Energy expenditure and severity of injury and illness indices in multiple trauma patients

Accuracy of predictive equations for resting energy expenditure estimation in mechanically ventilated Thai patients

Background

Indirect calorimetry (IC) is the most precise approach for estimating calorie demand in critically ill patients. Despite this, owing to unaffordable devices, it is rarely used in practice. Predictive equations are the alternatives.

Objectives

To assess the accuracy of 14 predictive resting energy expenditure(REE) equations in ventilated Thai patients.

Methods

We compared the accuracy and agreement of 14 equations. The equations included the American College of Chest Physicians(ACCP) equation, Harris-Benedict equation(HBE), 1.2×HBE, 1.5×HBE, Mifflin-St. Jeor(MSJ), Ireton-Jones 1992 and 2002, Penn State 2003(HBE and MSJ) and 2010, Swinamer 1990, Faisy, Brandi 1999, and 25 kcal/kg equation. An equation was ascertained as accurate if the calculated values fell within ±10% of the measured REEs. Spearman correlation coefficient, Bland-Altman method, and intraclass correlation coefficient were used to analysis.

Results

We obtained data from 24 ventilated patients undergoing REE measurement by IC. Fifty percent of them were male with a median age of 64.5 years, a median height of 160 cm, and a median body mass index of 22.95 kg/m2. The predictive precision of all equations was poor, with largely different accuracies from 6.7% to 48.1%. The most reliable equation was Penn State 2010. The ACCP, HBE, MSJ, and Penn State 2003(HBE) tended to underestimate calorie need. Contrastingly, the other equations tended to overestimate REEs. Despite a moderate degree of correlations, the Bland-Altman plots demonstrated clinically unacceptable discrepancies between measured REE and REE calculated by each equation.

Conclusions

In ventilated Thai patients, there were no precise equations for determining REE.

Medical nutrition therapy and clinical outcomes in critically ill adults: a European multinational, prospective observational cohort study (EuroPN)

BACKGROUND

Medical nutrition therapy may be associated with clinical outcomes in critically ill patients with prolonged intensive care unit (ICU) stay. We wanted to assess nutrition practices in European intensive care units (ICU) and their importance for clinical outcomes.

METHODS

Prospective multinational cohort study in patients staying in ICU ≥ 5 days with outcome recorded until day 90. Macronutrient intake from enteral and parenteral nutrition and non-nutritional sources during the first 15 days after ICU admission was compared with targets recommended by ESPEN guidelines. We modeled associations between three categories of daily calorie and protein intake (low: < 10 kcal/kg, < 0.8 g/kg; moderate: 10-20 kcal/kg, 0.8-1.2 g/kg, high: > 20 kcal/kg; > 1.2 g/kg) and the time-varying hazard rates of 90-day mortality or successful weaning from invasive mechanical ventilation (IMV).

RESULTS

A total of 1172 patients with median [Q1;Q3] APACHE II score of 18.5 [13.0;26.0] were included, and 24% died within 90 days. Median length of ICU stay was 10.0 [7.0;16.0] days, and 74% of patients could be weaned from invasive mechanical ventilation. Patients reached on average 83% [59;107] and 65% [41;91] of ESPEN calorie and protein recommended targets, respectively. Whereas specific reasons for ICU admission (especially respiratory diseases requiring IMV) were associated with higher intakes (estimate 2.43 [95% CI: 1.60;3.25] for calorie intake, 0.14 [0.09;0.20] for protein intake), a lack of nutrition on the preceding day was associated with lower calorie and protein intakes (- 2.74 [- 3.28; - 2.21] and - 0.12 [- 0.15; - 0.09], respectively). Compared to a lower intake, a daily moderate intake was associated with higher probability of successful weaning (for calories: maximum HR 4.59 [95% CI: 1.5;14.09] on day 12; for protein: maximum HR 2.60 [1.09;6.23] on day 12), and with a lower hazard of death (for calories only: minimum HR 0.15, [0.05;0.39] on day 19). There was no evidence that a high calorie or protein intake was associated with further outcome improvements.

CONCLUSIONS

Calorie intake was mainly provided according to the targets recommended by the active ESPEN guideline, but protein intake was lower. In patients staying in ICU ≥ 5 days, early moderate daily calorie and protein intakes were associated with improved clinical outcomes. Trial registration NCT04143503 , registered on October 25, 2019.

Do we need different predictive equations for the acute and late phases of critical illness? A prospective observational study with repeated indirect calorimetry measurements

BACKGROUND

Predictive equations (PEs) for estimating resting energy expenditure (REE) that have been developed from acute phase data may not be applicable in the late phase and vice versa. This study aimed to assess whether separate PEs are needed for acute and late phases of critical illness and to develop and validate PE(s) based on the results of this assessment.

METHODS

Using indirect calorimetry, REE was measured at acute (≤5 days; n = 294) and late (≥6 days; n = 180) phases of intensive care unit admission. PEs were developed by multiple linear regression. A multi-fold cross-validation approach was used to validate the PEs. The best PEs were selected based on the highest coefficient of determination (R²), the lowest root mean square error (RMSE) and the lowest standard error of estimate (SEE). Two PEs developed from paired 168-patient data were compared with measured REE using mean absolute percentage difference.

