentanyl 0.05

dexmedetomidine 0.032 / fentanyl 0.1

22

63

male

pneumonia

3

174

54

17.8

1256

1220

1624

1586

1586

16

21.5

20.3

21

9

10

8

0.7

0.69

0.72

240

520

840

propofol 100 / fentanyl 0.05

propofol 50 / fentanyl 0.075

dexmedetomidine 0.02 / fentanyl 0.075

23

70

male

tetanus

23

164

57

21.2

1192

1255

1445

1519

1647

25

8.8

20.1

1.4

12

12

7

0.87

0.78

0.84

360

1080

1700

propofol 150 / fentanyl 0.05

propofol 100 / fentanyl 0.05

midazoram 10

24

53

male

pneumonia

4

164

61

22.7

1368

1572

1512

1417

1415

19

17.6

27.2

7.2

12

12

9

0.78

0.83

0.85

740

740

1340

propofol 100 / fentanyl 0.05

propofol 100 / fentanyl 0.025

propofol 100 / fentanyl 0.05

25

59

male

pneumonia

3

185

68

19.9

1529

1652

2134

2018

2185

15

4

11.3

7.4

9

9

3

0.71

0.7

0.75

300

300

300

dexmedetomidine 0.04 / fentanyl 0.05

dexmedetomidine 0.04 / fentanyl 0.05

dexmedetomidine 0.024 / fentanyl 0.05

26

82

male

pneumonia

4

163

57

21.5

1111

1255

1426

1413

1647

16

26.8

24.4

6.8

10

9

6

0.7

0.68

0.71

580

1060

1540

dexmedetomidine 0.024

dexmedetomidine 0.024

dexmedetomidine 0.024 / fentanyl 0.05

27

28

female

phlegmone

4

162

77

29.3

1554

1527

1384

1504

1517

35

2.5

9.7

6.9

13

11

8

0.71

0.77

0.81

400

640

880

fentanyl 0.1

dexmedetomidine 0.02 / fentanyl 0.05

dexmedetomidine 0.02 / fentanyl 0.05

28

74

male

pneumonia

3

163

56

22.2

1154

1243

1147

1079

1118

26

6

8.1

9.2

8

8

2

0.86

0.84

0.68

500

660

1380

propofol 80 / dexmedetomidine 0.02 / fentanyl 0.05

propofol 150 / dexmedetomidine 0.024 / fentanyl 0.05

propofol 150 / dexmedetomidine 0.02 / fentanyl 0.05

29

56

female

tetanus

13

150

52

23.1

1161

1268

1193

1080

1268

18

0.5

1.9

6.8

9

7

5

0.89

0.93

0.92

680

620

1600

propofol 80 / fentanyl 0.05

propofol 60 / fentanyl 0.05

fentanyl 0.05

30

80

male

pneumonia

3

150

44

19.6

876

1102

991

1014

978

18

8.3

6

7

8

7

3

0.75

0.82

0.76

200

200

400

dexmedetomidine 0.02

dexmedetomidine 0.028

dexmedetomidine 0.028

31

80

male

pneumonia

6

157

59

23.9

1122

1278

1221

1198

1268

20

1.1

3

4

10

9

8

0.76

0.72

0.8

420

420

840

propofol 50 / fentanyl 0.025

propofol 50 / fentanyl 0.025

0

32

73

male

pneumonia

9

162

81

30.9

1499

1536

1672

1531

1432

19

10.1

12.3

5.6

8

8

4

0.68

0.7

0.71

240

800

920

propofol 100 / fentanyl 0.05

propofol 50 / dexmedetomidine 0.032 / fentanyl 0.05

propofol 40 / dexmedetomidine 0.024 / fentanyl 0.05

33

85

male

gastrointestinal perforation

4

165

50

18.4

1004

1173

1213

1293

1197

34

15.3

19.3

24.5

13

12

9

0.79

0.75

0.82

380

480

1280

propofol 60 / fentanyl 0.05

propofol 100 / fentanyl 0.05

propofol 80 / fentanyl 0.05

34

66

female

ileus

18

151

40

17.5

1001

1021

1032

1003

1103

25

4.2

21

2.1

12

10

6

0.68

0.71

0.77

300

640

900

dexmedetomidine 0.024 / fentanyl 0.05

dexmedetomidine 0.032 / fentanyl 0.05

fentanyl 0.05

35

74

male

pneumonia

8

165

44

16.2

993

1102

1308

1238

1143

39

33.4

35.6

4.1

12

14

10

0.86

0.78

0.89

200

1120

1570

fentanyl 0.05

dexmedetomidine 0.04 / fentanyl 0.05

dexmedetomidine 0.02 / fentanyl 0.05

36

69

female

miliary tuberculosis

3

146

31

14.5

895

940

852

797

767

33

5.8

20.7

9.1

8

6

6

0.82

0.72

0.74

680

680

780

fentanyl 0.025

fentanyl 0.025

fentanyl 0.025

37

62

male

pneumonia

4

162

53

20.2

