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.

Prevalence and Impact of Preexisting Comorbidities on Overall Clinical Outcomes of Hospitalized COVID-19 Patients.

COVID-19 risk increases with comorbidities, and the effect is magnified due to the contribution of individual and combined comorbidities to the overall clinical outcomes. We aimed to explore the influence of demographic factors, clinical manifestations, and underlying comorbidities on mortality, severity, and hospital stay in COVID-19 patients. Therefore, retrospective chart reviews were performed to identify all laboratory-confirmed cases of SARS-CoV-2 infection in Apollo Hospitals, Hyderabad, between March 2020 and August 2020.A total of 369 confirmed SARS-CoV-2 cases were identified: 272 (73.7%) patients were male, and 97 (26.2%) were female. Of the confirmed cases, 218 (59.1%) had comorbidities, and 151 (40.9%) were devoid of comorbidities. This study showed that old age and underlying comorbidities significantly increase mortality, hospital stay, and severity due to COVID-19 infection. The presence of all four comorbidities, diabetes mellitus (DM) + Hypertension (HTN) + coronary artery disease (CAD) + chronic kidney disease (CKD), conferred the most severity (81%). The highest mortality (OR: 44.03, 95% CI: 8.64-224.27) was observed during the hospital stay (12.73 ± 11.38; 95% CI: 5.08-20.38) in the above group. Multivariate analysis revealed that nonsurvivors are highest (81%) in (DM + HTN + CAD + CKD) category with an odds ratio (95% CI) of 44.03 (8.64-224.27). Age, gender, and comorbidities adjusted odds ratio decreased to 20.25 (3.77-108.77). Median survival of 7 days was observed in the (DM + HTN + CAD + CKD) category. In summary, the presence of underlying comorbidities has contributed to a higher mortality rate, greater risk of severe disease, and extended hospitalization periods, hence, resulting in overall poorer clinical outcomes in hospitalized COVID-19 patients.

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.