RESULTS

Mean absolute percentage difference between predicted and measured REE was <20%, which is not clinically significant. Thus, a single PE was developed and validated from data of the larger sample size measured in the acute phase. The best PE for REE (kcal/day) was 891.6(Height) + 9.0(Weight) + 39.7(Minute Ventilation)-5.6(Age) - 354, with R² = 0.442, RMSE = 348.3, SEE = 325.6 and mean absolute percentage difference with measured REE was: 15.1 ± 14.2% [acute], 15.0 ± 13.1% [late].

CONCLUSIONS

Separate PEs for acute and late phases may not be necessary. Thus, we have developed and validated a PE from acute phase data and demonstrated that it can provide optimal estimates of REE for patients in both acute and late phases.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03319329.

A Single-Center Prospective Observational Study Comparing Resting Energy Expenditure in Different Phases of Critical Illness: Indirect Calorimetry Versus Predictive Equations

OBJECTIVES

Several predictive equations have been developed for estimation of resting energy expenditure, but no study has been done to compare predictive equations against indirect calorimetry among critically ill patients at different phases of critical illness. This study aimed to determine the degree of agreement and accuracy of predictive equations among ICU patients during acute phase (≤ 5 d), late phase (6-10 d), and chronic phase (≥ 11 d).

DESIGN

This was a single-center prospective observational study that compared resting energy expenditure estimated by 15 commonly used predictive equations against resting energy expenditure measured by indirect calorimetry at different phases. Degree of agreement between resting energy expenditure calculated by predictive equations and resting energy expenditure measured by indirect calorimetry was analyzed using intraclass correlation coefficient and Bland-Altman analyses. Resting energy expenditure values calculated from predictive equations differing by ± 10% from resting energy expenditure measured by indirect calorimetry was used to assess accuracy. A score ranking method was developed to determine the best predictive equations.

SETTING

General Intensive Care Unit, University of Malaya Medical Centre.

PATIENTS

Mechanically ventilated critically ill patients.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Indirect calorimetry was measured thrice during acute, late, and chronic phases among 305, 180, and 91 ICU patients, respectively. There were significant differences (F= 3.447; p = 0.034) in mean resting energy expenditure measured by indirect calorimetry among the three phases. Pairwise comparison showed mean resting energy expenditure measured by indirect calorimetry in late phase (1,878 ± 517 kcal) was significantly higher than during acute phase (1,765 ± 456 kcal) (p = 0.037). The predictive equations with the best agreement and accuracy for acute phase was Swinamer (1990), for late phase was Brandi (1999) and Swinamer (1990), and for chronic phase was Swinamer (1990). None of the resting energy expenditure calculated from predictive equations showed very good agreement or accuracy.

CONCLUSIONS

Predictive equations tend to either over- or underestimate resting energy expenditure at different phases. Predictive equations with "dynamic" variables and respiratory data had better agreement with resting energy expenditure measured by indirect calorimetry compared with predictive equations developed for healthy adults or predictive equations based on "static" variables. Although none of the resting energy expenditure calculated from predictive equations had very good agreement, Swinamer (1990) appears to provide relatively good agreement across three phases and could be used to predict resting energy expenditure when indirect calorimetry is not available.

Malnutrition Essentials for Neurologists and Neurosurgeons: A Review of the Literature

Malnutrition still causes deaths in the world today and protein energy malnutrition (PEM) is characterized by increased oxidative stress, immune deficiency, and development of various infections. Even today, however, it is an underrecognized and undertreated entity in neurology and neurosurgery. In this article, we therefore seek to review the available literature regarding various factors affecting surgical outcome of children with malnutrition undergoing some neurosurgical interventions including shunt surgery and traumatic brain injury in intensive care unit, in addition to its effects upon oxidative stress status and immunity. Furthermore, we attempt to provide essential knowledge of malnutrition affecting surgical outcome of patients with PEM. Based on available evidence in the published literature, it is concluded that it is a serious public health problem characterized by increased oxidative stress, immune deficiency, and development of various infections.

Use of Predictive Equations for Energy Prescription Results in Inaccurate Estimation in Trauma Patients

BACKGROUND

Overfeeding and underfeeding are associated with poor clinical outcomes. In the absence of indirect calorimetry (IC), the Society of Critical Care Medicine/ASPEN recommend prescribing 25-30 kcal/kg. The Harris-Benedict equation (HBE) multiplied by a stress factor is commonly applied in critically ill patients. We describe the difference between estimated and actual energy needs in critically injured patients.

METHODS

From March to November 2018, we collected demographics and energy needs determined by continuous IC (started within 4 days) in intubated adults. Ideal or adjusted body weight was used for 25-30 kcal/kg, and HBE was multiplied by a 1.3 stress factor (1.3HBE). Daily requirements up to 14 days, extubation, or death were calculated using all 3 methods and compared with IC.

