Retrospective Evaluation of Commonly Used Equations to Predict Energy Expenditure in Mechanically Ventilated, Critically Ill Patients

Estimated versus measured energy expenditure in ventilated surgical-trauma critically Ill patients

BACKGROUND

The American and European guidelines recommend measuring resting energy expenditure (REE) using indirect calorimetry (IC). Predictive equations (PEs) are used to estimate REE, but there is limited evidence for their use in critically ill patients. The aim of this study is to evaluate the degree of agreement and accuracy between IC-REE and ten different PEs in mechanically ventilated surgical-trauma critically ill patients who met their estimated caloric requirement.

METHODS

IC-REE was retrospectively compared to PE-REE by 10 PEs. Degree of agreement between REE-PE and REE-IC was analyzed by the Bland-Altman test (BAt) and the Concordance Correlation Coefficient (CCC). The accuracy was calculated by the percentage of patients whose REE-PE values differ by up to ±10% in relation to REE-IC. All analyses were stratified by gender and BMI (< 25 vs ≥ 25).

RESULTS

104 patients were analyzed and the closest estimate to IC-REE was the modified Harris-Benedict equation (mHB) by the BAt with a mean difference of 49.2 overall, 61.6 for males, 28.5 for females, 67.5 for BMI < 25 and 42.5 for BMI ≥ 25. The overall CCC between the IC-REE and mHB was 0.652; 0.560 for males; 0.496 for females; 0.570 for BMI < 25; and 0.598 for BMI ≥ 25. Modified HB equation was the most accurate with overall accuracy of 44.2%.

CONCLUSIONS

Effectiveness of PEs for estimating REE of mechanically ventilated surgical-trauma critically ill patients is limited. Nonetheless, of all the 10 equations examined, the closest to IC measured REE was the modified HB equation. This article is protected by copyright. All rights reserved.

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.

ICU Nurses' Perceived Barriers to Effective Enteral Nutrition Practices: A Multicenter Survey Study

BACKGROUND

Critically ill patients are hypermetabolic and have increased energy requirements, making nutritional support a vital intervention. In the Intensive Care Units, enteral nutrition is based on opinions rather than evidence-based practices. Therefore, there is a need to identify the barriers to evidence based practice protocols for enteral feeding of patients in Jordanian ICUs.

AIMS

To explore Jordanian ICU nurses' perceived barriers for enteral nutrition that hinders them from utilizing the recommended EN guidelines.

METHODS

A descriptive cross-sectional design was utilized using self-administered questionnaire. A total of 131 nurses participated from different hospitals representing different healthcare sectors in Jordan.

RESULTS

The five barriers subscales' means were almost equal ranging from 4.04 (Delivery of EN to the Patient) to 4.33 (ICU Resources) (out of 7). The most important barrier was "Not enough nursing staff to deliver adequate nutrition" (M=4.80, SD=1.81, 60%), followed by "Fear of adverse events due to aggressively feeding patients" (M= 4.59, SD=1.50, 56%). Although no significant differences in the mean barrier score were revealed, minimal significant differences were revealed that were distributed among different barrier subscales.

CONCLUSION

Participants moderately perceived barriers with more focus on insufficient resources in ICU and among healthcare providers. Such barriers are modifiable and manageable, making their identification and management crucial for optimal patient care. This study confirms that enteral nutrition is a multidisciplinary responsibility.

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.

Indirect Calorimetry: A Practical Guide for Clinicians

This review provides clinicians with a comprehensive overview of indirect calorimetry including the principles, methodology, technologic advancements, benefits, and challenges. Clinical applications for indirect calorimetry and the potential limitations are specifically addressed for both the inpatient and outpatient setting. Measurement of energy expenditure is the most accurate method to assess energy needs. Indirect calorimetry remains a gold standard in measuring energy expenditure in the clinical settings. The benefits of providing optimal nutrition for recovery from illness and chronic health management are well documented. Indirect calorimetry offers a scientifically-based approach to customize a patient's energy needs and nutrient delivery to maximize the benefits of nutrition therapy. With recent advances in technology, indirect calorimeters are easier to operate, more portable, and affordable. Increased utilization of indirect calorimetry would facilitate individualized patient care and should lead to improved treatment outcomes.

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.

