Original Article |
Corresponding author: Siyana Nikolova ( siyana.n.k@gmail.com ) © 2023 Siyana Nikolova, Emral Kyosebekirov, Emil Mitkovski, Dimitar Kazakov, Valentin Stoilov, Georgi Pavlov, Chavdar Stefanov.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Nikolova S, Kyosebekirov E, Mitkovski E, Kazakov D, Stoilov V, Pavlov G, Stefanov C (2023) Comparative characteristics of some methods for estimating energy expenditure in critically ill mechanically ventilated patients. Folia Medica 65(6): 909-914. https://doi.org/10.3897/folmed.65.e100965
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Aim: To compare the energy expenditure (EE) assessed by ventilator-derived carbon dioxide production (EE–VCO2-ventilator) and the energy expenditure calculated from six predictive equations with the gold standard energy expenditure measured with indirect calorimetry (IC) in mechanically ventilated patients.
Materials and methods: This is a prospective, non-randomized, one-month study which included six mechanically ventilated patients with FiO2 <60% and PEEP <10 mbar. Thirty-minute measurements were taken using a Cosmed Q-NRG+ metabolic monitor. The average ventilator-derived VCO2 from the Drager Evita Infinity V500 respirator (VʹCO2, ml/min) was calculated for the same period. The IC-measured EE (MEE-IC) was compared with EE–VCO2-ventilator by a formula proposed in ESPEN (8.19×VCO2) and with six predictive equations.
Results: Mean MEE-IC was 1650±365 kcal. Mean measured EE–VCO2-ventilator was 1669±340 kcal. A statistically nonsignificant difference was found between the two measurements (p=0.84, correlation coefficient 0.98). Of the predictive equations we compared, the best correlation to the reference method was the Penn State 3 with mean EE of 1679±356 (p=0.81, correlation coefficient of 0.78).
Conclusions: In critically ill mechanically ventilated patients, the assessment of EE based on a ventilator-derived VCO2 is an alternative to IC and is more accurate than most predictive equations.
calories, energy metabolism, indirect calorimetry, predictive equations
Nutritional support is an integral part of intensive care. In practice, caloric needs are estimated using both measured energy expenditure (MEE) and a fixed sum of calories based on predictive equations.[
EE can be accurately calculated with IC which measures oxygen consumption (VO2) and carbon dioxide production (VCO2) from the respiratory mixture.[
ЕE kcal/day = 3.941×VO2 (L/min) + 1.11×VCO2 (L/min)×1440
Although IC is the reference method for EE assessment[
In CIPs, the EE calculated by predictive equations shows a significant difference from MEE measured by IC.[
An alternative method is the assessment of EE based on ventilator-derived VCO2. Modern mechanical ventilators can measure VCO2 continuously, making the method practical and allowing long-term monitoring.[
ЕE kcal/day = (3.941×VCO2/RQ + 1.11×VCO2)×1440
To date, several studies have examined the EE–VCO2-ventilator with mixed results.[25-27,31-33]
The aim of the present study was to compare the EE–VCO2-ventilator in mechanically ventilated patients calculated by the formula (8.19×VCO2)[
This is a prospective, non-randomized study conducted over a period of one month. It included six mechanically ventilated patients who were hospitalized and treated in the ICU of the Clinic of Anesthesiology and Intensive Care at St George University Hospital in Plovdiv. Thirty 30-minute measurements were taken using a Cosmed Q-NRG+ metabolic monitor. Three to seven measurements per patient were performed on different days. The sample of patients was random. They were between 52 and 62 years old, two men and four women. Two patients with polytrauma, one of them with a dominant thoracic trauma, with a thoracic drain placed, but with a reported leak from mechanical ventilation of less than 8%. The remaining patients had subdural hematoma or intracerebral hemorrhage. In 8 of the measurements, the patients were conscious and evaluated by GCS, with an average score of 12 points. In the rest of the measurements, the patients were sedated and assessed according to the Ramsay sedation scale, with an average score of 3-4 points. One of