RESULTS

Fifty-five subjects were included. Median age was 38 [27-58] years, 38 (69%) were male, body mass index was 28 [25-33] kg/m² , and Acute Physiology and Chronic Health Evaluation II score was 17 [14-24] Mechanism of injury was blunt (38, 69%), penetrating (9, 16%), and burn (8, 15%). By day 14, compared with measured energy requirements by IC, the other methods could result in a cumulative 1827-kcal (+7%) surplus (1.3HBE), a 1313-kcal (-5%) deficit (25 kcal/kg), or a 3950-kcal (+14%) surplus (30 kcal/kg) per patient over a median 9 days.

CONCLUSION

In critically injured patients, predictive equations for energy needs do not account for dynamic metabolic changes over time and could result in underfeeding or overfeeding. Adjusting daily prescription based on continuous IC may result in better individualized treatment.

Systematic review of factors associated with energy expenditure in the critically ill

BACKGROUND AND AIMS

Indirect calorimetry is the reference standard for energy expenditure measurement. Predictive formulae that replace it are inaccurate. Our aim was to review the patient and clinical factors associated with energy expenditure in critically ill patients.

METHODS

We conducted a systematic review of the literature. Eligible studies were those reporting an evaluation of factors and energy expenditure. Energy expenditure and factor associations with p-values were extracted from each study, and each factor was classified as either significantly, indeterminantly, or not associated with energy expenditure. Regression coefficients were summarized as measures of central tendency and spread. Metanalysis was performed on correlations.

RESULTS

The search strategy yielded 8521 unique articles, 307 underwent full text review, and 103 articles were included. Most studies were in adults. There were 95 factors with 352 evaluations. Minute volume, weight, age, % body surface area burn, sedation, post burn day, and caloric intake were significantly associated with energy expenditure. Heart rate, fraction of inspired oxygen, respiratory rate, respiratory disease diagnosis, positive end expiratory pressure, intensive care unit days, C- reactive protein, and size were not associated with energy expenditure. Multiple factors (n = 37) were identified with an unclear relationship with energy expenditure and require further evaluation.

CONCLUSIONS

An important interval step in the development of accurate formulae for energy expenditure estimation is a better understanding of relationships between patient and clinical factors and energy expenditure. The review highlights the limitations of currently available data, and identifies important factors that are not included in current prediction formulae of the critically ill.

Indirect calorimetry as point of care testing

Determining energy requirement is a fundamental of nutrition support. Indirect calorimetry (IC) has been long recognized as the gold standard for assessing basal or resting energy expenditure (REE). The measurement of REE is recommended particularly in the situation where adjustment of energy provision is critical. The result of the IC measurement can lead to changes in treatment and since the change can be carried out immediately at the bedside, this may be considered as point-of-care testing. Beyond the nutritional aspects, studies of energy expenditure with IC have brought out more understanding of the metabolic changes during the natural course of diseases or conditions as well as those related to the intervention. The literature in various disease states has shown that changes in energy expenditure may reveal hidden metabolic information that might be translated into clinical information and have the potential of being both prognostic indicators and/or treatment targets.

Should we calculate or measure energy expenditure? practical aspects in the ICU

Indirect calorimetry is currently a gold standard of resting energy expenditure (REE) assessment in critically ill patients. Many predictive equations of energy expenditure have been proved to imprecisely predict REE and lead to under- or overfeeding. The benefits of indirect calorimetry-guided nutrition therapy rather than calculation-based strategy have been demonstrated in randomized controlled trials. To minimize energy debt in the intensive care unit, we support early enteral feeding. REE should be measured as soon as the patient's conditions allow and the target of delivered calorie should be around 0.7 to 1 of measured REE to avoid overfeeding. The supplemental parenteral nutrition should be prescribed to close the caloric gap if the goal is not reached by enteral nutrition alone.

Energy Expenditure and Protein Requirements After Traumatic Injury

Traumatic injury induces hypermetabolism. The degree of hypermetabolism can be variable, depending on the type of injury, the degree of inflammation, body composition, age, and treatment regimens. To estimate metabolic rate in some types of injury, predictive equations have been published. Some of these equations have been tested in validation studies. For other types of injury, equations do not exist. Some expert panels have recommended measuring in lieu of estimating metabolic rate, though studies have not been performed to determine whether clinical outcome is affected by the method used to determine energy requirements. Traumatically injured patients are usually catabolic, but protein needs after traumatic injury continue to be debated. Some suggest that 1.5 g protein per kg body weight is adequate and that any additional protein is simply oxidized, adding to the nitrogen load to be excreted. Alternately, protein intake >2.0 g/kg body weight increases the absolute rate of body protein synthesis, and achievement of nitrogen balance has been associated with survival. Thus, provision of high-protein feeding to achieve nitrogen balance might be worthwhile, even if that balance is achieved at the cost of additional nitrogen production.

