Energy expenditure in COVID-19 mechanically ventilated patients: A comparison of three methods of energy estimation

Abstract

Background: Indirect calorimetry (IC) is the gold standard for measuring resting energy expenditure. Energy expenditure (EE) estimated by ventilator-derived carbon dioxide consumption (EEVCO₂ ) has also been proposed. In the absence of IC, predictive weight-based equations have been recommended to estimate daily energy requirements. This study aims to compare simple predictive weight-based equations with those estimated by EEVCO₂ and IC in mechanically ventilated patients of COVID-19.

Methods: Retrospective study of a cohort of critically ill adult patients with COVID-19 requiring mechanical ventilation and artificial nutrition to compare energy estimations by three methods through the calculation of bias and precision agreement, reliability, and accuracy rates.

Results: In 58 mechanically ventilated patients, a total of 117 paired measurements were obtained. The mean estimated energy derived from weight-based calculations was 2576 ± 469 kcal/24 h, as compared with 1507 ± 499 kcal/24 h when EE was estimated by IC, resulting in a significant bias of 1069 kcal/day (95% CI [-2158 to 18.7 kcal]; P < 0.001). Similarly, estimated mean EEVCO₂ was 1388 ± 467 kcal/24 h when compared with estimation of EE from IC. A significant bias of only 118 kcal/day (95% CI [-187 to 422 kcal]; P < 0.001), compared by the Bland-Altman plot, was noted.

Conclusion: The energy estimated with EEVCO₂ correlated better with IC values than energy derived from weight-based calculations. Our data suggest that the use of simple predictive equations may potentially lead to overfeeding in mechanically ventilated patients with COVID-19.

Keywords: COVID-19; EEVCO2; energy expenditure; indirect calorimetry; predictive equation.