the patients was connected to the ventilator with a tracheostomy cannula, the others were connected with endotracheal tubes. In 14 of the measurements, the patients were on pressure support ventilation, in the remaining measurements, they were in a combined mode - controlled plus supported ventilation, the average measured minute ventilation was 8 liters, and the average leak from mechanical ventilation was 4%. Only in three measurements did the patients receive vasopressors but continued to have mean arterial pressures greater than 65 mmHg; otherwise, all patients had stable hemodynamics. The calorimeter was calibrated according to the manufacturer’s recommendations with a routine Pneumotach test before each measurement, as well as a monthly Gas Analyzer test and a Blower test. Patients’ inclusion criteria were stable condition at least 30 minutes before measurement, normocapnia, ventilation with FiO2 <60% and PEEP <10 mbar. The average CO2 production from the Drager Evita Infinity V500 respirator (VʹCO2, ml/min) was tracked for the same period. The МEE-IC was compared with EE–VCO2-ventilator calculated by this formula - 8.19×VCO2[
The average МEЕ–IC was 1650 kcal. The mean measured EЕ–VCO2-ventilator was 1669 kcal. A statistically nonsignificant difference was found between the two measurements (p=0.84, r=0.98), the mean difference to the reference method and standard deviation (19±68). Of the predictive equations we compared, the lowest difference to the reference method was calculated with the Penn State 3 (30±236), mean EE of 1679 (p=0.81, r=0.78). The obtained results are presented in Table
Comparative characteristics of different methods for estimating energy expenditure
Measurement | Mean | Mean ΔcEE-mEE ± SD | p-value | r |
VCO2 (ml/min) | ||||
IC | 194 | |||
Ventilator | 204 | 0.44 | 0.91 | |
Energy expenditure (kcal/d) | ||||
IC | 1650 | |||
VCO2-ventilator | 1669 | 19±68 | 0.84 | 0.98 |
Harris-Benedict | 1663 | −143±68 | 0.12 | 0.72 |
ESPEN/ASPEN (20 kcal/kg/d) | 1577 | −73±279 | 0.41 | 0.65 |
ESPEN/ASPEN (25 kcal/kg/d) | 1971 | 321±288 | 0.002 | 0.65 |
Mifflin-St. Jeor | 1528 | −121±204 | 0.23 | 0.83 |
Penn State 1 | 1754 | 104±265 | 0.31 | 0.70 |
Penn State 2 | 1593 | −57±284 | 0.51 | 0.63 |
Penn State 3 | 1679 | 30±236 | 0.81 | 0.78 |
The present prospective study in mechanically ventilated patients confirms the concept that EE can be accurately estimated by ventilator-derived VCO2. Moreover, it shows that this method is more accurate than most predictive equations, especially those using only static parameters. However, the Penn State 3 equation is a good choice if predictive equations are to be used because it includes variables (minute ventilation and body temperature).
The results of our study are consistent with those of Stepel et al., who, in a sufficient sample size (84 patients on mechanical ventilation, a heterogeneous group), compared МEE from a 24-h IC, EP–VCO2-ventilator as well as EE–VCO2 from a metabolic monitor. They found that the EE–VCO2-ventilator was acceptably accurate and more precise than predictive equations.[
One of the latest studies, Linder et al.[
Rousing et al.[
Briassoulis et al.[
A disadvantage of our study is the small number of patients, 6 patients who had a total of 30 measurements on different days, which can be a potential source of bias in the obtained results. Moreover, factors such as gender and age are not taken into consideration.
In critically ill patients on invasive mechanical ventilation, assessment of EЕ by analysis of CO2 production by the ventilator is a reliable alternative. EE–VCO2-ventilator is more accurate than most predictive equations. Unlike indirect calorimetry, the method is easy to apply, convenient for long-term monitoring, does not take additional time and resources, and is not associated with additional disconnection of the patient from the respiratory circuit. The results of our study coincide with those of Stapel et al. Further research is needed to determine the applicability of the method in routine practice. If, however, it is necessary to use predictive equations in mechanically ventilated patients, the Penn State 3 equation is a good choice.