Ventilator-derived carbon dioxide production to assess energy expenditure in critically ill patients: proof of concept

Introduction

Measurement of energy expenditure (EE) is recommended to guide nutrition in critically ill patients. Availability of a gold standard indirect calorimetry is limited, and continuous measurement is unfeasible. Equations used to predict EE are inaccurate. The purpose of this study was to provide proof of concept that EE can be accurately assessed on the basis of ventilator-derived carbon dioxide production (VCO₂) and to determine whether this method is more accurate than frequently used predictive equations.

Methods

In 84 mechanically ventilated critically ill patients, we performed 24-h indirect calorimetry to obtain a gold standard EE. Simultaneously, we collected 24-h ventilator-derived VCO₂, extracted the respiratory quotient of the administered nutrition, and calculated EE with a rewritten Weir formula. Bias, precision, and accuracy and inaccuracy rates were determined and compared with four predictive equations: the Harris–Benedict, Faisy, and Penn State University equations and the European Society for Clinical Nutrition and Metabolism (ESPEN) guideline equation of 25 kcal/kg/day.

Results

Mean 24-h indirect calorimetry EE was 1823 ± 408 kcal. EE from ventilator-derived VCO₂ was accurate (bias +141 ± 153 kcal/24 h; 7.7 % of gold standard) and more precise than the predictive equations (limits of agreement −166 to +447 kcal/24 h). The 10 % and 15 % accuracy rates were 61 % and 76 %, respectively, which were significantly higher than those of the Harris–Benedict, Faisy, and ESPEN guideline equations. Large errors of more than 30 % inaccuracy did not occur with EE derived from ventilator-derived VCO₂. This 30 % inaccuracy rate was significantly lower than that of the predictive equations.

Conclusions

In critically ill mechanically ventilated patients, assessment of EE based on ventilator-derived VCO₂ is accurate and more precise than frequently used predictive equations. It allows for continuous monitoring and is the best alternative to indirect calorimetry.

Controversies in nutritional support for critically ill children

Nutritional support for critically ill infants and children is of paramount importance and can greatly affect the outcome of these patients. The energy requirement of children is unique to their size, gestational age, and physiologic stress, and the treatment algorithms developed in adult intensive care units cannot easily be applied to pediatric patients. This article reviews some of the ongoing controversial topics of fluid, electrolyte, and nutritional support for critically ill pediatric patients focusing on glycemic control and dysnatremia. The use of enteral and parenteral nutrition as well as parenteral nutritional-associated cholestasis will also be discussed.

Prevalence of Underprescription or Overprescription of Energy Needs in Critically Ill Mechanically Ventilated Adults as Determined by Indirect Calorimetry: A Systematic Literature Review

BACKGROUND

Underfeeding and overfeeding has been associated with adverse patient outcomes. Resting energy expenditure can be measured using indirect calorimetry. In its absence, predictive equations are used. A systematic literature review was conducted to determine the prevalence of underprescription and overprescription of energy needs in adult mechanically ventilated critically ill patients by comparing predictive equations to indirect calorimetry measurements.

METHODS

Ovid MEDLINE, CINAHL Plus, Scopus, and EMBASE databases were searched in May 2013 to identify studies that used both predictive equations and indirect calorimetry to determine energy expenditure. Reference lists of included publications were also searched. The number of predictive equations that underestimated or overestimated energy expenditure by ±10% when compared to indirect calorimetry measurements were noted at both an individual and group level.

RESULTS

In total, 2349 publications were retrieved, with 18 studies included. Of the 160 variations of 13 predictive equations reviewed at a group level, 38% underestimated and 12% overestimated energy expenditure by more than 10%. The remaining 50% of equations estimated energy expenditure to within ±10 of indirect calorimetry measurements. On an individual patient level, predictive equations underestimated and overestimated energy expenditure in 13-90% and 0-88% of patients, respectively. Differences of up to 43% below and 66% above indirect calorimetry values were observed.

CONCLUSIONS

Large discrepancies exist between predictive equation estimates and indirect calorimetry measurements in individuals and groups. Further research is needed to determine the influence of indirect calorimetry and predictive equation limitations in contributing to these observed differences.

