Predictive energy equations for spinal muscular atrophy type I children

Author:

Bertoli Simona12ORCID,De Amicis Ramona1ORCID,Bedogni Giorgio1ORCID,Foppiani Andrea1ORCID,Leone Alessandro1ORCID,Ravella Simone1ORCID,Mastella Chiara3,Baranello Giovanni45,Masson Riccardo5,Bertini Enrico6ORCID,D'Amico Adele6,Pedemonte Marina7,Bruno Claudio7,Agosto Caterina8,Giaquinto Ester9,Bassano Michela9,Battezzati Alberto1ORCID

Affiliation:

1. International Center for the Assessment of Nutritional Status (ICANS), Department of Food Environmental and Nutritional Sciences (DeFENS), University of Milan, Milan, Italy

2. Department of Endocrine and Metabolic Diseases, Obesity Unit and Laboratory of Nutrition and Obesity Research, IRCCS (Scientific Institute for Research, Hospitalization, and Healthcare) Italian Auxologic Institute (IAI), Milan, Italy

3. SAPRE (Early Habilitation Service), Child and Adolescent Neuropsychiatric Unit, IRCCS (Scientific Institute for Research, Hospitalization, and Healthcare) Ospedale Maggiore Policlinico Cà Granda Foundation, Milan, Italy

4. GOSH-UCL NIHR (Great Ormond Street Hospital, University College of London, National Institute for Health Research) Biomedical Research Centre, The Dubowitz Neuromuscular Centre, Great Ormond Street Institute of Child Health, London, United Kingdom

5. Developmental Neurology Unit, IRCCS (Scientific Institute for Research, Hospitalization, and Healthcare) Neurological Institute Carlo Besta Foundation, Milan, Italy

6. Department of Neurosciences, Neuromuscular and Neurodegenerative Disorders Unit, Laboratory of Molecular Medicine, IRCCS (Scientific Institute for Research, Hospitalization, and Healthcare) Bambino Gesù Children's Research Hospital, Rome Italy

7. Italian Department of Neurosciences and Rehabilitation, Institute “G. Gaslini,” Genoa, Italy

8. Department of Women's and Children's Health, University of Padua, Padua, Italy

9. M. Bufalini Hospital, Dietetic and Nutrition Unit, Cesena, Italy

Abstract

ABSTRACT Background Knowledge on resting energy expenditure (REE) in spinal muscular atrophy type I (SMAI) is still limited. The lack of a population-specific REE equation has led to poor nutritional support and impairment of nutritional status. Objective To identify the best predictors of measured REE (mREE) among simple bedside parameters, to include these predictors in population-specific equations, and to compare such models with the common predictive equations. Methods Demographic, clinical, anthropometric, and treatment variables were examined as potential predictors of mREE by indirect calorimetry (IC) in 122 SMAI children consecutively enrolled in an ongoing longitudinal observational study. Parameters predicting REE were identified, and prespecified linear regression models adjusted for nusinersen treatment (discrete: 0 = no; 1 = yes) were used to develop predictive equations, separately in spontaneously breathing and mechanically ventilated patients. Results In naïve patients, the median (25th, 75th percentile) mREE was 480 (412, 575) compared with 394 (281, 554) kcal/d in spontaneously breathing and mechanically ventilated patients, respectively (P = 0.009). In nusinersen-treated patients, the median (25th, 75th percentile) mREE was 609 (592, 702) compared with 639 (479, 723) kcal/d in spontaneously breathing and mechanically ventilated patients, respectively (P = 0.949). Both in spontaneously breathing and mechanically ventilated patients, the best prediction of REE was obtained from 3 models, all using as predictors: 1 body size related measurement and nusinersen treatment status. Nusinersen treatment was correlated with higher REE both in spontaneously breathing and mechanically ventilated patients. The population-specific equations showed a lower interindividual variability of the bias than the other equation tested, however, they showed a high root mean squared error. Conclusions We demonstrated that ventilatory status, nusinersen treatment, demographic, and anthropometric characteristics determine energy requirements in SMAI. Our SMAI-specific equations include variables available in clinical practice and were generally more accurate than previously published equations. At the individual level, however, IC is strongly recommended for assessing energy requirements. Further research is needed to externally validate these predictive equations.

Funder

Fondazione Telethon

Spinal Muscular Atrophy Families

Publisher

Oxford University Press (OUP)

Subject

Nutrition and Dietetics,Medicine (miscellaneous)

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