ArticlePediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies2011
Energy imbalance and the risk of overfeeding in critically ill children.
Article in Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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32 citing papers in PubMed, 136 citations in OpenAlex.
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- Amino Acids as Metabokines in Hypercatabolic States: Rethinking Nutritional Protein-Based Strategies Beyond Caloric Support.Nutrients · 2026Review
- Respiratory quotient as an early predictor of length of stay after cardiac surgery: A prospective observational study.Asia Pacific journal of clinical nutrition · 2025Observational
- Quantity of Caloric Support After Pediatric Severe Traumatic Brain Injury: Description of Associated Outcomes in a Single Retrospective Center Cohort, 2010-2022.Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies · 2025Article
- Nutritional Intensive Support in a Pediatric Patient With Severe Traumatic Brain Injury: A Case Report.Clinical nutrition research · 2024Article
- An In-Depth Look at Nutrition Support and Adequacy for Critically Ill Children with Organ Dysfunction.Children (Basel, Switzerland) · 2024Article
- Advances in pediatric acute kidney injury pharmacology and nutrition: a report from the 26th Acute Disease Quality Initiative (ADQI) consensus conference.Pediatric nephrology (Berlin, Germany) · 2024Article
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- The Effect of Various, Everyday Practices on Glucose Levels in Critically Ill Children.Journal of diabetes science and technology · 2022Article
- A methodological and clinical approach to measured energy expenditure in the critically ill pediatric patient.Frontiers in pediatrics · 2022Review
- Nutritional Support for Pediatric Severe Traumatic Brain Injury.Frontiers in pediatrics · 2022Review
- Clinical Case Reports on the acceptability and tolerance of a High-Energy whey peptide-based Pediatric oral nutritional supplement in children aged over 12 months.Clinical case reports · 2021Article
- Nutritional survey in critically ill children: a single center study in China.Translational pediatrics · 2020Article
- A Comparative Analysis of Equations to Estimate Patient Energy Requirements Following Cardiopulmonary Bypass for Correction of Congenital Heart Disease.JPEN. Journal of parenteral and enteral nutrition · 2020Article
- What do we know about optimal nutritional strategies in children with pediatric acute respiratory distress syndrome?Annals of translational medicine · 2019Review
- Feeding modality is a barrier to adequate protein provision in children receiving continuous renal replacement therapy (CRRT).Pediatric nephrology (Berlin, Germany) · 2019Observational
- Nutrition Support and Tight Glucose Control in Critically Ill Children: Food for Thought!Frontiers in pediatrics · 2018Article
- The Metabolic Response to Stress and Infection in Critically Ill Children: The Opportunity of an Individualized Approach.Nutrients · 2017Review
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
objectiveTo examine the role of targeted indirect calorimetry in detecting the adequacy of energy intake and the risk of cumulative energy imbalance in a subgroup of critically ill children suspected to have alterations in resting energy expenditure. We examined the accuracy of standard equations used for estimating resting energy expenditure in relation to measured resting energy expenditure in relation to measured resting energy expenditure and cumulative energy balance over 1 week in this cohort.
designA prospective cohort study.
settingPediatric intensive care unit in a tertiary academic center.
interventionsA subgroup of critically ill children in the pediatric intensive care unit was selected using a set of criteria for targeted indirect calorimetry. MEASUREMENTS: Measured resting energy expenditure from indirect calorimetry and estimated resting energy expenditure from standard equations were obtained. The metabolic state of each patient was assigned as hypermetabolic (measured resting energy expenditure/estimated resting energy expenditure >110%), hypometabolic (measured resting energy expenditure/estimated resting energy expenditure <90%), or normal (measured resting energy expenditure/estimated resting energy expenditure = 90-110%). Clinical variables associated with metabolic state and factors influencing the adequacy of energy intake were examined. MAIN
resultsChildren identified by criteria for targeted indirect calorimetry, had a median length of stay of 44 days, a high incidence (72%) of metabolic instability and alterations in resting energy expenditure with a predominance of hypometabolism in those admitted to the medical service. Physicians failed to accurately predict the true metabolic state in a majority (62%) of patients. Standard equations overestimated the energy expenditure and a high incidence of overfeeding (83%) with cumulative energy excess of up to 8000 kcal/week was observed, especially in children <1 yr of age. We did not find a correlation between energy balance and respiratory quotient (RQ) in our study.
conclusionsWe detected a high incidence of overfeeding in a subgroup of critically ill children using targeted indirect calorimetry The predominance of hypometabolism, failure of physicians to correctly predict metabolic state, use of stress factors, and inaccuracy of standard equations all contributed to overfeeding in this cohort. Critically ill children, especially those with a longer stay in the PICU, are at a risk of unintended overfeeding with cumulative energy excess.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.