Energy expenditure and indirect calorimetry in critical illness and convalescence: current evidence and practical considerations

Optimizing Protein in the Diets of Critically Ill Children: Time for Re-Evaluation

Indirect calorimetry: The 6 main issues.

careful selection of the appropriate mode of feeding and monitoring the success of the feeding strategy. The use of specific nutrients, which possess a drug-like effect on the immune or inflammatory state during critical illness, continues to be an exciting area of investigation. The lack of systematic research and clinical trials on various aspects of nutrition support in the PICU is striking and makes it challenging to compile evidence based practice guidelines. There is an urgent need to conduct well-designed, multicenter trials in this area of clinical practice. The extrapolation of data from adult critical care literature is not desirable and many of the interventions proposed in adults will have to undergo systematic examination and careful study in critically ill children prior to their application in this population. In the following sections, we will discuss some of the key aspects of nutrition support therapy in the PICU; examine the literature and provide best practice guidelines based on evidence from PICU patients, where available. While some PICU popu lations include neonates, A.S.P.E.N. Clinical Guidelines for neonates will be published as a separate series.

In this issue of Nutrition in Clinical Practice, Malone provides an overview of assessing energy expenditure in the ICU. Malone’s article complements two previous reviews in this journal regarding indirect calorimetry. The topics discussed include basic concepts in indirect calorimetry, appropriate measurement conditions, application of resting energy expenditure toward estimation of total energy expenditure, pitfalls and potential applications of the Fick equation, use of various predictive formulas, and indications for indirect calorimetry. It would be impractical to write an exhaustive review on indirect calorimetry as there are entire books dedicated to this subject. However, these three reviews from the journal would provide the reader with a solid foundation in the understanding of the use of indirect calorimetry in clinical practice. I felt compelled to use this editorial to embellish on or provide an alternative viewpoint regarding some of the issues discussed in Malone’s review. Sometimes in our eagerness to implement indirect calorimetry into our practice, we inadvertently omit several essential elements of the procedure that must be done before measuring patients. These elements are not often described in reviews. One of the most important of these elements is the validation of measurement conditions and techniques using healthy subjects. This is particularly pertinent if you plan to compare your resting energy expenditure measurements with normal or predicted values. For example, if you plan to use the Harris-Benedict equations as your normal or predicted values, then the vast majority of healthy subjects should fall within 10% or 15% of these values. Before measuring patients at the hospital, we measured 10 healthy subjects who were within 10% of ideal body weight. Nine subjects were within 10% of predicted values by the Harris-Benedict equations and the tenth was within 13% of predicted values. As a result, we felt more comfortable using the Harris-Benedict equation as our reference, or normal or predicted, energy expenditure when measuring patients at the hospital. Another area for further elaboration is the use of indirect calorimetry in patients who are ventilator dependent. Malone appropriately identifies some pitfalls in this area. In addition to the parameters identified in the review, the stability of the FiO2 should be monitored before the indirect calorimetry measurement. Certain ventilators tend to have more fluctuation in oxygen concentration delivery than others, resulting in additional errors in oxygen consumption measurements. We use oxygen consumption error sensitivity to provide a more reliable indicator of measurement error than respiratory quotient (RQ). This marker takes into account inspired oxygen concentration, concentration variability, and metabolic demand. Examining the data for a nonphysiologic RQ can only detect gross errors. A small fluctuation in inspired oxygen content (eg, 60.0% versus 60.5%) can result in approximately a 24% error in oxygen consumption sensitivity in an average-sized, unstressed individual. The error would be further magnified in a stressed, critically ill patient. It is also important to use a metabolic cart with a sensitive oxygen sensor for hospitalized ventilator-dependent patients. Our system uses a differential paramagnetic oxygen sensor that is sensitive to 0.01% (eg, it can detect differences from 50.01% to 50.02% in inspired oxygen content). This is in contrast to some other systems that may only be able to detect to the 0.1% level and may be more likely to be associated with greater error in patients receiving higher FiO2 concentrations. Use of predictive methods is always a concern given the variability of energy expenditure for a given disease. Nevertheless, I agree with Malone’s philosophy in giving guidance to those clinicians without the capability to measure energy expenditure. It was clearly pointed out that the “older estimates” grossly overestimate measured energy expenditure. The study by Foster et al in 100 consecutive patients requiring parenteral nutrition clearly illustrates that point. Of 191 published guidelines, approximately 50% of patient case-formula matches overestimated energy expenditure by up to 1000 kcal/d, and more than 45% of the matches Correspondence: Roland N. Dickerson, PharmD, University of Tennessee Health Science Center, 26 S. Dunlap St., Memphis, TN 38163.