Nutrition Delivery Affects Outcomes in Pediatric Acute Respiratory Distress Syndrome

BACKGROUND

Malnutrition is prevalent in critically ill children. We aim to describe nutrition received by children with acute respiratory distress syndrome (ARDS) and to determine whether provision of adequate nutrition is associated with improved clinical outcomes.

MATERIALS AND METHODS

We studied characteristics and outcomes of 2 groups of patients: (1) those who received adequate calories (defined as ≥80% of predicted resting energy expenditure) and (2) those who received adequate protein (defined as ≥1.5g/kg/d of protein). Outcomes of interest were mortality, ventilator-free days (VFDs), intensive care unit (ICU)-free days, multiorgan dysfunction, and need for extracorporeal membrane oxygenation. Categorical variables were analyzed using the Fisher exact test, and continuous variables were analyzed using the Mann-Whitney U test. Univariate and multivariate logistic regression models were used to identify associated risk factors related to these outcomes of interest.

RESULTS

In total, 107 patients with ARDS were identified. There was a reduction in ICU mortality in patients who received adequate calories (34.6% vs 60.5%, P = .025) and adequate protein (14.3% vs 60.2%, P = .002) compared with those that did not. Patients with adequate protein intake also had more VFDs (median [interquartile range], 12 [3.0-19.0] vs 0 [0.0-14.8] days; P = .005). After adjusting for severity of illness, adequate protein remained significantly associated with decreased mortality (adjusted odds ratio [95% confidence interval], 0.09 [0.01-0.94]; P = .044).

CONCLUSION

Our study demonstrated that adequate nutrition delivery in children with ARDS was associated with improved clinical outcomes. Protein delivery may have potentially more impact than overall caloric delivery.

Energy Expenditure in Critically Ill Elderly Patients: Indirect Calorimetry vs Predictive Equations

BACKGROUND

Predictive equations (PEs) are used for estimating resting energy expenditure (REE) when the measurements obtained from indirect calorimetry (IC) are not available. This study evaluated the degree of agreement and the accuracy between the REE measured by IC (REE-IC) and REE estimated by PE (REE-PE) in mechanically ventilated elderly patients admitted to the intensive care unit (ICU).

METHODS

REE-IC of 97 critically ill elderly patients was compared with REE-PE by 6 PEs: Harris and Benedict (HB) multiplied by the correction factor of 1.2; European Society for Clinical Nutrition and Metabolism (ESPEN) using the minimum (ESPENmi), average (ESPENme), and maximum (ESPENma) values; Mifflin-St Jeor; Ireton-Jones (IJ); Fredrix; and Lührmann. Degree of agreement between REE-PE and REE-IC was analyzed by the interclass correlation coefficient and the Bland-Altman test. The accuracy was calculated by the percentage of male and/or female patients whose REE-PE values differ by up to ±10% in relation to REE-IC.

RESULTS

For both sexes, there was no difference for average REE-IC in kcal/kg when the values obtained with REE-PE by corrected HB and ESPENme were compared. A high level of agreement was demonstrated by corrected HB for both sexes, with greater accuracy for women. The best accuracy in the male group was obtained with the IJ equation but with a low level of agreement.

CONCLUSIONS

The effectiveness of PEs is limited for estimating REE of critically ill elderly patients. Nonetheless, HB multiplied by a correction factor of 1.2 can be used until a specific PE for this group of patients is developed.

Energy expenditure in mechanically ventilated patients: The weight of body weight!

BACKGROUND & AIMS

Optimal nutritional care for intensive care unit (ICU) patients requires precise determination of energy expenditure (EE) to avoid deleterious under- or overfeeding. The reference method, indirect calorimetry (IC), is rarely accessible and inconstantly feasible. Various equations for predicting EE based on body weight (BW) are available. This study aims at determining the best prediction strategy unless IC is available.

METHODS

Mechanically ventilated patients staying ≥72 h in the ICU were included, except those with contraindications for IC measurements. IC and BW measurements were routinely performed. EE was predicted by the ESPEN formula and other predictive equations using BW (i.e. anamnestic (AN), measured (MES), adjusted for cumulated water balance (ADJ), calculated for a body mass index (BMI) of 22.5). Comparisons were made using Pearson correlation and Bland & Altman plots.

RESULTS

85 patients (57 ± 19 y, 61 men, SAPS II 43 ± 16) were included. Correlations between IC and predicted EE using the ESPEN formula with different BW (BW_AN, BW_MES, BW_ADJ, and BW_BMI22.5) were 0.44, 0.40, 0.36, and 0.47, respectively. Bland & Altman plots showed wide and inconsistent variations. Predictive equations including body temperature and minute ventilation showed the best correlations, but when using various BWs, differences in predicted EE were observed.

CONCLUSION

No EE predictive equation, regardless of the BW used, gives statistically identical results to IC. If IC cannot be performed, predictive equations including minute ventilation and body temperature should be preferred. BW has a significant impact on estimated EE and the use of measured BW_MES or BW _{BMI 22.5} is associated with the best EE prediction. Clinical trial registration number on ClinicalTrial.gov: NCT02552446. Ethical committee number: CE-14-070.