Nutrition therapy for critically ill and injured patients

BACKGROUND

Nutrition support has undergone significant advances in recent decades, revolutionizing the care of critically ill and injured patients. However, providing adequate and optimal nutrition therapy for such patients is very challenging: it requires careful attention and an understanding of the biology of the individual patient's disease or injury process, including insight into the consequent changes in nutrients needed.

OBJECTIVE

The objective of this article is to review the current principles and practices of providing nutrition therapy for critically ill and injured patients.

METHODS

Review of the literature and evidence-based guidelines.

RESULTS

The evidence demonstrates the need to understand the biology of nutrition therapy for critically ill and injured patients, tailored to their individual disease or injury, age, and comorbidities.

CONCLUSION

Nutrition therapy for critically ill and injured patients has become an important part of their overall care. No longer should we consider nutrition for critically ill and injured patients just as "support" but, rather, as "therapy", because it is, indeed, a key therapeutic modality.

Bedside calculation of energy expenditure does not guarantee adequate caloric prescription in long-term mechanically ventilated critically ill patients: a quality control study

Nutrition is essential in critically ill patients, but translating caloric prescriptions into adequate caloric intake remains challenging. Caloric prescriptions (P), effective intake (I), and caloric needs (N), calculated with modified Harris-Benedict formulas, were recorded during seven consecutive days in ventilated patients. Adequacy of prescription was estimated by P/N ratio. I/P ratio assessed accuracy of translating a prescription into administered feeding. I/N ratio compared delivered calories with theoretical caloric needs. Fifty patients were prospectively studied in a mixed medicosurgical ICU in a teaching hospital. Basal and total energy expenditure were, respectively, 1361 ± 171 kcal/d and 1649 ± 233 kcal/d. P and I attained 1536 ± 602 kcal/d and 1424 ± 572 kcal/d, respectively. 24.6% prescriptions were accurate, and 24.3% calories were correctly administered. Excessive calories were prescribed in 35.4% of patients, 27.4% being overfed. Caloric needs were underestimated in 40% prescriptions, with 48.3% patients underfed. Calculating caloric requirements by a modified standard formula covered energy needs in only 25% of long-term mechanically ventilated patients, leaving many over- or underfed. Nutritional imbalance mainly resulted from incorrect prescription. Failure of "simple" calculations to direct caloric prescription in these patients suggests systematic use of more reliable methods, for example, indirect calorimetry.

Perioperative nutritional support: immunonutrition, probiotics, and anabolic steroids

Nutritional support in surgical patients has evolved from simple provision of adequate calories to retard loss of lean body mass to the provision of specific nutrients in an attempt to manipulate metabolic and immune responses. Although still limited, the current understanding of this complex subject indicates that the type, route, amount, and composition of nutritional support provided to patients can affect their outcome. Further studies are, however, needed to better characterize the exact nutritional support that is most beneficial for a specific disease state and a specific patient.

Nutrition support for the acute lung injury/adult respiratory distress syndrome patient: a review

Support for Acute Lung Injury (ALI) and Adult Respiratory Distress Syndrome (ARDS) in many ways represents the summation of all intensive care unit nutrition modalities. Basic tenets of management are based on those established for the general population of mechanically ventilated patients. As a marker of critical illness however, patients with ALI/ARDS suffer from other organ dysfunctions that require advanced support. Specific issues to be considered in this population include carbon dioxide production, prevention of aspiration, and modulation of the inflammatory response. These particular areas, with special attention paid to the role of lipids in ALI/ARDS, will be reviewed.

Optimal nutrition during the period of mechanical ventilation decreases mortality in critically ill, long-term acute female patients: a prospective observational cohort study

Introduction

Optimal nutrition for intensive care patients has been proposed to be the provision of energy as determined by indirect calorimetry, and protein provision of at least 1.2 g/kg pre-admission weight per day. The evidence supporting these nutritional goals is based on surrogate outcomes and is not yet substantiated by patient oriented, clinically meaningful endpoints. In the present study we evaluated the effects of achieving optimal nutrition in ICU patients during their period of mechanical ventilation on mortality.

Methods

This was a prospective observational cohort study in a mixed medical-surgical, 28-bed ICU in an academic hospital. 243 sequential mixed medical-surgical patients were enrolled on day 3–5 after admission if they had an expected stay of at least another 5–7 days. They underwent indirect calorimetry as part of routine care. Nutrition was guided by the result of indirect calorimetry and we aimed to provide at least 1.2 g of protein/kg/day. Cumulative balances were calculated for the period of mechanical ventilation. Outcome parameters were ICU, 28-day and hospital mortality.