Perioperative nutrition

The nutritional needs of critically ill septic patients or patients with multiple injuries are often difficult to estimate. Indirect calorimetry can simply and accurately determine individual caloric and nutritional needs, especially in cases of critically ill patients with complicated injuries. This prospective study compared the measured energy expenditures of 30 patients using indirect calorimetry with their predicted basal energy expenditure according to the Harris-Benedict equation, or their calculated energy expenditure derived from basal energy expenditure times, an activity factor, and a stress factor. These numbers were then used to evaluate the relationship between measured energy expenditure, measured energy expenditure per kilogram, and four specific scoring systems--the Septic Severity Score (SSS), the Injury Severity Score (ISS), the Trauma Score (TS), and APACHE II. The results showed the severity of sepsis or trauma correlated with the measured energy expenditure per kilogram of body weight. Among the 15 septic patients, in whom the measured energy expenditure per kilogram was 42.2 +/- 2.6 kcal/kg, the SSS provided a better predictor of energy needs and closer correlation with measured energy expenditure per kilogram (r = 0.69, Y = 1.41 + 0.72 X). Their stress factors could be modified as "0.97 + 0.0125 x SSS" to get a more accurate Harris-Benedict calculation. For the 15 patients with multiple injuries in whom the measured energy expenditure per kilogram was 34.9 +/- 1.6 kcal/kg, the ISS offered the best correlation with measured energy expenditure per kilogram (r = 0.84, Y = -31.47 +/- 1.73 X). Their stress factors could be modified as "1.04 + 0.0077 x ISS" to get a more accurate Harris-Benedict calculation.

Availability and use of indirect calorimetry in adult Australian and New Zealand intensive care units: A report using data from an observational study of nutrition practices.

Optimal nutritional therapy has been associated with better clinical outcomes and requires providing energy as closed as possible to measured energy expenditure. We reviewed the current innovations in energy expenditure assessment in humans, focusing on indirect calorimetry and other new alternative methods. Although considered the reference method to measure energy expenditure, the use of indirect calorimetry is currently limited by the lack of an adequate device. However, recent technical developments may allow a broader use of indirect calorimetry for in-patients and out-patients. An ongoing international academic initiative to develop a new indirect calorimeter aimed to provide innovative and affordable technical solutions for many of the current limitations of indirect calorimetry. New alternative methods to indirect calorimetry, including CO2 measurements in mechanically ventilated patients, isotopic approaches and accelerometry-based fitness equipments, show promises but have been either poorly studied and/or are not accurate compared to indirect calorimetry. Therefore, to date, energy expenditure measured by indirect calorimetry remains the gold standard to guide nutritional therapy. Some new innovative methods are demonstrating promises in energy expenditure assessment, but still need to be validated. There is an ongoing need for easy-to-use, accurate and affordable indirect calorimeter for daily use in in-patients and out-patients.

Review recent literature on the role of indirect calorimetry in critical care nutrition management. Critical illness demands objective, targeted nutritional therapy to prevent adverse effects of underfeeding/over feeding. Thus, all recent societal guidelines recommend indirect calorimetry use to determine energy needs. Very recently, indirect calorimetry technology has finally evolved to allow for accurate, simple, and routine utilization in a wider range of ICU patients. Recent data continues to confirm poor correlation between measured and equation-predicted energy expenditure emphasizing need for indirect calorimetry to be standard of care. This may be particularly true in COVID-19, where significant progressive hypermetabolism and variability in energy expenditure has been shown. Metabolic physiology can change frequently during ICU stay in response to changes in clinical condition or care. Thus, repeated longitudinal indirect calorimetry measures are needed throughout ICU stay to optimize care, with initial data showing improved clinical outcomes when indirect calorimetry targets are utilized. Personalized ICU care demands objective data to guide therapy. This includes use of indirect calorimetry to determine energy expenditure and guide ICU nutrition therapy. Long-awaited new innovations in indirect calorimetry technology should finally lead to indirect calorimetry to becoming a fundamental component of modern ICU standard of care and clinical research moving forward.

Adequate “nutritional support is an essential element for achieving favorable outcomes in critically ill patients, which requires an accurate evaluation of energy needs to avoid under or overfeeding.” Energy requirements of critically ill patients can be assessed either by Predictive equations (PEs) or by “indirect calorimetry(IC) measurements.” However, assessment of energy expenditure (EE) is a challenging task in intensive care unit patients” because EE during critical illness is widely variable and the current PEs are inaccurate to determine the caloric requirement in these patients.” Currently, IC is considered a gold standard for measuring EE as recommended by guidelines.” Despite being the most accurate method of measuring EE, adequate data are lacking to validate the beneficial effects of IC-guided nutrition therapy on clinical outcomes in critically ill patients. Because of this, the actual clinical benefits of IC are poorly appreciated, and it is still an underutilized tool among dietitians in clinical practice.” Therefore, in many centers, PEs are commonly used instead. The purpose of this review is to summarize the findings of recent studies regarding IC-guided nutrition therapy and its impact on clinical outcomes in critically ill patients.

