Ventilator-derived carbon dioxide production to assess energy expenditure in critically ill patients: proof of concept

Abstract

Introduction: Measurement of energy expenditure (EE) is recommended to guide nutrition in critically ill patients. Availability of a gold standard indirect calorimetry is limited, and continuous measurement is unfeasible. Equations used to predict EE are inaccurate. The purpose of this study was to provide proof of concept that EE can be accurately assessed on the basis of ventilator-derived carbon dioxide production (VCO2) and to determine whether this method is more accurate than frequently used predictive equations.

Methods: In 84 mechanically ventilated critically ill patients, we performed 24-h indirect calorimetry to obtain a gold standard EE. Simultaneously, we collected 24-h ventilator-derived VCO2, extracted the respiratory quotient of the administered nutrition, and calculated EE with a rewritten Weir formula. Bias, precision, and accuracy and inaccuracy rates were determined and compared with four predictive equations: the Harris-Benedict, Faisy, and Penn State University equations and the European Society for Clinical Nutrition and Metabolism (ESPEN) guideline equation of 25 kcal/kg/day.

Results: Mean 24-h indirect calorimetry EE was 1823 ± 408 kcal. EE from ventilator-derived VCO2 was accurate (bias +141 ± 153 kcal/24 h; 7.7 % of gold standard) and more precise than the predictive equations (limits of agreement -166 to +447 kcal/24 h). The 10 % and 15 % accuracy rates were 61 % and 76 %, respectively, which were significantly higher than those of the Harris-Benedict, Faisy, and ESPEN guideline equations. Large errors of more than 30 % inaccuracy did not occur with EE derived from ventilator-derived VCO2. This 30 % inaccuracy rate was significantly lower than that of the predictive equations.

Conclusions: In critically ill mechanically ventilated patients, assessment of EE based on ventilator-derived VCO2 is accurate and more precise than frequently used predictive equations. It allows for continuous monitoring and is the best alternative to indirect calorimetry.

Figures

Fig. 1

Consolidated Standards of Reporting Trials diagram representing the inclusion of patients. FiO2 fraction of inspired oxygen, ICU intensive care unit, MV mechanical ventilation, PEEP positive end-expiratory pressure

Fig. 2

Correlation and agreement between the methods used to assess energy expenditure (EE) and gold standard indirect calorimetry. a Regression plots showing the correlation between the different methods used to assess EE and gold standard indirect calorimetry. b Bland–Altman plots showing the agreement between the methods used to assess EE and gold standard indirect calorimetry. The solid lines indicate the bias (mean difference with indirect calorimetry). The thick dashed lines indicate the limits of agreement (bias ±2 standard deviations). Every dot represents 1 of 84 patients. The x-axis represents the mean of the method used to assess EE and gold standard indirect calorimetry. The y-axis represents the difference in EE in kilocalories per 24 h between the method used and gold standard indirect calorimetry. EE:Esp25, Energy expenditure calculated with the European Society for Clinical Nutrition and Metabolism guideline equation of 25 kcal/kg/day; EE:Faisy, Energy expenditure calculated with the Faisy equation; EE:HB, Energy expenditure calculated with the Harris–Benedict equation; EE:PSU, Energy expenditure calculated with the Penn State University 2003b equation; EE:VCO2, Energy expenditure from ventilator-derived volume of carbon dioxide and nutritional respiratory quotient

Fig. 3

Bias and precision of the methods used to assess energy expenditure (EE). The x-axis shows the different methods used to assess EE. The y-axis represents the bias (mean difference with gold standard indirect calorimetry) and the precision (±1 standard deviation) in kilocalories per day. *Variance of the bias significantly smaller than that of the predictive equations. EE:Esp25, Energy expenditure calculated with the European Society for Clinical Nutrition and Metabolism guideline equation of 25 kcal/kg/day; EE:Faisy, Energy expenditure calculated with the Faisy equation; EE:HB, Energy expenditure calculated with the Harris–Benedict equation; EE:PSU, Energy expenditure calculated with the Penn State University 2003b equation; EE:VCO2, Energy expenditure from ventilator-derived volume of carbon dioxide and nutritional respiratory quotient

Fig. 4

Accuracy and inaccuracy of the different methods quantified in less than 10 % and less than 15 % accuracy rates and greater than 25 % and greater than 30 % inaccuracy rates. a Less than 10 % and less than 15 % accuracy rates were defined as the proportion of patients for whom energy expenditure (EE) was predicted within 10 % and within 15 % of gold standard EE:Calorimetry. b Greater than 25 % and greater than 30 % inaccuracy rates were defined as the proportion of patients for whom EE differed by more than 25 % and more than 30 % from gold standard EE:Calorimetry. The x-axis shows the different methods used to assess EE. The y-axis represents the accuracy rates or inaccuracy rates in percentages. The error bars reflect upper bounds of 95 % confidence intervals. *Significantly different from EE:VCO2 (p values are shown in Table 3). EE:Esp25, Energy expenditure calculated with the European Society for Clinical Nutrition and Metabolism guideline equation of 25 kcal/kg/day; EE:Faisy, Energy expenditure calculated with the Faisy equation; EE:HB, Energy expenditure calculated with the Harris–Benedict equation; EE:PSU, Energy expenditure calculated with the Penn State University 2003b equation; EE:VCO2, Energy expenditure from ventilator-derived volume of carbon dioxide and nutritional respiratory quotient