Results

In women, when corrected for weight, height, Apache II score, diagnosis category, and hyperglycaemic index, patients who reached their nutritional goals compared to those who did not, showed a hazard ratio (HR) of 0.199 for ICU mortality (CI 0.048–0.831; P = 0.027), a HR of 0.079 for 28 day mortality (CI 0.013–0.467; P = 0.005) and a HR of 0.328 for hospital mortality (CI 0.113–0.952; P = 0.04). Achievement of energy goals whilst not reaching protein goals, did not affect ICU mortality; the HR for 28 day mortality was 0.120 (CI 0.027–0.528; P = 0.005) and 0.318 for hospital mortality (CI 0.107–0.945; P = 0.039). No difference in outcome related to optimal feeding was found for men.

Conclusions

Optimal nutritional therapy improves ICU, 28-day and hospital survival in female ICU patients. Female patients reaching both energy and protein goals have better outcomes than those reaching only the energy goal. In the present study men did not benefit from optimal nutrition.

Cumulative energy imbalance in the pediatric intensive care unit: role of targeted indirect calorimetry

INTRODUCTION

Failure to accurately estimate energy requirements may result in underfeeding or overfeeding. In this study, a dedicated multidisciplinary nutrition team measured energy expenditure in critically ill children.

METHODS

Steady-state indirect calorimetry was used to obtain measured resting energy expenditure, which was compared with equation-estimated energy expenditure and the total energy intake for each subject. The children's metabolic status was examined in relation to standard clinical characteristics.

RESULTS

Sixteen measurements were performed in 14 patients admitted to the multidisciplinary pediatric intensive care unit over a period of 12 months. Mean age of subjects in this cohort was 11.2 years (range 1.6 months to 32 years) and included 7 males and 7 postoperative patients. Altered metabolism was detected in 13 of 14 subjects and in 15 of 16 (94%) measurements. There was no correlation between the metabolic status of subjects and their clinical characteristics. Average daily energy balance was 200 kcal/d (range -518 to +859 kcal/d). Agreement between measured resting energy expenditure and equation-estimated energy expenditure was poor, with mean bias of 72.3 +/- 446 kcal/d (limits of agreement -801.9 to + 946.5 kcal/d).

CONCLUSIONS

A disparity was observed between equation-estimated energy expenditure, measured resting energy expenditure, and total energy intake, with a high incidence of underfeeding or overfeeding. A wide range of metabolic alterations were recorded, which could not be accurately predicted using standard clinical characteristics. Targeted indirect calorimetry on high-risk patients selected by a dedicated nutrition team may prevent cumulative excesses and deficits in energy balance.

Validation of a predictive method for an accurate assessment of resting energy expenditure in medical mechanically ventilated patients

OBJECTIVE

Use comparison with indirect calorimetry to confirm the ability of our previously described equation to predict resting energy expenditure in mechanically ventilated patients.

DESIGN

Prospective, validation study.

SETTING

Eighteen-bed, medical intensive care unit at a teaching hospital.

PATIENTS

All adult patients intubated >24 hrs were assessed for eligibility. Exclusion criteria were clinical situations that could contribute to erroneous calorimetric measurements.

INTERVENTIONS

Resting energy expenditure was calculated using the original Harris-Benedict equations and those corrected for usual stress factors, the Swinamer equation, the Fusco equation, the Ireton-Jones equation, and our equation: resting energy expenditure (kcal/day) = 8 x weight (kg) + 14 x height (cm) + 32 x minute ventilation (L/min) + 94 x temperature (degrees C) - 4834.

