Can Vco2-Based Estimates of Resting Energy Expenditure Replace the Need for Indirect Calorimetry in Critically Ill Children?

Nutrition for critically ill children with congenital heart disease

Children with congenital heart disease often require admission to the cardiac intensive care unit at some point in their lives, either after elective surgical or catheter-based procedures or during times of acute critical illness. Meeting both the macronutrient and micronutrient needs of children in the cardiac intensive care unit requires complex decision-making when considering gastrointestinal perfusion, vasoactive support, and fluid balance goals. Although nutrition guidelines exist for critically ill children, these cannot always be extrapolated to children with congenital heart disease. Children with congenital heart disease may also suffer unique circumstances, such as chylothoraces, heart failure, and the need for mechanical circulatory support, which greatly impact nutrition delivery. Guidelines for neonates and children with heart disease continue to be developed. We provide a synthesized narrative review of current literature and considerations for nutrition evaluation and management of critically ill children with congenital heart disease.

Determining energy and protein needs in critically ill pediatric patients: A scoping review

INTRODUCTION

In critically ill pediatric patients, optimal energy and protein intakes are associated with a decreased risk of morbidity and mortality. However, the determination of energy and protein needs is complex. The objective of this scoping review was to understand the extent and type of evidence related to the methods used to determine energy and protein needs in critically ill pediatric patients.

METHODS

An international expert group composed of dietitians, pediatric intensivists, a nurse, and a methodologist conducted the review, based on the Johanna Briggs Institute methodology. Two researchers searched for studies published between 2008 and 2023 in two electronic databases, screened abstracts and relevant full texts for eligibility, and extracted data.

RESULTS

A total of 39 studies were included, mostly conducted in critically ill children undergoing ventilation, to assess the accuracy of predictive equations for estimating resting energy expenditure (REE) (n = 16, 41%) and the impact of clinical factors (n = 22, 56%). They confirmed the risk of underestimation or overestimation of REE when using predictive equations, of which the Schofield equation was the least inaccurate. Apart from weight and age, which were positively correlated with REE, the impact of other factors was not always consistent. No new indirect calorimeter method used to determine protein needs has been validated.

CONCLUSION

This scoping review highlights the need for scientific data on the methods used to measure energy expenditure and determine protein needs in critically ill children. Studies using a reference method are needed to validate an indirect calorimeter.

External Validation with Accuracy Confounders of VCO2-Derived Predicted Energy Expenditure Compared to Resting Energy Expenditure Measured by Indirect Calorimetry in Mechanically Ventilated Children

Optimal energy provision, guided by measured resting energy expenditure (REE) and determined by indirect calorimetry (IC), is fundamental in Intensive Care Units (ICU). Because IC availability is limited, methods to predict REE based on carbon dioxide production (VCO2) measurements (REEVCO2) alone have been proposed as a surrogate for REE measured by IC (REEIC). The study aimed at externally and internally validating the accuracy of the REEVCO2 as an alternative to REEIC in mechanically ventilated children. A ventilator’s integrated gas exchange module (E-COVX) was used to prospectively measure REEIC and predict REEVCO2 on 107 mechanically ventilated children during the first 24 h of admission. The accuracy of the REEVCO2 compared to REEIC was assessed through the calculation of bias and precision, paired median differences, linear regression, and ROC analysis. Accuracy within ±10% of the REEIC was deemed acceptable for the REEVCO2 equation. The calculated REEVCO2 based on respiratory quotient (RQ) 0.89 resulted in a mean bias of −72.7 kcal/day (95% limits of agreement −321.7 to 176.3 kcal/day) and a high coefficient of variation (174.7%), while 51.4% of the calculations fell outside the ±10% accuracy rate. REEVCO2 derived from RQ 0.80 or 0.85 did not improve accuracy. Only measured RQ (Beta 0.73, p < 0.001) and no-recorded neuromuscular blocking agents (Beta −0.13, p = 0.044) were independently associated with the REEVCO2−REEIC difference. Among the recorded anthropometric, metabolic, nutrition, or clinical variables, only measured RQ was a strong predictor of REEVCO2 inaccuracy (p < 0.001). Cutoffs of RQ = 0.80 predicted 89% of underestimated REEIC (sensitivity 0.99; specificity 0.89) and RQ = 0.82 predicted 56% of overestimated REEIC (sensitivity of 0.99; specificity 0.56). REEVCO2 cannot be recommended as an alternative to REEIC in mechanically ventilated children, regardless of the metabolic, anthropometric, or clinical status at the time of the evaluation.

A methodological and clinical approach to measured energy expenditure in the critically ill pediatric patient

The metabolic response to injury and stress is characterized initially by a decreased energy expenditure (Ebb phase) followed by an increased metabolic expenditure (Flow phase). Indirect calorimetry is a methodology utilized to measure energy expenditure and substrate utilization by measuring gas exchange in exhaled air and urinary nitrogen. The use of indirect calorimetry in critically ill patients requires precise equipment to obtain accurate measurements. The most recent guidelines suggested that measured energy expenditure by indirect calorimetry be used to determine energy requirements. This article reviews the methodological and clinical use of indirect calorimetry in critically ill pediatric patients.

Standardisation of management after Norwood operation has not improved 1-year outcomes

INTRODUCTION

Treatment of hypoplastic left heart syndrome varies across institutions. This study examined the impact of introducing a standardised programme.

METHODS

This retrospective cohort study evaluated the effects of a comprehensive strategy on 1-year transplant-free survival with preserved ventricular and atrioventricular valve (AVV) function following a Norwood operation. This strategy included standardised operative and perioperative management and dedicated interstage monitoring. The post-implementation cohort (C2) was compared to historic controls (C1). Outcomes were assessed using logistic regression and Kaplan-Meier analysis.