1223

1208

1107

1245

1112

20

2.2

1.5

0.7

6

8

5

0.89

0.91

0.86

400

960

1440

dexmedetomidine 0.024

dexmedetomidine 0.02 / fentanyl 0.05

dexmedetomidine 0.024

38

79

female

gastrointestinal perforation

3

150

50

22.1

1029

1112

1183

1221

1255

24

19.9

13

11.3

9

6

4

0.71

0.72

0.66

400

400

830

dexmedetomidine 0.032 / fentanyl 0.05

dexmedetomidine 0.04 / fentanyl 0.05

dexmedetomidine 0.032 / fentanyl 0.05

39

76

female

gastrointestinal perforation

4

152

62

22.2

1167

1221

1047

1031

1162

23

10

23.1

6.8

10

10

5

0.71

0.87

0.95

320

960

1480

propofol 50 / fentanyl 0.05

propofol 50 / fentanyl 0.05

fentanyl 0.025

40

61

male

pneumonia

3

156

67

27.5

1358

1372

1133

1231

1348

18

2.2

21.7

13.2

7

6

2

0.83

0.71

0.68

200

400

1440

dexmedetomidine 0.032 / fentanyl 0.05

dexmedetomidine 0.032 / fentanyl 0.05

dexmedetomidine 0.024

41

80

female

pneumonia

20

133

35

19.8

857

976

911

825

843

31

1.6

5.3

2.4

12

10

6

0.73

0.77

1.02

200

200

880

dexmedetomidine 0.02 / fentanyl 0.05

dexmedetomidine 0.02 / fentanyl 0.05

0

42

61

male

pneumonia

3

166

60

21.8

1303

1290

1365

1412

1241

26

7.6

16.3

18.1

10

9

5

0.79

0.73

0.75

320

320

320

propofol 50 / fentanyl 0.05

propofol 50 / fentanyl 0.05

propofol 50 / fentanyl 0.025

43

72

male

pneumonia

20

163

47

17.7

1036

1138

1174

1275

1239

33

5.8

8.7

7.4

13

12

8

0.97

0.75

0.78

200

780

1540

dexmedetomidine 0.02 / fentanyl 0.05

dexmedetomidine 0.024 / fentanyl 0.05

dexmedetomidine 0.02 / fentanyl 0.05

44

70

male

pneumonia

7

171

46

15.7

1066

1126

881

1001

1010

39

4.2

3.5

2.9

13

14

11

0.74

0.7

0.82

200

200

780

midazolam 5

midazoram 5

0

45

63

female

tetanus

31

153

54

23.1

1148

1148

1084

1362

1460

26

2.8

5

1

10

8

3

0.75

0.77

0.83

360

600

1120

propofol 150 / fentanyl 0.05

propofol 150 / fentanyl 0.05

0

46

77

male

pneumonia

6

155

65

27.1

1209

1348

1408

1427

1683

25

27.4

23.5

8.7

9

10

6

0.87

0.73

0.75

200

200

880

propofol 100 / fentanyl 0.05

propofol 150 / fentanyl 0.05

propofol 100 / dexmedetomidine 0.04 / fentanyl 0.05

47

56

female

gastrointestinal perforation

7

156

47

19.3

1126

1227

1205

1269

1321

35

24.8

28.7

12.8

14

11

8

0.73

0.7

0.87

400

600

840

dexmedetomidine 0.02 / fentanyl 0.05

dexmedetomidine 0.02 / fentanyl 0.05

fentanyl 0.025

Harris-Benedict equation (HBE) [4]

Males: BMR (kcal/day) = 66.5 + 13.8 × Weight (kg) + 5.0 × Height (cm) - 6.8 × age

Females: BMR (kcal/day) = 655.1 + 9.6 × Weight (kg) + 1.8 × Height (cm) - 4.7 × age.

Schofield equation [5]

Males: 18-30 years old: 15.057 × Weight (kg) + 692.2, 30-60 years old: 11.472 × Weight (kg) + 873.1, > 60 years old: 11.711 × Weight (kg) + 587.7

Females: 18-30 years old: 14.818 × Weight (kg) + 486.6, 30-60 years old: 8.126 × Weight (kg) + 845.6, > 60 years old: 9.082 × Weight (kg) + 658.5

We calculated total energy intake from the doctor’s order sheet. The decision regarding parenteral and/or enteral nutrition was made by a conference between the attending physician and ICU doctors. REE values measured by IC were not utilized in decision-making. Instead, for the subject with a state of good nutrition, we prescribed mainly enteral nutrients and the total energy intake was gradually increased over time. Whereas, for the subject with a state of poor nutrition, intravenous feeding solution was mainly administered.