Recent changes in guidelines recommendation during early phase of critical illness and use of indirect calorimetry. The aim of this review is to discuss methods of determining energy requirements in the critically ill and highlight factors impacting resting energy expenditure. An appraisal of recent literature discussing indirect calorimetry guided-nutrition potential benefits or pitfalls. Recent attempts to devise strategy and pilot indirect calorimetry use in the critically ill patients requiring continuous renal replacement therapy or extracorporeal membrane oxygenation are also discussed. Additionally, we briefly touched on variability between guidelines recommended energy target and measured energy expenditure for adult critically ill patients with obesity. While energy requirement in the critically ill continues to be an area of controversy, recent guidelines recommendations shift toward providing less aggressive calories during acute phase of illness in the first week of ICU.Use of indirect calorimetry may provide more accurate energy target compared to the use of predictive equations. Despite the absence of literature to support long term mortality benefits, there are many potential benefits for the use of indirect calorimetry when available.

Chapter 16. Glucose and nutrition

Indirect calorimetry in nutritional therapy. A position paper by the ICALIC study group

A HIGH DEGREE of variability in energy expenditure has characterized the metabolic response to traumatic brain injury. A goal of parenteral or enteral repletion in this population is the precise estimation of caloric requirement to avoid complications associated with overfeeding and underfeeding. The first aim of this study was to evaluate three predictive formulas for comparison to measured energy expenditure (MEE) derived from indirect calorimetry in patients with traumatic brain injury. A total of 385 measurements were obtained in 102 patients and were compared concurrently with these predictive formulas. The best predictive method in this phase (bivariate regression) yielded r = 0.39 and P < 0.001 (231 repeated measures). This best prediction, when compared with MEE, however, was able to capture values within 75 to 125% of MEE in only 56% of measurements. The two remaining formulas yielded r = 0.38 (P < 0.001) and r = 0.23 (P < 0.001) in 386 and 267 repeated measures, respectively. The second aim of this study was to evaluate the ability of additional nutritional markers to improve predictive ability. Regression analyses were performed on nutritional markers including indices of severity of injury, concurrent drug therapy, vital signs, neurological status, gluconeogenesis, protein synthesis/excretion, and immune response. The statistical results of the analysis on these multiple nutritional markers showed only heart rate, temperature, and number of days elapsed after injury to be significant predictors of MEE by indirect calorimetry in multiple regression analyses (R = 0.32; P < 0.001). These data suggest clinically significant discrepancies between MEE and these predictive formulas. Further regression analyses with additional variables did not result in substantially improved prediction. The ability to decipher the meaning of specific metabolic indicators and to make reasonable clinical decisions as to specific caloric supplementation may be tenuous when estimating energy expenditure with predictive formulas. The routine use of indirect calorimetry to guide caloric supplementation in patients with traumatic brain injury is warranted.

Objective To investigate the energy expenditure of mechanically ventilated patients,compare the measured energy expenditure (MREE) with the energy expenditure expected from the Harris-Benedict equation adjusted with correction factors (PREE). Methods Twenty-four critically ill adult patients who were mechanically ventilated in the intensive care unit were enrolled in this study. Data during the 72 hours of mechanical ventilation were collected for computation of severity of illness. Resting energy expenditures were derived at 72hours after mechanical ventilation by indirect calorimetry. Predicted basal energy expenditure was obtained at the same time using the Harris-Benedict equation and predicted resting energy expenditure was calculated using the Harris-Benedict value adjusted with correction factors for illness. Results The Acute Physiology and Chronic Health Evaluation Ⅱ (APACHE Ⅱ)scores and Marshall scores were 14 ± 5 and 6 ± 3, respectively. MREE and PREE were (6 793.64 ± 1 197.15) and (8 041.02 ± 1 971.54) kJ/day, respectively. There was no correlation between MREE and PREE (r2 = 0. 28, P = 0. 07), and the difference between MREE and PREE was statistically significant (t = 7.62, P = 0.04). No statistically significant correlations were observed between both MREE or PREE and APACHE Ⅱ score or Marshall score (r2 = 0. 14, P = 0. 08; r2= 0. 08, P = 0. 63; r2 = 0. 05, P =0. 65; r2 = 0.03, P = 0. 87, respectively). Conclusions In mechanically ventilated patients, the energy expenditure is not correlated with the severity of illness. The Harris-Benedict prediction modified with correction factors for severity of illness systematically overestimates the total energy expenditure. Key words: Energy expenditure; Calorimetry,indirect; Mechanical ventilation; Critical illness