Corinne Jotterand Chaparro1, Patrick Taffé2, Clémence Moullet3, Jocelyne Laure Depeyre3, David Longchamp4, Marie-Hélène Perez4, Jacques Cotting5. 1. Department of Nutrition and Dietetics, School of Health Professions, University of Applied Sciences Western Switzerland, Geneva 1227, Switzerland; Pediatric Intensive Care Unit, Medico-Surgical Department of Pediatrics, University Hospital of Lausanne, Lausanne 1011, Switzerland. 2. Institute of Social and Preventive Medicine, Lausanne 1010, Switzerland. 3. Department of Nutrition and Dietetics, School of Health Professions, University of Applied Sciences Western Switzerland, Geneva 1227, Switzerland. 4. Pediatric Intensive Care Unit, Medico-Surgical Department of Pediatrics, University Hospital of Lausanne, Lausanne 1011, Switzerland. 5. Pediatric Intensive Care Unit, Medico-Surgical Department of Pediatrics, University Hospital of Lausanne, Lausanne 1011, Switzerland. Electronic address: jacques.cotting@chuv.ch.
Abstract
OBJECTIVE: To determine, based on indirect calorimetry measurements, the biases of predictive equations specifically developed recently for estimating resting energy expenditure (REE) in ventilated critically ill children, or developed for healthy populations but used in critically ill children. STUDY DESIGN: A secondary analysis study was performed using our data on REE measured in a previous prospective study on protein and energy needs in pediatric intensive care unit. We included 75 ventilated critically ill children (median age, 21 months) in whom 407 indirect calorimetry measurements were performed. Fifteen predictive equations were used to estimate REE: the equations of White, Meyer, Mehta, Schofield, Henry, the World Health Organization, Fleisch, and Harris-Benedict and the tables of Talbot. Their differential and proportional biases (with 95% CIs) were computed and the bias plotted in graphs. The Bland-Altman method was also used. RESULTS: Most equations underestimated and overestimated REE between 200 and 1000 kcal/day. The equations of Mehta, Schofield, and Henry and the tables of Talbot had a bias ≤10%, but the 95% CI was large and contained values by far beyond ±10% for low REE values. Other specific equations for critically ill children had even wider biases. CONCLUSIONS: In ventilated critically ill children, none of the predictive equations tested met the performance criteria for the entire range of REE between 200 and 1000 kcal/day. Even the equations with the smallest bias may entail a risk of underfeeding or overfeeding, especially in the youngest children. Indirect calorimetry measurement must be preferred.
OBJECTIVE: To determine, based on indirect calorimetry measurements, the biases of predictive equations specifically developed recently for estimating resting energy expenditure (REE) in ventilated critically ill children, or developed for healthy populations but used in critically ill children. STUDY DESIGN: A secondary analysis study was performed using our data on REE measured in a previous prospective study on protein and energy needs in pediatric intensive care unit. We included 75 ventilated critically ill children (median age, 21 months) in whom 407 indirect calorimetry measurements were performed. Fifteen predictive equations were used to estimate REE: the equations of White, Meyer, Mehta, Schofield, Henry, the World Health Organization, Fleisch, and Harris-Benedict and the tables of Talbot. Their differential and proportional biases (with 95% CIs) were computed and the bias plotted in graphs. The Bland-Altman method was also used. RESULTS: Most equations underestimated and overestimated REE between 200 and 1000 kcal/day. The equations of Mehta, Schofield, and Henry and the tables of Talbot had a bias ≤10%, but the 95% CI was large and contained values by far beyond ±10% for low REE values. Other specific equations for critically ill children had even wider biases. CONCLUSIONS: In ventilated critically ill children, none of the predictive equations tested met the performance criteria for the entire range of REE between 200 and 1000 kcal/day. Even the equations with the smallest bias may entail a risk of underfeeding or overfeeding, especially in the youngest children. Indirect calorimetry measurement must be preferred.
Authors: Lyvonne N Tume; Anna Bickerdike; Lynne Latten; Simon Davies; Madeleine H Lefèvre; Gaëlle W Nicolas; Frédéric V Valla Journal: Eur J Pediatr Date: 2017-09-18 Impact factor: 3.183