Nutrition Assessment With Indirect Calorimetry in Patients Evaluated for Left Ventricular Assist Device Implantation

BACKGROUND

Malnutrition is known to negatively impact the clinical course of advanced heart failure and is associated with increased mortality following left ventricular assist device (LVAD) implantation. Appropriate assessment of nutrition requirements in these patients is critical in their clinical care, yet there has been little discussion on how to best determine resting energy expenditure (REE) in the hospital setting. We investigated the use of indirect calorimetry in a group of patients with advanced heart failure.

MATERIALS AND METHODS

Results from preoperative indirect calorimetry testing in 98 patients undergoing evaluation for LVAD candidacy were collected. REE was compared with 10 predictive equations that estimated caloric need based on a range of patient-specific demographic and clinical variables.

RESULTS

This study enrolled 22 female and 76 male patients with a mean age of 59.4 ± 12.5 years, body mass index of 29.6 ± 6.0 kg/m(2), and ejection fraction of 19.4 ± 6.6%. The average REE by indirect calorimetry in this group was 1610.0 ± 612.7 kcal/d. All predictive equations significantly overestimated REE. However, those equations intended for use in the critically ill demonstrated the greatest accuracy, with the Brandi equation achieving both the highest correlation (r = 0.605, P < .001) and the lowest standard error of the estimate (504.8 kcal/d).

CONCLUSIONS

Indirect calorimetry may be reliably and safely used to determine caloric requirements in patients with advanced heart failure. The use of predictive equations based on demographic and clinical parameters appears to generate inaccurate estimations of REE in these patients. However, equations designed for use in critically ill patients better estimate nutrition requirements than those designed for healthy individuals.

Nutrition management after pediatric solid organ transplantation

Survival rates for pediatric transplant recipients and organ grafts have increased due to improvements in surgical techniques and with immunosuppressant treatment therapies. Interdisciplinary management after pediatric organ transplantation is essential to assist not only with the complex medical issues and complications that can result from immunosuppressant therapy but also with the achievement of normal growth and development. Impaired growth is a complication frequently experienced by pediatric transplant patients. The presence or absence of impaired growth is affected by the length of illness prior to transplant, graft function, the use of corticosteroids, and the development of infectious complications after surgery. A review of posttransplant nutrition assessment, nutrition requirements, and nutrition goals is provided. In addition, a case series of experiences with nutrition management of pediatric solid organ transplant recipients is described.

Metabolic vs nutrition support: a hypothesis

It is now generally accepted that early feeding post injury exerts a positive effect on outcome in the critically ill, despite the fact that many of these patients are well nourished or even overnourished on admission. One possible mechanism is that early feeding post injury may have a positive influence on the duration and intensity of the systemic inflammatory response, especially when coupled with intensive insulin therapy to maintain normoglycemia at <150 mg/dL. Current clinical nutrition guidelines recommend early enteral nutrition providing full nutrition requirements in the critically ill patient; however, in the first week post injury, exclusive enteral feeding is typically inadequate, particularly in protein. A potentially new and different therapeutic goal to modulate the systemic inflammatory response might be more effectively accomplished for the first week post injury by hypocaloric feedings (~9-18 kcal/kg or 50%-75% resting metabolic expenditure) principally as intravenous dextrose but with at least 1 g/kg protein as intravenous amino acids to provide early metabolic support. This proposed regime, along with intensive insulin therapy to maintain glucose homeostasis, should promote the protein synthetic component of the postinjury inflammatory response while reducing net protein catabolism. A formal trial of early metabolic support in the acutely injured should be safe, easy to execute, and potentially efficacious, with subsequent improvement in the inflammatory state and, it is hoped, clinical outcomes.

The evolutionary role of nutrition and metabolic support in critical illness

Maintenance of nutritional status is particularly challenging during critical illness. There is a common perception of a race against the clock to adequately feed the patient to prevent or minimize the sometimes catastrophic muscle wasting and general catabolic state that can result in the patient's deterioration. However, the course of critical illness may be separated into 3 phases, each with highly differing metabolic needs. The initial phase, in which the body attempts to fight the acute insult, is generally hypermetabolic. When the body fails to overcome the insult, it enters into a second phase, which is akin to hibernation. This stage is characterized by a functional metabolic shutdown triggered either by a lack of adequate energy supply or perhaps by the direct switching off of metabolism to spare excess use of a dwindling substrate and energy resource. Those strong enough to survive this phase enter into a period of recovery during which appetite returns, anabolism recommences, and organ function is restored. Nutrition should perhaps closely follow these nonlinear requirements, so as to avoid deleterious under- or overnutrition during the appropriate phase. This approach fits a teleologic argument that enabled many sick people to survive well before the advent of modern medicine and explains why catabolism still occurs despite adequate feeding.

Nutritional requirements of surgical and critically-ill patients: do we really know what they need?