Statistical analysis

Data analysis was performed using SigmaPlot 13 (Systat Software, Inc., San Jose, CA) and GraphPad Prism 5 (GraphPad Software, Inc., La Jolla, CA). Quantitative variables were described as means and standard deviations. Differences between groups were compared using Mann-Whitney U test, paired t-test, one-way ANOVA, or two-way ANOVA post hoc test. P < 0.05 was considered significant.

Results

A total of 47 patients with sepsis were included in this study. Their demographic data is shown in Table 1. The patients who survived to discharge only were included, because most moribund patients showed unexpected values of respiratory quotient, within the range adopted as exclusion criteria. We compared REE measured by IC with predicted energy expenditure (as BMR) calculated by the equations mentioned above. As a stress factor, we adopted 1.4-fold rescaling for comparison between measured and predicted energy expenditure, because it has been reported that values between 1.2 and 1.6 should be used as the stress factor for septic patients. In the intubated patients in this study, REE was always smaller than the total energy expenditure (TEE) estimated by 1.4-fold rescaling of the HBE-based BMR (two-way ANOVA with post hoc Bonferroni test, P < 0.0001), as shown in Figure 1. This was also the case for BMR estimated by the Schofield equation (Figure 1). Since the TEE calculated by Harris-benedict and Schofield equations were not different, we used HBE for further analysis. REE values were plotted against BMR calculated by HBE to determine the stress factor for septic patients (Figure 2). REE and BMR correlated reasonably well on the first day (R = 0.79). Additionally, the slope of the graph, namely, REE/BMR, was 1.09. REE also correlated well with BMR on both the second and last days (R = 0.76 and 0.78, respectively). Surprisingly, REE/BMR on the second and last days were 1.07 and 1.11, respectively, suggesting that the estimated stress factor did not change over time (see also Table 2). Many patients in this study were administered some sort of sedative (Table 3, Table S1). However, REE/BMR did not depend on the number of sedatives administered to the patients throughout the intubation period (one-way ANOVA, P > 0.05). These results suggest that sedatives had minimal effects on REE/BMR.

Figure 1. Comparison of the energy expenditure measured by indirect calorimetry (IC) and calculated by Harris-Benedict and Schofield equations. Basal metabolic rate (BMR) was multiplied by 1.4, as a tentative stress factor. Resting energy expenditure (REE) measured by IC was always smaller than estimated total energy expenditure by the prediction equation (two-way ANOVA with post hoc Bonferroni test, P < 0.0001).

Number of patients

47

Male

29 (61.7%)

Age (years)

63 ± 15  (21-85)

Height (cm)

159 ± 11 (133-185)

Weight (kg)

56 ± 17 (30-111)

BMI (kg / m²) 

21.8 ± 5.4 (11-37)

APACHEⅡ score

25 ± 7 (13-39)

BMR on admission:
Harris-Benedict (kcal/day)

1221 ± 268 (857-2176)

BMR on admission:
Schofiled (kcal/day)

1289 ± 251 (930-2145)

Primary site of infection

 

respiratory

24

skin and joint

11

abdominal

9

blood stream

1

urinary

2

Table 1. Patients’ demographic data.

Next, we sought the reasons for the relative constancy of REE/BMR in septic patients during the intubation period. To evaluate the severity of illness, sequential organ failure assessment (SOFA) scores and blood concentrations of C-reactive protein (CRP) were analyzed (Table 2). SOFA scores on the last day were lower than those on the first day (Mann-Whitney U test, P < 0.001). This trend corroborates with a decrease in CRP concentrations, suggesting improvement in the general condition of the patients. We also compared total energy intake (Table 2), since that may have impacted REE, and found that total energy intake on the last day was greater than that on the first day (Mann-Whitney U test, P < 0.001). Finally, we analyzed RQ and found that RQ on the last day was greater than that on the first day (Mann-Whitney U test, P = 0.04). Increased energy intake accompanied with RQ gain suggested that the exogenous energy supplied on the last intubation day was sufficient for the patients.

Discussion

In this study, we found that REE/BMR, i.e., the estimated stress factor, in survivors of sepsis was in the range of 1.07 to 1.11. Moreover, the estimated stress factor did not change over time during the intubation period (Figure 2 and Table 2).

Figure 2. Relationship between resting energy expenditure (REE) and basal metabolic rate (BMR). REE and BMR correlated well on the first, second and last intubation days (R = 0.79. 0.76, and 0.78). The value of REE/BMR was always approximately 1.1.

 

1st day

Last day

P

REE / BMR

1.10 ± 0.16

1.12 ± 0.17

0.46

SOFA score

10.9 ± 3.0

6.3 ± 3.1

< 0.001

CRP (mg / dL)

14.2 ± 11.2

8.2 ± 6.6

0.02

Energy intake (kcal / day)

448 ± 267

1171 ± 415

< 0.001

Respiratory quotient

0.764 ± 0.08

0.797 ± 0.09

0.04

Table 2. Comparisons of the ratio of measured resting energy expenditure (REE) to basal metabolic rate (BMR), SOFA score, blood concentration of CRP, energy intake, and respiratory quotient between the first and last intubation days. Paired t-test was performed for comparison of REE/BMR. Mann-Whitney U test was used for analyses of the remaining data.

