Resting energy expenditure by indirect calorimetry versus the ventilator-VCO2 derived method in critically ill patients: The DREAM-VCO2 prospective comparative study. (October 2020)

• Record Type: Journal Article
• Authors: Koekkoek, W.A.C.; Xiaochen, G.; van Dijk, D.; van Zanten, A.R.H.
• Is Part Of: Clinical nutrition ESPEN. Volume 39(2020)
• Page Start: 137
• Page End: 143
• Publication Date: 2020-10
• Subjects: Nutrition -- Indirect calorimetry -- Respiratory quotient -- Resting energy expenditure -- Mechanical ventilation; Nutritionally induced diseases -- Periodicals; Metabolism -- Disorders -- Periodicals; 616.39005
• DOI: 10.1016/j.clnesp.2020.07.005
• Languages: English
• ISSNs: 2405-4577

Abstract

Summary: Background & aims: Both overfeeding and underfeeding of intensive care unit (ICU) patients are associated with worse outcomes. Predictive equations of nutritional requirements, though easily implemented, are highly inaccurate. Ideally, the individual caloric target is based on the frequent assessment of energy expenditure (EE). Indirect calorimetry is considered the gold standard but is not always available. EE estimated by ventilator-derived carbon dioxide consumption (EEVCO2 ) has been proposed as an alternative to indirect calorimetry, but there is limited evidence to support the use of this method. Methods: We prospectively studied a cohort of adult critically ill patients requiring mechanical ventilation and artificial nutrition. We aimed to compare the performance of the EEVCO2 with the EE measured by indirect calorimetry through the calculation of bias and precision (accuracy), agreement, reliability and 10% accuracy rates. The effect of including the food quotient (nutrition intake derived respiratory quotient) in contrast to a fixed respiratory quotient (0.86), into the EEVCO2 formula was also evaluated. Results: In 31 mechanically ventilated patients, a total of 414 paired measurements were obtained. The mean estimated EEVCO2 was 2134 kcal/24 h, and the mean estimated EE by indirect calorimetry was 1623 kcal/24 h, depicting a significant bias of 511 kcal (95% CI 467–560, p < 0.001). The precision of EEVCO2 was low (lower and upper limit of agreement −63.1 kcal and 1087. o kcal), the reliability was good (intraclass correlation coefficient 0.613; 95% CI 0.550–0.669, p < 0.001) and the 10% accuracy rate was 7.0%. The food quotient was not significantly different from the respiratory quotient (0.870 vs. 0.878), with a small bias of 0.007 (95% CI 0.000–0.015, p = 0.54), low precision (lower and upper limit of agreement −0.16 and 0.13), poor reliability (intraclass correlation coefficient 0.148; 95% CI 0.053–0.240, p = 0.001) and a 10% accuracy rate of 77.5%. Estimated mean EEVCO2, including the food quotient, was 2120 kcal/24 h, with a significant bias of 496 kcal (95% CI 451–542; p < 0.001) and low precision (lower and upper limit of agreement −157.6 kcal and 1170.3 kcal). The reliability with EE estimated by indirect calorimetry was good (intraclass correlation coefficient 0.610, 95% CI 0.550–0.661, p < 0.001), and the 10% accuracy rate was 9.2%. Conclusions: EEVCO2, compared with indirect calorimetry, overestimates actual energy expenditure. Although the reliability is acceptable, bias is significant, and the precision and accuracy rates are unacceptably low when the VCO2 method is used. Including the food quotient into the EEVCO2 equation does not improve its performance. Predictive equations, although inaccurate, may even predict energy expenditure better compared with the VCO2 -method. Indirect calorimetry remains the gold standard method.