Malnutrition remains a problem in surgical and critically-ill patients. In surgical patients the incidence of malnutrition ranges from 9 to 44%. Despite this variability there is a consensus that malnutrition worsens during hospital stay. In the intensive care unit (ICU), 43% of the patients are malnourished. Although poor nutrition during hospitalisation may be attributable to many factors, not least inadequacies in hospital catering services, there must also be the question of whether those patients who receive nutritional support are being fed appropriately. Indirect calorimetry is the ‘gold standard’ for determining an individual's energy requirements, but limited time and financial resources preclude the use of this method in everyday clinical practice. Studies in surgical and ICU patient populations have been reviewed to determine the ‘optimal’ energy and protein requirements of these patients. There are only a small number of studies that have attempted to measure energy requirements in the various surgical patient groups. Uncomplicated surgery has been associated with energy requirements of 1·0–1·15×BMR whilst complicated surgery requires 1·25–1·4×BMR in order to meet the patient's needs. Identifying the optimal requirements of ICU patients is far more difficult because of the heterogeneous nature of this population. In general, 5·6 kJ (25 kcal)/kg per d is an acceptable and achievable target intake, but patients with sepsis or trauma may require almost twice as much energy during the acute phase of their illness. The implications of failing to meet and exceeding the requirements of critically-ill patients are also reviewed.

Analysis of estimation methods for resting metabolic rate in critically ill adults

BACKGROUND

Prediction of metabolic rate is an important part of the nutrition assessment of critically ill patients, yet there are limited data regarding the best equation to use to make this prediction.

METHODS

Standardized indirect calorimetry measurements were made in 202 ventilated, adult critical care patients, and resting metabolic rate was calculated using the following equations: Penn State equation, Faisy, Brandi, Swinamer, Ireton-Jones, Mifflin, Mifflinx1.25, Harris Benedict, Harris Benedictx1.25, Harris Benedict using adjusted weight for obesity, and each of the adjusted weight versions of Harris Benedictx1.25. The subjects were subgrouped by age and obesity status (young nonobese, young obese, elderly nonobese, elderly obese). Performance of each equation was assessed using bias, precision, and accuracy rate statistics.

RESULTS

Accuracy rates in the study population ranged from 67% for the Penn State equation to 18% for the weight-adjusted Harris Benedict equation (without multiplication). Within subgroups, the highest accuracy rate was 77% in the elderly nonobese using the Penn State equation and the lowest was 0% for the weight-adjusted Harris Benedict equation. The Penn State equation was the only equation that was unbiased and precise across all subgroups. The obese elderly group was the most difficult to predict. Therefore, a separate regression was computed for this group: Mifflin(0.71)+Tmax(85)+Ve(64)-3085.

CONCLUSIONS

The Penn State equation provides the most accurate assessment of metabolic rate in critically ill patients if indirect calorimetry is unavailable. An alternate form of this equation for elderly obese patients is presented, but has yet to be validated.

Prediction of resting metabolic rate in critically ill adult patients: results of a systematic review of the evidence

Metabolic rate is generally assessed by use of equations in critically ill patients, but evidence pertaining to the validity of these equations in this population has not been systematically evaluated. This paper represents the first such systematic analysis in adult patients. A work group created by the American Dietetic Association identified pertinent peer-reviewed articles. The work group systematically evaluated these articles and formulated conclusion statements and grades based on the available evidence. Seven equations plus the Fick method were found to have validation work that met criteria for inclusion in this analysis. The Harris-Benedict equation with and without modifiers had the most validation work behind it (n=13), followed by Ireton-Jones (1992 and 1997) (n=9), Penn State (1998, 2003) (n=2), and Swinamer (n=1). Five studies pertaining to the Fick method met acceptance criteria. Based on these validation studies, the Harris-Benedict, Ireton-Jones 1997, and Fick methods can be confidently eliminated from use in assessment of energy expenditure in critically ill patients. The Penn State 2003, Swinamer, and Ireton-Jones 1992 equations may be useful in critically ill nonobese patients, whereas the Ireton-Jones 1992 and Penn State 1998 equations seem to be useful in obese patients. The strength of these conclusions is moderated because of limited and sometimes inconsistent data. More validation work is needed to confirm and increase the strength of these conclusions.

How many calories are necessary during critical illness?

Several nutritional alternatives exist to provide critically ill patients sufficient calories to meet metabolic demands. Intuitively, investigators, nutritionists, and clinicians have pursued the goal of providing high-calorie nutrition support, believing that this would improve outcomes. There is little evidence, however, that meeting caloric goals is of significant benefit. In fact, accumulating data suggest that feeding patients below previously described caloric goals is associated with better outcomes, including decreases in hospital stay, ventilator dependence, use of antibiotics, and even mortality. This suggests that permissive underfeeding could replace the paradigm of meeting measured caloric goals. Prospective evidence to support adoption of permissive underfeeding is lacking, however. Appropriate clinical studies are necessary to prove its safety and efficacy.

