Predicting energy needs in ventilator-dependent critically ill patients: effect of adjusting weight for edema or adiposity

• Published in: The American journal of clinical nutrition 1997-11, Vol.66 (5), p.1250-1256
• Main Authors: Cutts, ME, Dowdy, RP, Ellersieck, MR, Edes, TE
• Format: Article
• Language: English
• Subjects: Adolescent; Adult; Aged; Aged, 80 and over; Basal Metabolism; Biological and medical sciences; Body Weight; Calorimetry, Indirect; Critical Care - methods; Edema - metabolism; Energy Intake; Energy Metabolism - physiology; Female; Fundamental and applied biological sciences. Psychology; Humans; Intermediate and energetic metabolism; Male; Metabolisms and neurohumoral controls; Middle Aged; Nutrition; Obesity; Obesity - metabolism; Patients; Predictive Value of Tests; Respiration, Artificial; Vertebrates: anatomy and physiology, studies on body, several organs or systems; Weight control
• ISSN: 0002-9165; 1938-3207
• DOI: 10.1093/ajcn/66.5.1250

Predicting energy needs in critical illness can be difficult because of uncertainties about the influence of multiple factors on energy expenditure. Understanding these components is important to avoid limiting optimal outcome by underfeeding and to avoid complications of overfeeding. Prediction strategies often use a patient’s weight to estimate needs. For overweight patients, there is controversy as to whether actual or modified weight should be used in predictions. This study was designed to evaluate a proposed technique to improve the accuracy of predicting energy needs in critically ill, overweight subjects. Subjects’ energy needs were predicted [with Harris-Benedict equation (HBE) and kilojoules per kilogram (KPK) strategies] by using both actual weight and an adjusted weight developed to attempt to more accurately reflect lean mass. Results were compared with measured energy expenditure determined by indirect calorimetry. Results indicated that use of actual weights in predictions for overweight subjects may lead to overfeeding. Use of adjusted weights led to more accurate energy predictions with the KPK than with the HBE strategy. Adjusted-weight strategies could explain > 45% of the variability of resting energy expenditure in subjects 130-159% of ideal body weight. Results of this study suggest that using adjusted weights with the KPK prediction strategy may be preferable for this population, particularly for patients > or = 130% of ideal body weight. This study also indicated that multiple diagnoses may not lead to increased energy requirements.