MEASUREMENTS AND MAIN RESULTS

Resting energy expenditure was measured by indirect calorimetry for the 45 included patients. Resting energy expenditure calculated with our predictive model correlated with the measured resting energy expenditure (r2 = .62, p < .0001), and Bland-Altman analysis showed a mean bias of -192 +/- 277 kcal/day, with limits of agreement ranging from -735 to 351 kcal/day. Resting energy expenditure calculated with the Harris-Benedict equations was more weakly correlated with measured resting energy expenditure (r2 = .41, p < .0001), with Bland-Altman analysis showing a mean bias of 279 +/- 346 kcal/day between them and the limits of agreement ranging from -399 to 957 kcal/day. Applying usual stress-correction factors to the Harris-Benedict equations generated wide variability, and the correlation with measured resting energy expenditure was poorer (r2 = .18, p < .0001), with Bland-Altman analysis showing a mean bias of -357 +/- 750 kcal/day and limits of agreement ranging from -1827 to 1113 kcal/day. The use of the Swinamer, Fusco, or Ireton-Jones predictive methods yielded weaker correlation between calculated and measured resting energy expenditure (r2 = .41, p < .0001; r2 = .38, p < .0001; r2 = .39, p < .0001, respectively) than our equation, and Bland-Altman analysis showed no improvement in agreement and variability between methods.

CONCLUSIONS

The Faisy equation, based on static (height), less stable (weight), and dynamic biometric variables (temperature and minute ventilation), provided precise and unbiased resting energy expenditure estimations in mechanically ventilated patients.

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.

The addition of fiber and the use of continuous infusion decrease the incidence of diarrhea in elderly tube-fed patients in medical wards of a general regional hospital: a controlled clinical trial

GOALS

To determine if feeds high in fiber continuously administered might minimize diarrhea.

BACKGROUND

The addition of soluble fiber to enteral feedings has not consistently decreased diarrhea in controlled clinical trials, and the effect of the use of intermittent or continuous infusions on the rate of diarrhea is similarly controversial.

STUDY

We studied 148 of 160 selected elderly well-nourished patients with acute disease prohibiting oral intake in a controlled clinical trial in the setting of an internal medicine departments in a regional hospital who were divided into 4 groups and fed according to combinations of intermittent or continuous systems, with fiber-free or fiber rich formulas. The 5-day rate of diarrhea was defined as 2 liquid stools or 3 or more semisolid or liquid bowel movements during a 24-hour period. Other outcome variables included mortality, hospital days, prolonged hospitalization (over 20 d), fever, and stools positive for Clostridium difficile cytotoxin A/B.

RESULTS

The increased relative risk of the continuous/fiber-free, intermittent/fiber, and intermittent/fiber-free groups compared with the continuous/fiber group was 2.8 [95% confidence interval (CI)=1.0-8.1], 2.5 (95% CI=0.9-7.1), and 5.0 (95% CI=1.9-13.2), respectively. These findings were independent of age (>80 y), female sex, being treated with antibiotics for respiratory or urinary infections, receiving respiratory support, or being fully conscious. There were no significant differences in the other outcomes.

CONCLUSIONS

We conclude that in elderly well-nourished hospitalized patients with acute diseases prohibiting oral intake, continuous and closed enteral feedings with the addition of fiber is effective in reducing the rate of diarrhea.

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.

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.

Energy expenditure in hospitalized patients: implications for nutritional support

An understanding of energy expenditure in hospitalized patients is necessary to determine optimal energy supply in the care of individuals who require nutritional support. A review was conducted of 19 studies in which resting energy expenditure (REE) had been measured using indirect calorimetry and compared with estimated basal energy expenditure (BEE) from the Harris-Benedict equation. Studies of patients with burns, head injuries, and fever were excluded because REE is known to be increased in these conditions. The studies reported data on 1256 patients with the following diagnoses: postoperative (28%), trauma or sepsis (26%), cancer (18%), pulmonary disease (9%), cardiovascular disease (2%), miscellaneous (9%), and unspecified (6%). The average REE in the 19 studies was 113% of the BEE. The mean +/- SD REE/BEE ratio was higher in 11 studies in which the REE was measured during feeding than in 5 studies in which the measurement was made during fasting (117% +/- 3% vs 105% +/- 4%; P = .047). In those 11 studies, overfeeding may have contributed to higher REE values than otherwise would have been observed. Some evidence indicated that the REE/BEE ratio is higher in more severe illness, but results were inconsistent. Unfortunately, little information is available concerning total energy expenditure, which includes the contribution of physical activity. It appears that most patients can be fed adequately with energy equal to 100% to 120% of estimated BEE. Hypoenergetic feeding may be appropriate in some overweight and obese individuals. Additional research in hospitalized patients on total energy expenditure and on the relationship between severity of illness and energy expenditure is needed.