Are We Feeding Our Critically Ill Covid Patients, Right?

ABSTRACT

Objective: Primary objective: To study the energy expenditure in a significant number of mechanically ventilated COVID-19 patients in ARDS. Secondary objective: 1. To compare the deviations seen with predictive equations based on actual and ideal body weight. 2. To compare the EE derived versus the VCO2 based estimation. Materials and methods: The Resting Energy expenditure (REE) of 60 patients was measured with the help of the ESCOVYX-module for indirect calorimetry using the GE CARESCAPE R860 ventilator. The steady-state was validated by ensuring a respiratory quotient of 0.7-0.8 and variation of 5% for VCO2 and VO2 for at least 30 minutes. It was ensured that for 60 minutes the patient was not disturbed by endotracheal tube suction, no ventilatory changes were performed, and no vasopressors alteration was done. The absence of a leak was ascertained on the ventilator. The calculation was done from day 2 onwards after mechanical ventilation and subsequently every 2nd day till the patient was on ventilator. The resting energy expenditure was also calculated by the simple predictive equations as per ESPEN COVID-19 guidelines, i.e., 25-30 kcal/kg of which the mean of 27 kcal/kg was chosen. Bodyweight was estimated by height equation 50 kg for 5 ft plus 2.3 kg for each inch >5 feet. The quantitative measures were studied by Bland and Altman plot to describe an agreement between the two by constructing a line of agreement. The limits were calculated by using the mean and standard deviation of the difference between the two measurements. Statistics The EE derived from the two methods is compared by Bland and Altman plots. Reliability and adequacy between the methods are tested using ROC curves with kappa coefficient (reliability coefficient). For the coefficient of variation, ANOVA is used when applicable. IBM SPSS Statistics for Windows, version 24.0 (IBM Corporation, Chicago, USA) was used to perform analyses. MedCalc version 19 (MedCalc bv, Ostend, Belgium) was used to create BlandeAltman plots. Results: No 1 The estimated mean energy expenditure derived from weight-based calculations was 2576 ± 469 kcal/24 hours, which was significantly higher when compared with an estimation of EE from indirect calorimetry of 1507 ± 499 kcal/24 hours (15-20 kcal/kg/day). This correlation is significant but not useful for prediction (R = 0.345). No 2 The estimated mean EEVCO2 was 1388 ± 467 kcal/24 hours compared with an estimation of EE from indirect calorimetry of 1507 ± 499 kcal/24 hours. The Bias and precision, as visualized by the limits of agreement, are shown in the Bland-Altman plot where there was a significant bias of only 118 kcal/day (95% CI (-187 to 422 kcal);p < 0.001. The regression analysis reveals that for every one unit change in EEVCO2 value, there is one unit change in EE by IC. This correlation is significant (R = 0.951). Similarly, the Bland-Altman plot was tested between the estimated mean EEVCO2 and EE derived from weight-based calculations. The difference was wide with significant bias of 1187 kcal/day (95% CI (-2256 to (-118) kcal);p < 0.001). Conclusion: The ESPEN guidelines (30 kcal/kg through the disease state) for energy estimation may not be right in COVID-19 patients and the study calls for more personalisation of energy estimation by the correct use of indirect calorimetry.