The numerical value of the stress factor that should be multiplied by BMR to predict total energy expenditure in critically ill patients remains controversial. Notably, the optimal number for septic patients is unknown. A previous study that included 73 mechanically ventilated, non-surgical, critically ill patients reported that the measured energy expenditure, namely REE, was no different from that predicted by the HBE, which does not involve multiplication by a stress factor [17]. The authors found that patients with sepsis are an exception to this and concluded that REE was ∼1.2 fold higher than that calculated by the unmodified formula during sepsis. Our estimated stress factor in septic patients was relatively small, but did not greatly differ from their data. One possible explanation for the small stress factor was sedation of the subjects. Indeed, it has been reported that REE/BMR decreased significantly by increasing the depth of sedation in postoperative patients [29]. In our study, all patients were intubated and most of them were sedated. However, REE/BMR was not found to be dependent on the number of sedatives administered (Table 3). Besides, patients who did not receive any sedatives might also have been drowsy due to endogenous sedative molecules, such as cannabinoids and ammonia. In other words, the degree of sedation might have been uniform regardless of whether or not sedatives were administered.

 

Number of  sedatives used

 

 

0

1

2 ≤

P

1st day

1.17 ± 0.13 (3)

1.06 ± 0.19 (10)

1.10 ± 0.15 (34)

0.60

2nd day

1.18 ± 0.13 (3)

1.11 ± 0.16 (6)

1.08 ± 0.15 (38)

0.52

last day

1.13 ± 0.16 (8)

1.09 ± 0.14 (16)

1.14 ± 0.19 (23)

0.59

Table 3. Comparison of the ratios of measured resting energy expenditure (REE) to basal metabolic rate (BMR) on the three days in terms of the number of sedatives used. One-way ANOVA was used for analysis.

The lack of change in REE/BMR over time was likely caused by following mechanisms. It is known that greater energy intake results in an increase in REE. This was likely the case in this study. The increase in RQ on the last day suggested a shift of the main energy substrate from fats to carbohydrates (Table 2). This shift was also probably caused by the increased energy intake. Conversely, overfeeding on the last day may have resulted in enhanced glycogen and fat synthesis [30]. This is called “nutritional stress”. It has been reported that in the process of glycogen and fat synthesis, 5 and 20%, respectively, of the generated molecules are themselves used up during the process of synthesis [31]. Besides, consumption of glycogen and fat results in an increase in REE. Taken together, excessive energy intake on the last day likely resulted in an increase in REE accompanied by glycogen and fat synthesis. Whereas, decrease in stress hormones, including adrenaline, noradrenaline, cortisol, growth factor and glucagon, resulting from the improvement in the patients’ condition, probably caused a decrease in REE. Stress hormones are released from the adrenal gland or locus ceruleus in the early stages of sepsis, and these induce catabolism of skeletal muscle and fat. Although few studies have shown the effect of stress hormones on energy expenditure, research has shown that exogenous adrenaline and cortisol raise the metabolic rate [32,33]. On the last intubation day, the general condition of the patients in this study had improved significantly, as indicated by the decrease in serum levels of the inflammatory marker, CRP (Table 2). Therefore, we opined that resolution of the illness resulted in a decrease in stress hormones, which in turn led to the decrease in REE. Collectively, an increase in REE caused by the increased energy intake may have been counteracted by a decrease in REE caused by the improvement in the patients’ condition.

Our study has some limitations. This study did not have a specific protocol for nutrition control while the patients were intubated. Therefore, there may have been inter-individual differences in the types of nutrients that were administered to the patients. In theory, measured REE might fluctuate with this uncontrolled factor, because RQ depends on the class of nutrient consumed. To overcome this issue, prospective studies including patients under uniform nutrition control should be performed. Another possible limitation of this study is a small number of measurements per day. Although IC can continuously monitor REE, we adopted data measured at a single time point per day. This protocol was formulated to avert inconstancy in the patient’s condition that can affect REE measurement. Since we did not intend to utilize the data obtained from IC for nutrition control, slight overfeeding probably occurred in the late intubation period. Despite this, however, we believe that our findings regarding the stress factor in mechanically ventilated septic patients under sedation may contribute to estimation of total energy expenditure using prediction equations.

Conclusions

The measured REE by IC in septic patients under sedation was approximately 1.1 times greater than BMR. The ratio of measured REE to BMR does not change with resolution of the illness throughout the intubation period. This result was likely caused by the concomitant increase in energy intake and improvement in patient general condition at this time. These findings may contribute to better nutrition control in septic patients in the ICU.

Acknowledgements

The authors are grateful to all staff of the Intensive Care Unit of Gunma University Hospital for their continuous help and support.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

All the authors participated in data collection. JK designed and conducted the study. JK and TT wrote the manuscript. FK and SS supervised the study. All the authors read and approved the final manuscript.