Poor agreement between continuous measurements of energy expenditure and routinely used prediction equations in intensive care unit patients

BACKGROUND & AIMS

A wide variation in 24h energy expenditure has been demonstrated previously in intensive care unit (ICU) patients. The accuracy of equations used to predict energy expenditure in critically ill patients is frequently compared with single or short-duration indirect calorimetry measurements, which may not represent the total energy expenditure (TEE) of these patients. To take into account this variability in energy expenditure, estimates have been compared with continuous indirect calorimetry measurements.

METHODS

Continuous (24h/day for 5 days) indirect calorimetry measurements were made in patients requiring mechanical ventilation for 5 days. The Harris-Benedict, Schofield and Ireton-Jones equations and the American College of Chest Physicians recommendation of 25 kcal/kg/day were used to estimate energy requirements.

RESULTS

A total of 192 days of measurements, in 27 patients, were available for comparison with the different equations. Agreement between the equations and measured values was poor. The Harris-Benedict, Schofield and ACCP equations provided more estimates (66%, 66% and 65%, respectively) within 80% and 110% of TEE values. However, each of these equations would have resulted in clinically significant underfeeding (<80% of TEE) in 16%, 15% and 22% of patients, respectively, and overfeeding (>110% of TEE) in 18%, 19% and 13% of patients, respectively.

CONCLUSIONS

Limits of agreement between the different equations and TEE values were unacceptably wide. Prediction equations may result in significant under or overfeeding in the clinical setting.

Resting energy expenditure during mechanical ventilation and its relationship with the type of lesion

BACKGROUND

Resting energy expenditure (REE) of critically ill patients is usually calculated according to basal energy expenditure obtained from Harris-Benedict equations traditionally corrected by different stress factors, resulting in a variable accuracy for the individual patient. The objective of this study was to investigate whether or not the type of lesion affects the metabolism level of critically ill patients treated with mechanical ventilation. We performed a retrospective study measuring the REE of critically ill patients with 3 different types of lesions (trauma, medical, surgical) who were treated with mechanical ventilation and sedation. Each lesion group of patients was matched with another group, differing in the type of lesion, according to gender, age, and weight.

METHODS

Eighty-seven from a database of 175 critically ill patients undergoing indirect calorimetry were necessary for matching. Twenty matched pairs of patients for each of the following different type of lesion were obtained: medical vs surgical, medical vs trauma, and surgical vs trauma.

RESULTS

The mean REE difference was 52 kcal/d (95% confidence interval [CI] of -136 -241 kcal/d) for the medical vs surgical group, 5 kcal/d (95% CI -236 -247 kcal/d) for the medical vs trauma group and 43 kcal/d (95% CI of -132-219 kcal/d) for the surgical vs trauma group. No statistically significant differences between groups were found in the measured REE. We did not find statistically significant differences in the measured REE of patients with and without infection.

CONCLUSIONS

Critically ill patients with different types of lesion treated with mechanical ventilation have similar measured REE.

Accurate Determination of Energy Needs in Hospitalized Patients

OBJECTIVE

To evaluate the accuracy of seven predictive equations, including the Harris-Benedict and the Mifflin equations, against measured resting energy expenditure (REE) in hospitalized patients, including patients with obesity and critical illness.

DESIGN

A retrospective evaluation using the nutrition support service database of a patient cohort from a similar timeframe as those used to develop the Mifflin equations.

SUBJECTS/SETTING

All patients with an ordered nutrition assessment who underwent indirect calorimetry at our institution over a 1-year period were included.

INTERVENTION

Available data was applied to REE predictive equations, and results were compared to REE measurements.

MAIN OUTCOME MEASURES

Accuracy was defined as predictions within 90% to 110% of the measured REE. Differences >10% or 250 kcal from REE were considered clinically unacceptable.

STATISTICAL ANALYSES PERFORMED

Regression analysis was performed to identify variables that may predict accuracy. Limits-of-agreement analysis was carried out to describe the level of bias for each equation.

RESULTS

A total of 395 patients, mostly white (61%) and African American (36%), were included in this analysis. Mean age+/-standard deviation was 56+/-18 years (range 16 to 92 years) in this group, and mean body mass index was 24+/-5.6 (range 13 to 53). Measured REE was 1,617+/-355 kcal/day for the entire group, 1,790+/-397 kcal/day in the obese group (n=51), and 1,730+/-402 kcal/day in the critically ill group (n=141). The most accurate prediction was the Harris-Benedict equation when a factor of 1.1 was multiplied to the equation (Harris-Benedict 1.1), but only in 61% of all the patients, with significant under- and over-predictions. In the patients with obesity, the Harris-Benedict equation using actual weight was most accurate, but only in 62% of patients; and in the critically ill patients the Harris-Benedict 1.1 was most accurate, but only in 55% of patients. The bias was also lowest with Harris-Benedict 1.1 (mean error -9 kcal/day, range +403 to -421 kcal/day); but errors across all equations were clinically unacceptable.

