Accuracy of Formulas For Determing Energy Needs

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Journal of the American Dietetic Association. Volume

107, Issue 3, Pages 393-401 (March 2007)

Accurate Determination of Energy Needs in Hospitalized

Patients

ph Boullata, PharmD, , MS, RD,

Faith Cottrell, Hudson, MS, RD, Charlene

Compher, PhD, RD, FADA

Abstract

Objective

To evaluate the accuracy of seven predictive

equations, including the -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 -Benedict equation

when a factor of 1.1 was multiplied to the equation

(-Benedict 1.1), but only in 61% of all the

patients, with significant under- and overpredictions.

In the patients with obesity, the -Benedict

equation using actual weight was most accurate, but

only in 62% of patients; and in the critically ill

patients the -Benedict 1.1 was most accurate,

but only in 55% of patients. The bias was also lowest

with -Benedict 1.1 (mean error & #8722;9

kcal/day, range +403 to & #8722;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

-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.