Funding

This study was supported by JSPS KAKENHI Grant Numbers 25893031 and 16K20376.

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Editorial Information

Editor-in-Chief

Kazuhisa Nishizawa
Teikyo University

Article Type

Research Article

Publication history

Received: October 08, 2016
Accepted: November 16, 2016
Published: November 18, 2016

Copyright

©2016 Kamiyama J. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Citation

Kamiyama J, Takazawa T, Yanagisawa A, Kanamoto M, Tobe M, et al. (2016) Comparison between resting energy expenditure measured by indirect calorimetry and metabolic rate estimate based on Harris-Benedict equation in septic patients. Biomed Res Clin Prac 1: DOI: 10.15761/BRCP.1000123

Corresponding author

Tomonori Takazawa

Intensive Care Unit, Gunma University Hospital, Japan, Tel: +81-27-220-8693; Fax: +81-27-220-8692

Number of patients

47

Male

29 (61.7%)

Age (years)

63 ± 15  (21-85)

Height (cm)

159 ± 11 (133-185)

Weight (kg)

56 ± 17 (30-111)

BMI (kg / m²) 

21.8 ± 5.4 (11-37)

APACHEⅡ score

25 ± 7 (13-39)

BMR on admission:
Harris-Benedict (kcal/day)

1221 ± 268 (857-2176)

BMR on admission:
Schofiled (kcal/day)

1289 ± 251 (930-2145)

Primary site of infection

 

respiratory

24

skin and joint

11

abdominal

9

blood stream

1

urinary

2

Table 1. Patients’ demographic data.

 

1st day

Last day

P

REE / BMR

1.10 ± 0.16

1.12 ± 0.17

0.46

SOFA score

10.9 ± 3.0

6.3 ± 3.1

< 0.001

CRP (mg / dL)

14.2 ± 11.2

8.2 ± 6.6

0.02

Energy intake (kcal / day)

448 ± 267

1171 ± 415

< 0.001

Respiratory quotient

0.764 ± 0.08

0.797 ± 0.09

0.04

Table 2. Comparisons of the ratio of measured resting energy expenditure (REE) to basal metabolic rate (BMR), SOFA score, blood concentration of CRP, energy intake, and respiratory quotient between the first and last intubation days. Paired t-test was performed for comparison of REE/BMR. Mann-Whitney U test was used for analyses of the remaining data.

 

Number of  sedatives used

 

 

0

1

2 ≤

P

1st day

1.17 ± 0.13 (3)

1.06 ± 0.19 (10)

1.10 ± 0.15 (34)

0.60

2nd day

1.18 ± 0.13 (3)

1.11 ± 0.16 (6)

1.08 ± 0.15 (38)

0.52

last day

1.13 ± 0.16 (8)

1.09 ± 0.14 (16)

1.14 ± 0.19 (23)

0.59

Table 3. Comparison of the ratios of measured resting energy expenditure (REE) to basal metabolic rate (BMR) on the three days in terms of the number of sedatives used. One-way ANOVA was used for analysis.

Table S1. Demographic data of patients, resting energy expenditure, calculated energy expenditure, APACHE II score, blood concentration of CRP, SOFA score, respiratory quotient, energy intake, and sedative usage in the study subjects.

number

age
(years)

sex

disease

intubated
days

height
(cm)

weight
(kg)

BMI
(kg/m²)

HBE
(kcal) 

Schofield
(kcal)

REE
1st intubated day (kcal)

REE
2nd intubated day (kcal)

REE
last intubated day (kcal)

APACHEⅡ score
on ICU admission

CRP
1st intubated day (mg/dL)

CRP
2nd intubated day (mg/dL)

CRP
last intubated day (mg/dL)

SOFA
1st intubated day

SOFA
2nd intubated day

SOFA
last intubated day

RQ
1st intubated day

RQ
2nd intubated day

RQ
last intubated day

energy intake
1st intubated day (kcal)

energy intake
2nd intubated day (kcal)

energy intake
last intubated day (kcal)

sedatives
1st intubated day (mg/hr)

sedatives
2nd intubated day (mg/hr)

sedatives
last intubated day (mg/hr)