RESULTS

The study included 105 patients, 76 in C1 and 29 in C2. Groups had similar baseline characteristics, including percentage with preserved ventricular (96% C1 versus 100% C2, p = 0.28) and AVV function (97% C1 versus 93% C2, p = 0.31). Perioperatively, C2 had higher indexed oxygen delivery (348 ± 67 ml/minute/m2 C1 versus 402 ± 102ml/minute/m2 C2, p = 0.015) and lower renal injury (47% C1 versus 3% C2, p = 0.004). The primary outcome was similar in both groups (49% C1 and 52% C2, p = 0.78), with comparable rates of death and transplantation (36% C1 versus 38% C2, p = 0.89) and ventricular (2% C1 versus 0% C2, p = 0.53) and AVV dysfunction (11% C1 versus 11% C2, p = 0.96) at 1-year. When accounting for cohort and 100-day freedom from hospitalisation, female gender (OR 3.7, p = 0.01) increased and ventricular dysfunction (OR 0.21, p = 0.02) and CPR (OR 0.11, p = 0.002) or ECMO use (OR 0.15, p = 001) decreased the likelihood of 1-year transplant-free survival.

CONCLUSIONS

Standardised perioperative management was not associated with improved 1-year transplant-free survival. Post-operative ventricular or AVV dysfunction was the strongest predictor of 1-year mortality.

Feeding should be individualized in the critically ill patients

PURPOSE OF REVIEW

Any critical care therapy requires individual adaptation, despite standardization of the concepts supporting them. Among these therapies, nutrition care has been repeatedly shown to influence clinical outcome. Individualized feeding is the next needed step towards optimal global critical care.

RECENT FINDINGS

Both underfeeding and overfeeding generate complications and should be prevented. The long forgotten endogenous energy production, maximal during the first 3 to 4 days, should be integrated in the nutrition plan, through a slow progression of feeding, as full feeding may result in early overfeeding. Accurate and repeated indirect calorimetry is becoming possible thanks to the recent development of a reliable, easy to use and affordable indirect calorimeter. The optimal timing of the prescription of the measured energy expenditure values as goal remains to be determined. Optimal protein prescription remains difficult as no clinically available tool has yet been identified reflecting the body needs.

SUMMARY

Although energy expenditure can now be measured, we miss indicators of early endogenous energy production and of protein needs. A pragmatic ramping up of extrinsic energy provision by nutrition support reduces the risk of overfeeding-related adverse effects.

A Comparative Analysis of Equations to Estimate Patient Energy Requirements Following Cardiopulmonary Bypass for Correction of Congenital Heart Disease

BACKGROUND

No consensus exists on the optimal method to estimate resting energy expenditure (REE) in critically ill children following cardiopulmonary bypass (CPB). This study assesses the accuracy of REE estimation equations in children with congenital heart disease following CPB and tests the feasibility of using allometric scaling as an alternative energy prediction equation.

METHODS

A retrospective analysis of a pediatric cohort following CPB (n = 107; median age 5.2 months, median weight 5.65 kg) who underwent serial measures (median 5 measurements) of REE using indirect calorimetry for 72 hours following CPB. We estimated REE using common estimation methods (Dietary Reference Intake, Harris Benedict, Schofield, World Health Organization [WHO]) as well as novel allometric equations. We compared estimated with measured REE to determine accuracy of each equation using overall discrepancy, calculated as a time-weighted average of the absolute deviation.

RESULTS

All equations incorrectly estimated REE at all time points following CPB, with overestimation error predominating. WHO had the lowest discrepancy at 10.7 ± 8.4 kcal/kg/d. The allometric equation was inferior, with an overall discrepancy of 16.9 ± 10.4. There is a strong nonlinear relationship between body surface area and measured REE in this cohort, which is a key source of estimation error using linear equations.

CONCLUSION

In a cohort of pediatric patients with congenital heart disease following CPB, no currently utilized clinical estimation equation reliably estimated REE. Allometric scaling proved inferior in estimating REE in children following CPB. Indirect calorimetry remains the ideal method of determining REE after CPB until nonlinear methods can be derived due to overestimation using linear equations.

Estimation of Resting Energy Expenditure Using Predictive Equations in Critically Ill Children: Results of a Systematic Review

Provision of adequate energy intake to critically ill children is associated with improved prognosis, but resting energy expenditure (REE) is rarely determined by indirect calorimetry (IC) due to practical constraints. Some studies have tested the validity of various predictive equations that are routinely used for this purpose, but no systematic evaluation has been made. Therefore, we performed a systematic review of the literature to assess predictive equations of REE in critically ill children. We systematically searched the literature for eligible studies, and then we extracted data and assigned a quality grade to each article according to guidelines of the Academy of Nutrition and Dietetics. Accuracy was defined as the percentage of predicted REE values to fall within ±10% or ±15% of the measured energy expenditure (MEE) values, computed based on individual participant data. Of the 993 identified studies, 22 studies testing 21 equations using 2326 IC measurements in 1102 children were included in this review. Only 6 equations were evaluated by at least 3 studies in critically ill children. No equation predicted REE within ±10% of MEE in >50% of observations. The Harris-Benedict equation overestimated REE in two-thirds of patients, whereas the Schofield equations and Talbot tables predicted REE within ±15% of MEE in approximately 50% of observations. In summary, the Schofield equations and Talbot tables were the least inaccurate of the predictive equations. We conclude that a new validated indirect calorimeter is urgently needed in the critically ill pediatric population.).