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Energy expenditure in 100 ventilated, critically ill children: improving the accuracy of predictive equations
M S White1, R W Shepherd, J A McEniery
1Children's Nutrition Research Center, Department of Pediatrics and Child Health, University of Queensland, Brisbane, Australia.
Insights
New equations accurately predict energy needs for critically ill children. These improved methods offer a better alternative to current energy requirement predictions for pediatric intensive care units.
Area of Science:
- Pediatric critical care medicine
- Clinical nutrition
- Metabolic research
Background:
- Accurate energy expenditure prediction is crucial for critically ill children.
- Existing predictive equations often lack precision and accuracy in this population.
Purpose of the Study:
- To evaluate current energy requirement prediction methods.
- To develop and validate novel equations for energy expenditure in ventilated, critically ill children.
Main Methods:
- Prospective, observational study in a pediatric intensive care unit.
- Indirect calorimetry used to measure energy expenditure in 100 ventilated children.
- Multiple regression analysis to identify key predictive variables.
Main Results:
- Standard equations showed poor accuracy in predicting energy expenditure.
- New equations developed using variables like age, weight, temperature, and days post-admission demonstrated high correlation (r² = .898 and .867).
- Validation showed no significant difference between measured and predicted energy expenditure, except for infants under 2 months.
Conclusions:
- Novel equations provide a more accurate method for assessing energy requirements in ventilated, critically ill children.
- These new equations serve as a valuable alternative to existing predictive tools.
Objective:
The purpose of this study was to evaluate current methods of predicting energy requirements and to develop and validate new equations derived from energy expenditure measurements of ventilated, critically ill children.
Design:
Prospective, observational, sequential study.
Setting:
Pediatric intensive care unit.
Patients:
A total of 100 ventilated, critically ill children who fit the criteria of energy expenditure measurement. Additional patients (n = 25) were included in the validation study.
Intervention:
An indirect calorimeter was used to measure energy expenditure for a period of 30 mins.
Measurements And Main Results:
The mean measured energy expenditure was 185+/-51 kJ/kg per day. Predicted energy expenditure from standard equations was compared with measured energy expenditure by using the Bland and Altman "methods comparison procedure," and poor precision and accuracy were observed. Patient variables were collected at the time of measurement, and multiple regression analysis was performed to determine the independent contribution of each variable to measure energy expenditure. New predictive equations were formulated and validated with additional energy expenditure measurements. Patient variables that did not correlate significantly with energy expenditure were gender, Pediatric Risk of Mortality score, and commencement of nutritional support. An equation was derived from patient variables (age, weight, weight for age Z score, body temperature, number of days after intensive care admission, and primary reason for admission) that correlated significantly (r2 = .898) with measured energy expenditure. A second, simplified equation (energy expenditure kJ/day = ¿17 x age [months]¿ + ¿48 x weight [kg]¿ + ¿292 x body temperature degrees C¿ - 9,677) was produced (r2 = .867). Validation found no significant difference between measured and predicted energy expenditure by the new equations; however, the equations did not predict accurately for patients <2 months of age.
Conclusion:
The new equations provide a more accurate alternative to current predictive methods in assessing energy requirements of ventilated, critically ill children.