1

45

female

miliary tuberculosis

22

159

31

11.2

1027

1097

1239

1043

1263

32

21

18

1.1

13

10

8

0.69

0.78

0.74

500

690

1440

propofol 80 / fentanyl 0.05

propofol 100 / fentanyl 0.025

fentanyl 0.05

2

63

female

pneumonia

12

145

39

18.5

994

1012

1183

1137

1040

33

33.9

32

6.2

12

14

7

0.88

0.81

0.81

680

680

1250

propofol 50 / fentanyl 0.05

propofol 50 / fentanyl 0.05

fentanyl 0.05

3

76

male

pneumonia

20

178

70

18.8

1406

1407

1604

1544

1307

20

30.1

28

3

9

8

4

0.64

0.8

0.78

480

960

1520

dexmedetomidine 0.032 / fentanyl 0.05

dexmedetomidine 0.032 / fentanyl 0.075

fentanyl 0.05

4

60

male

necrotising fasciitis

22

174

69

22.4

1478

1395

1640

1762

1637

17

22

22.8

2

5

7

3

0.74

0.85

0.97

240

680

2080

propofol 100 / fentanyl 0.05

dexmedetomidine 0.024 / fentanyl 0.05

0

5

49

male

renal abcess

6

157

56

22.8

1292

1515

1682

1551

1424

22

11.2

12

5.9

14

14

3

0.73

0.74

0.81

540

970

1180

propofol 100

propofol 60

propofol 60

6

38

male

phlegmone

6

174

86

28.3

1864

1859

2268

2148

2240

22

25.5

23.3

9.4

9

8

4

0.72

0.76

0.69

560

560

1540

propofol 150 / fentanyl 0.05

propofol 150 / fentanyl 0.05

fentanyl 0.05

7

42

female

cholangitis

4

162

81

31

1530

1503

1696

1592

1480

31

13.8

9.3

6.2

16

14

11

0.69

0.71

0.77

400

1080

1080

0

0

0

8

42

male

gastrointestinal perforation

3

174

111

36.5

2176

2145

1894

1772

2175

26

9.4

15.9

28.7

9

4

2

0.78

0.85

0.75

390

760

760

propofol 100 / fentanyl 0.05

propofol 150 / fentanyl 0.05

propofol 150 / fentanyl 0.05

9

77

female

candidemia

16

138

38

20

906

1003

1225

1100

1297

32

11.8

9.2

6.1

15

12

8

0.77

0.95

0.73

840

840

1060

dexmedetomidine 0.024 / fentanyl 0.05

dexmedetomidine 0.024 / fentanyl 0.05

dexmedetomidine 0.032 / fentanyl 0.05

10

72

male

pneumonia

4

165

40

14.6

950

1056

1072

1144

1018

20

3.7

5.6

7.2

9

9

6

0.68

1

0.76

1760

1760

1790

propofol 50

propofol 50

propofol 60 / fentanyl 0.05

11

68

female

pseudomembranous colitis

20

150

35

15.6

941

976

1015

1142

1228

32

22.6

27

4

10

11

6

0.77

0.78

1.06

300

820

1640

0

0

0

12

21

female

phlegmone

14

140

35

17.9

1144

1005

902

1109

1194

13

26.2

13.9

3.1

7

7

4

0.63

0.86

0.81

580

1060

1580

propofol 120 / fentanyl 0.025

propofol 120 / fentanyl 0.05

propofol 120 / fentanyl 0.05

13

73

female

extremity gangrene

4

147

30

13.9

865

930

1132

1122

1158

22

1

2.3

1

8

7

4

0.72

0.8

0.76

630

630

630

0

0

0

14

69

male

cholangitis

3

158

64

25.8

1275

1340

994

1172

1195

23

3.1

3

7.5

10

8

2

0.68

0.74

0.79

520

520

400

propofol 50 / dexmedetomidine 0.02 / fentanyl 0.05

propofol 50 / dexmedetomidine 0.024 / fentanyl 0.075

dexmedetomidine 0.024 / fentanyl 0.075

15

55

female

necrotising fasciitis

8

165

65

23.9

1318

1373

1349

1248

1337

25

44.8

45.4

4.6

11

12

3

0.69

0.78

0.84

630

1230

1540

propofol 50 / dexmedetomidine 0.024 / fentanyl 0.075

propofol 50 / dexmedetomidine 0.024 / fentanyl 0.075

fentanyl 0.05

16

60

female

pneumonia

6

159

84

33.2

1468

1421

1813

1696

1852

17

2.9

25.1

8.1

17

15

12

0.86

0.73

0.72

200

680

1580

propofol 80 / dexmedetomidine 0.032 / fentanyl 0.075

propofol 80 / dexmedetomidine 0.4 / fentanyl 0.075

propofol 60 / dexmedetomidine 0.4 / fentanyl 0.05

17

82

male

pneumonia

25

152

47

20.3

916

1138

1158

1367

1161

22

28.7

27

2.1

12

13

9

0.72

0.68

0.73

870

870

1480

dexmedetomidine 0.024 / fentanyl 0.075

dexmedetomidine 0.024 / fentanyl 0.05

fentanyl 0.025

18

50

male

pelvic abscess

6

160

72

28.1

