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

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.

A comparison of predictive equations of energy expenditure and measured energy expenditure in critically ill patients

PURPOSE

Multiple equations exist for predicting resting energy expenditure (REE). The accuracy of these for estimating energy requirements of critically ill patients is not clear, especially for obese patients. We sought to compare REE, calculated with published formulas, with measured REE in a cohort of mechanically ventilated subjects.

MATERIALS AND METHODS

We retrospectively identified all mechanically ventilated patients with measured body mass index who underwent indirect calorimetry in the intensive care unit. Limits of agreement and Pitman's test of difference in variance were performed to compare REE by equations with REE measured by indirect calorimetry.

RESULTS

A total of 927 patients were identified, including 401 obese patients. There were bias and poor agreement between measured REE and REE predicted by the Harris-Benedict, Owen, American College of Chest Physicians, and Mifflin equations (P > .05). There was poor agreement between measured and predicted REE by the Ireton-Jones equation, stratifying by sex. Ireton-Jones was the only equation that was unbiased for men and those in weight categories 1 and 2. In all cases except Ireton-Jones, predictive equations underestimated measured REE.

CONCLUSION

None of these equations accurately estimated measured REE in this group of mechanically ventilated patients, most underestimating energy needs. Development of improved predictive equations for adequate assessment of energy needs is needed.

Optimal caloric intake for critically ill patients: first, do no harm

Despite considerable efforts to define energy requirements for critically ill patients, no single method has been found to be precise and unbiased for all patients. As a result, clinicians have used various methods that may overestimate energy requirements for some patients. Provision of target caloric intake without regard to the complications of overfeeding, such as hyperglycemia, hypercapnia, or gastric feeding intolerance, could result in overall detrimental clinical outcome. Inadequate nutrition support is also associated with adverse clinical outcomes that necessitate optimization of delivery and tolerance of the nutrition regimen. A pivotal paper by Krishnan and colleagues published in 2003 brought these issues to the forefront of clinical practice. Key papers that support or refute the practice of "permissive underfeeding" are reviewed. Further research is necessary to determine the minimum amount of nutrition required to achieve a therapeutic benefit as well as to ascertain at what amount of additional nutrition intake offers no further improvement in clinical outcome.

Providing nutrition to critically ill obese adults: use of the nursing process

Caring for obese critically ill patients is not always the same as caring for critically ill patients who are not obese. Fortunately, nurses have many resources available to them to guide them in this process. However, research that specifically addresses the needs of obese critically ill patients is still lacking in many areas and should be considered as potential areas to develop evidence-based practices.

Deadspace ventilation: a waste of breath!

Problems with ventilatory efficiency results in abnormal CO(2) clearance. Measuring deadspace ventilation should be the most reliable method of monitoring ventilatory efficiency in mechanically ventilated patients. Since its first description by Bohr in the late 19th century to the current use of single-breath test for volumetric CO(2), our understanding of the physiological deadspace has vastly improved. Yet indices of oxygenation seem to be the mainstay when instigating or fine-tuning ventilatory strategies. Deadspace and with it ventilatory efficiency has been largely forgotten. Recently though there has been a resurgence of interest in ventilatory efficiency. Several indices have been described that either predict deadspace or track ventilatory efficiency at the bedside. Thus making it more accessible and easy to monitor and study in large groups of patients, factors which have perhaps resulted in its under-utilisation in critical care. This review revisits the physiological concepts and methods of measuring deadspace. Described are the various clinical applications of deadspace measurements in the critically unwell. The potential reasons that have led to the variable being under-used are also examined. Finally we describe the indices currently available to track ventilatory efficiency at the bedside.

Published predictive equations overestimate measured resting metabolic rate in young, healthy females

OBJECTIVE

To compare resting metabolic rate (RMR) measured by indirect calorimetry versus RMR predicted by several published formulas in a sample of healthy young women.

METHODS

RMR was measured using indirect calorimetry and predicted using 6 commonly used equations (Nelson, 1992; Mifflin, 1990; Owen, 1986; Schofield(Weight), 1985; Schofield(Weight and Height), 1985; Harris-Benedict, 1919) in 47 reportedly healthy young females (age = 22.8 ± 2.9 years; body mass index = 21.8 ± 2.1 kg/m(2)). Comparisons between measured versus predicted RMR were conducted using paired t tests, and agreement using Pearson's correlation coefficient, analysis of variance, and the method of Bland-Altman.

RESULTS

All 6 equations overestimated measured RMR by 140-738 kcal/d (all p < 0.001). The proportion of subjects for whom measured versus predicted RMR differed by ±10% ranged from 74% (Nelson) to 100% (Harris-Benedict). The adjusted coefficients of determination (R(2)) between measured and predicted RMR ranged from 0.13 to 0.19 (all p < 0.05). Bland-Altman analysis R(2) values ranged from 0.03 (p = 0.233; Harris-Benedict) to 0.72 (p = 0.000; Owen). Given its continued popularity, we modified the Harris-Benedict equation (RMR(modified Harris-Benedict) (kcal/d) = 738 / (RMR(Harris-Benedict) - 738)). Doing so reduced the mean difference between measured and predicted RMR from +738 kcal/d to -0.53 kcal/d (p = 0.984).

CONCLUSION

No equation performed well, and none should be used interchangeably with measured RMR. We recommend that a new equation be validated for, and prospectively tested in, young women. In the interim, RMR should be measured in this population or predicted using the modified Harris-Benedict equation that we developed.

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.