CONCLUSIONS

No equation accurately predicted REE in most hospitalized patients. Without a reliable predictive equation, only indirect calorimetry will provide accurate assessment of energy needs. Although indirect calorimetry is considered the standard for assessing REE in hospitalized patients, several predictive equations are commonly used in practice. Their accuracy in hospitalized patients has been questioned. This study evaluated several of these equations, and found that even the most accurate equation (the Harris-Benedict 1.1) was inaccurate in 39% of patients and had an unacceptably high error. Without knowing which patient's REE is being accurately predicted, indirect calorimetry may still be necessary in difficult to manage hospitalized patients.

Nutritional gain versus financial gain: The role of metabolic carts in the surgical ICU

BACKGROUND

Adequate nutritional replacement of critically ill and injured patients is of paramount importance, as it decreases infectious morbidity and mortality. However, multiple methods of determining nutritional requirements exist, including mathematical formulas, weight based calculations, and the use of metabolic cart measurements, the latter of which is associated with significant labor and equipment costs. We hypothesized that metabolic cart measurements, despite increasing the cost of care, would more accurately determine nutritional requirements in a critically ill population than formulaic or weight-based calculations.

METHODS

Consecutive metabolic cart measurements were prospectively obtained on 59 critically ill surgery and trauma patients, and compared with predicted values as determined by the Harris-Benedict equation and weight-based calculations. Comparison was made to actual resting energy expenditure data acquired via indirect calorimetry data obtained from serial metabolic carts.

RESULTS

There were 59 patients who formed the study population, with 37% of the population having two or more metabolic cart readings (total number of cart readings was 106). There was no statistically significant difference between the metabolic cart results, the predicted resting energy expenditure as calculated by the Harris-Benedict equation adjusted with a factor of 1.5, and a weight based calculation at 30 kcal/kg adjusted body weight. Metabolic requirements were stable over time (4-48 days) without significant variation. Nutritional parameters, as evaluated by the visceral proteins prealbumin and transferrin significantly increased with time in injured patients.

CONCLUSIONS

Either 30 kcal/kg adjusted body weight or the resting energy expenditure calculated from the Harris-Benedict equation multiplied by 1.5 adequately predicts the nutritional requirements of critically ill surgery and trauma patients. The addition of metabolic cart data does not provide any additional information in the determination of caloric needs in the critically ill and injured patient. In this population, omission of metabolic cart data would have saved 33,000 dollars without adversely affecting patient outcome.

Advances in Surgical Nutrition

Dr. Stanley Dudrick invented total parenteral nutrition in 1968, providing a desperately needed therapy to those patients who could not eat. It has since saved thousands of patients worldwide. Nutrition interventions (NI) in surgical/trauma and critically ill patients have evolved dramatically during the last 20 years from a supportive therapy to a clear therapeutic role. Like any other form of therapy, NI will benefit patients when adequately indicated and prescribed. NI, however, may cause significant side effects and harm when poorly ordered. This article reviews the indications for the prescription of the different forms of NI available to the clinician caring for the surgical patient.

Indirect calorimetry: a trend toward continuous metabolic assessment

Physiologic monitoring of the patient's metabolic response to illness and nutritional needs has been available for many decades. Traditional methods for estimating and intermittently assessing the patient's metabolic status provide incomplete and often misleading information. The measurement oxygen consumption (VO2) and carbon dioxide production (VCO2) for assessment of the critically ill patient's metabolic status has been underutilized partly because of the limitations of available technologies. Recent advances in gas exchange technologies have made VO2 and VCO2 assessment readily available at the bedside on a continuous basis. This article provides a clinical review of specific current literature related to indirect calorimetry. A synthesis of the data supports the use of gas exchange measurements of VO2 and VCO2 for serial assessment of metabolic changes and for monitoring of the patient's nutritional status. Furthermore, a multidisciplinary approach to metabolic monitoring and nutritional assessment provides a cost-efficient means of patient care, which, when properly implemented, improves patient outcomes.

Clinical evaluation of a continuous oxygen consumption monitor in mechanically ventilated patients

We measured oxygen consumption using a new noninvasive modular metabolic monitor, M-COVX trade mark, in ventilated critically ill patients. Oxygen consumption was measured continuously as part of routine monitoring for up to 24 h following mechanical ventilation in 27 patients admitted to a general intensive care unit. We explored several possible sources of error. Most errors related to inaccurate tidal volume measurement, which resulted in rejection of a median 14% (interquartile range 8-34%) of data. Water accumulation in the pneumotachograph was responsible and occurred more frequently with water bath humidifiers. After manual removal of erroneous data mean oxygen consumption values were virtually identical to calculated values in 24 of 27 patients. We conclude that in most ventilated patients averaging of continuous oxygen consumption data with the M-COVX module results in small errors.

Metabolic response and parenteral nutrition in trauma, sepsis, and burns

Trauma, sepsis, and burns cause abnormal manifestations in the body. These manifestations can cause alterations in body metabolism, which complicates nutritional management. Goals of nutrition support with assessment modifications for a constantly changing population are reviewed. Patients in such stress states as burns, trauma, and sepsis many times need altered nutrition. This article outlines guidelines for total parenteral formula modification and monitoring, and discusses other complications such as drug interactions with parenteral formulas.