1523

1698

1634

1582

1692

25

16.5

20.8

20.1

19

19

14

1

0.7

0.74

430

620

940

propofol 120 / fentanyl 0.05

propofol 80 / fentanyl 0.05

propofol 120 / dexmedetomidine 0.32 / fentanyl 0.05

19

37

male

extremity gangrene

4

165

58

21.3

1443

1538

1665

1514

1535

25

25.2

25

22.1

16

15

12

0.79

0.85

0.81

200

1000

1240

dexmedetomidine 0.032 / fentanyl 0.05

dexmedetomidine 0.04 / fentanyl 0.05

dexmedetomidine 0.04 / fentanyl 0.05

20

37

male

pneumonia

3

172

51

17.2

1372

1457

1221

1081

1131

16

10.8

18.1

17.7

8

9

7

0.79

0.8

0.85

560

1240

1240

propofol 70

propofol 50 / midazolam 10

propofol 50 / midazolam 10

21

78

male

septic arthritis

7

152

69

29.9

1254

1395

1652

1294

1698

24

27.8

27.5

8.9

15

15

12

0.68

0.87

0.79

300

630

1240

dexmedetomidine 0.024 / fentanyl 0.05

dexmedetomidine 0.024 / fentanyl 0.05

dexmedetomidine 0.032 / fentanyl 0.1

22

63

male

pneumonia

3

174

54

17.8

1256

1220

1624

1586

1586

16

21.5

20.3

21

9

10

8

0.7

0.69

0.72

240

520

840

propofol 100 / fentanyl 0.05

propofol 50 / fentanyl 0.075

dexmedetomidine 0.02 / fentanyl 0.075

23

70

male

tetanus

23

164

57

21.2

1192

1255

1445

1519

1647

25

8.8

20.1

1.4

12

12

7

0.87

0.78

0.84

360

1080

1700

propofol 150 / fentanyl 0.05

propofol 100 / fentanyl 0.05

midazoram 10

24

53

male

pneumonia

4

164

61

22.7

1368

1572

1512

1417

1415

19

17.6

27.2

7.2

12

12

9

0.78

0.83

0.85

740

740

1340

propofol 100 / fentanyl 0.05

propofol 100 / fentanyl 0.025

propofol 100 / fentanyl 0.05

25

59

male

pneumonia

3

185

68

19.9

1529

1652

2134

2018

2185

15

4

11.3

7.4

9

9

3

0.71

0.7

0.75

300

300

300

dexmedetomidine 0.04 / fentanyl 0.05

dexmedetomidine 0.04 / fentanyl 0.05

dexmedetomidine 0.024 / fentanyl 0.05

26

82

male

pneumonia

4

163

57

21.5

1111

1255

1426

1413

1647

16

26.8

24.4

6.8

10

9

6

0.7

0.68

0.71

580

1060

1540

dexmedetomidine 0.024

dexmedetomidine 0.024

dexmedetomidine 0.024 / fentanyl 0.05

27

28

female

phlegmone

4

162

77

29.3

1554

1527

1384

1504

1517

35

2.5

9.7

6.9

13

11

8

0.71

0.77

0.81

400

640

880

fentanyl 0.1

dexmedetomidine 0.02 / fentanyl 0.05

dexmedetomidine 0.02 / fentanyl 0.05

28

74

male

pneumonia

3

163

56

22.2

1154

1243

1147

1079

1118

26

6

8.1

9.2

8

8

2

0.86

0.84

0.68

500

660

1380

propofol 80 / dexmedetomidine 0.02 / fentanyl 0.05

propofol 150 / dexmedetomidine 0.024 / fentanyl 0.05

propofol 150 / dexmedetomidine 0.02 / fentanyl 0.05

29

56

female

tetanus

13

150

52

23.1

1161

1268

1193

1080

1268

18

0.5

1.9

6.8

9

7

5

0.89

0.93

0.92

680

620

1600

propofol 80 / fentanyl 0.05

propofol 60 / fentanyl 0.05

fentanyl 0.05

30

80

male

pneumonia

3

150

44

19.6

876

1102

991

1014

978

18

8.3

6

7

8

7

3

0.75

0.82

0.76

200

200

400

dexmedetomidine 0.02

dexmedetomidine 0.028

dexmedetomidine 0.028

31

80

male

pneumonia

6

157

59

23.9

1122

1278

1221

1198

1268

20

1.1

3

4

10

9

8

0.76

0.72

0.8

420

420

840

propofol 50 / fentanyl 0.025

propofol 50 / fentanyl 0.025

0

32

73

male

pneumonia

9

162

81

30.9

1499

1536

1672

1531

1432

19

10.1

12.3

5.6

8

8

4

0.68

0.7

0.71

240

800

920

propofol 100 / fentanyl 0.05

propofol 50 / dexmedetomidine 0.032 / fentanyl 0.05

propofol 40 / dexmedetomidine 0.024 / fentanyl 0.05

33

85

male

gastrointestinal perforation

4

165

50

18.4

1004

1173

1213

1293

1197

34

15.3

19.3

24.5

13

12

9

0.79

0.75

0.82

380

480

1280

propofol 60 / fentanyl 0.05

propofol 100 / fentanyl 0.05

propofol 80 / fentanyl 0.05

34

66

female

ileus

18

151

40

17.5

1001

1021

