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

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.

Tailoring nutrition therapy amid the COVID-19 pandemic: Does it work?

BACKGROUND: The COVID-19 pandemic has been a challenge for nutrition monitoring and delivery. This study evaluates clinical and nutritional characteristics of patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and investigates the relationship between nutrition delivery and clinical outcomes. METHODS: Prospective observational study of adults admitted for >24 hrs to a tertiary-care hospital during a period of 2months. Data was collected on disease severity, energy, protein delivery and adequacy, use of mechanical ventilation (MV), hospital length of stay (LOS). Multivariate logistic regression models were used to determine the associations with mortality as the primary outcome. RESULTS: 1083 patients: 69% male (n = 747), 31% females (n = 336), mean age 58.2 ± 12.8 with 26.6 ± 4.32 BMI were analysed. 1021 patients survived and 62 deaths occurred, with 183 and 900 patients in the ICU and ward, respectively. Inadequate calorie and protein delivery had significantly higher mortality than those with adequate provision (p < 0.001) among the ICU patients. In bivariate logistic regression analysis, inadequacy of energy and protein, disease severity, comorbidities ≥3, NRS score ≥3 and prone ventilation correlates with mortality (p < 0.001). In multivariate logistic regression analysis of the ICU patients, energy inadequacy (OR:3.6, 95%CI:1.25-10.2) and prone ventilation (OR:11.0, 95%CI:3.8-31.9) were significantly (p < 0.05) associated with mortality after adjusting for disease severity, comorbidities and MV days. CONCLUSION: Most patients infected with SARS-CoV-2 are at nutrition risk that can impact outcome. Our data suggest that addressing nutritional adequacy can be one of the measures to reduce hospital LOS, and mortality among nutritionally risk patients.