1032

1003

1103

25

4.2

21

2.1

12

10

6

0.68

0.71

0.77

300

640

900

dexmedetomidine 0.024 / fentanyl 0.05

dexmedetomidine 0.032 / fentanyl 0.05

fentanyl 0.05

35

74

male

pneumonia

8

165

44

16.2

993

1102

1308

1238

1143

39

33.4

35.6

4.1

12

14

10

0.86

0.78

0.89

200

1120

1570

fentanyl 0.05

dexmedetomidine 0.04 / fentanyl 0.05

dexmedetomidine 0.02 / fentanyl 0.05

36

69

female

miliary tuberculosis

3

146

31

14.5

895

940

852

797

767

33

5.8

20.7

9.1

8

6

6

0.82

0.72

0.74

680

680

780

fentanyl 0.025

fentanyl 0.025

fentanyl 0.025

37

62

male

pneumonia

4

162

53

20.2

1223

1208

1107

1245

1112

20

2.2

1.5

0.7

6

8

5

0.89

0.91

0.86

400

960

1440

dexmedetomidine 0.024

dexmedetomidine 0.02 / fentanyl 0.05

dexmedetomidine 0.024

38

79

female

gastrointestinal perforation

3

150

50

22.1

1029

1112

1183

1221

1255

24

19.9

13

11.3

9

6

4

0.71

0.72

0.66

400

400

830

dexmedetomidine 0.032 / fentanyl 0.05

dexmedetomidine 0.04 / fentanyl 0.05

dexmedetomidine 0.032 / fentanyl 0.05

39

76

female

gastrointestinal perforation

4

152

62

22.2

1167

1221

1047

1031

1162

23

10

23.1

6.8

10

10

5

0.71

0.87

0.95

320

960

1480

propofol 50 / fentanyl 0.05

propofol 50 / fentanyl 0.05

fentanyl 0.025

40

61

male

pneumonia

3

156

67

27.5

1358

1372

1133

1231

1348

18

2.2

21.7

13.2

7

6

2

0.83

0.71

0.68

200

400

1440

dexmedetomidine 0.032 / fentanyl 0.05

dexmedetomidine 0.032 / fentanyl 0.05

dexmedetomidine 0.024

41

80

female

pneumonia

20

133

35

19.8

857

976

911

825

843

31

1.6

5.3

2.4

12

10

6

0.73

0.77

1.02

200

200

880

dexmedetomidine 0.02 / fentanyl 0.05

dexmedetomidine 0.02 / fentanyl 0.05

0

42

61

male

pneumonia

3

166

60

21.8

1303

1290

1365

1412

1241

26

7.6

16.3

18.1

10

9

5

0.79

0.73

0.75

320

320

320

propofol 50 / fentanyl 0.05

propofol 50 / fentanyl 0.05

propofol 50 / fentanyl 0.025

43

72

male

pneumonia

20

163

47

17.7

1036

1138

1174

1275

1239

33

5.8

8.7

7.4

13

12

8

0.97

0.75

0.78

200

780

1540

dexmedetomidine 0.02 / fentanyl 0.05

dexmedetomidine 0.024 / fentanyl 0.05

dexmedetomidine 0.02 / fentanyl 0.05

44

70

male

pneumonia

7

171

46

15.7

1066

1126

881

1001

1010

39

4.2

3.5

2.9

13

14

11

0.74

0.7

0.82

200

200

780

midazolam 5

midazoram 5

0

45

63

female

tetanus

31

153

54

23.1

1148

1148

1084

1362

1460

26

2.8

5

1

10

8

3

0.75

0.77

0.83

360

600

1120

propofol 150 / fentanyl 0.05

propofol 150 / fentanyl 0.05

0

46

77

male

pneumonia

6

155

65

27.1

1209

1348

1408

1427

1683

25

27.4

23.5

8.7

9

10

6

0.87

0.73

0.75

200

200

880

propofol 100 / fentanyl 0.05

propofol 150 / fentanyl 0.05

propofol 100 / dexmedetomidine 0.04 / fentanyl 0.05

47

56

female

gastrointestinal perforation

7

156

47

19.3

1126

1227

1205

1269

1321

35

24.8

28.7

12.8

14

11

8

0.73

0.7

0.87

400

600

840

dexmedetomidine 0.02 / fentanyl 0.05

dexmedetomidine 0.02 / fentanyl 0.05

fentanyl 0.025

Figure 1. Comparison of the energy expenditure measured by indirect calorimetry (IC) and calculated by Harris-Benedict and Schofield equations. Basal metabolic rate (BMR) was multiplied by 1.4, as a tentative stress factor. Resting energy expenditure (REE) measured by IC was always smaller than estimated total energy expenditure by the prediction equation (two-way ANOVA with post hoc Bonferroni test, P < 0.0001).

Figure 2. Relationship between resting energy expenditure (REE) and basal metabolic rate (BMR). REE and BMR correlated well on the first, second and last intubation days (R = 0.79. 0.76, and 0.78). The value of REE/BMR was always approximately 1.1.