Valeria Calcaterra1,2, Giacomo Biganzoli3, Gloria Pelizzo4,5, Hellas Cena6,7, Alessandra Rizzuto3, Francesca Penagini2, Elvira Verduci2,8, Alessandra Bosetti2, Daniela Lucini9, Elia Biganzoli10, Gian Vincenzo Zuccotti2,5. 1. Pediatric and Adolescent Unit, Department of Internal Medicine, University of Pavia, 27100 Pavia, Italy. 2. Pediatric Department, "V. Buzzi" Children's Hospital, 20154 Milan, Italy. 3. Pharmacogenomics & Precision Therapeutics Master Degree, University of Milan, 20142 Milan, Italy. 4. Pediatric Surgery Unit, "V. Buzzi" Children's Hospital, University of Milan, 20154 Milan, Italy. 5. Department of Biomedical and Clinical Science "L. Sacco", University of Milan, 20157 Milan, Italy. 6. Laboratory of Dietetics and Clinical Nutrition, Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, Italy. 7. Clinical Nutrition and Dietetics Service, Unit of Internal Medicine and Endocrinology, ICS Maugeri IRCCS, 27100 Pavia, Italy. 8. Department of Health Sciences, University of Milan, 20146 Milan, Italy. 9. Department of Medical Biotechnologies and Translational Medicine, University of Milan, 20133 Milan, Italy. 10. Department of Clinical Sciences and Community Health & DSRC, University of Milan, 20122 Milan, Italy.
Abstract
BACKGROUND: The prevalence of pediatric metabolic syndrome is usually closely linked to overweight and obesity; however, this condition has also been described in children with disabilities. We performed a multivariate pattern analysis of metabolic profiles in neurologically impaired children and adolescents in order to reveal patterns and crucial biomarkers among highly interrelated variables. PATIENTS AND METHODS: We retrospectively reviewed 44 cases of patients (25M/19F, mean age 12.9 ± 8.0) with severe disabilities. Clinical and anthropometric parameters, body composition, blood pressure, and metabolic and endocrinological assessment (fasting blood glucose, insulin, total cholesterol, high-density lipoprotein cholesterol, triglycerides, glutamic oxaloacetic transaminase, glutamate pyruvate transaminase, gamma-glutamyl transpeptidase) were recorded in all patients. As a control group, we evaluated 120 healthy children and adolescents (61M/59F, mean age 12.9 ± 2.7). RESULTS: In the univariate analysis, the children-with-disabilities group showed a more dispersed distribution, thus with higher variability of the features related to glucose metabolism and insulin resistance (IR) compared to the healthy controls. The principal component (PC1), which emerged from the PC analysis conducted on the merged dataset and characterized by these variables, was crucial in describing the differences between the children-with-disabilities group and controls. CONCLUSION: Children and adolescents with disabilities displayed a different metabolic profile compared to controls. Metabolic syndrome (MetS), particularly glucose metabolism and IR, is a crucial point to consider in the treatment and care of this fragile pediatric population. Early detection of the interrelated variables and intervention on these modifiable risk factors for metabolic disturbances play a central role in pediatric health and life expectancy in patients with a severe disability.
BACKGROUND: The prevalence of pediatric metabolic syndrome is usually closely linked to overweight and obesity; however, this condition has also been described in children with disabilities. We performed a multivariate pattern analysis of metabolic profiles in neurologically impaired children and adolescents in order to reveal patterns and crucial biomarkers among highly interrelated variables. PATIENTS AND METHODS: We retrospectively reviewed 44 cases of patients (25M/19F, mean age 12.9 ± 8.0) with severe disabilities. Clinical and anthropometric parameters, body composition, blood pressure, and metabolic and endocrinological assessment (fasting blood glucose, insulin, total cholesterol, high-density lipoprotein cholesterol, triglycerides, glutamic oxaloacetic transaminase, glutamate pyruvate transaminase, gamma-glutamyl transpeptidase) were recorded in all patients. As a control group, we evaluated 120 healthy children and adolescents (61M/59F, mean age 12.9 ± 2.7). RESULTS: In the univariate analysis, the children-with-disabilities group showed a more dispersed distribution, thus with higher variability of the features related to glucose metabolism and insulin resistance (IR) compared to the healthy controls. The principal component (PC1), which emerged from the PC analysis conducted on the merged dataset and characterized by these variables, was crucial in describing the differences between the children-with-disabilities group and controls. CONCLUSION:Children and adolescents with disabilities displayed a different metabolic profile compared to controls. Metabolic syndrome (MetS), particularly glucose metabolism and IR, is a crucial point to consider in the treatment and care of this fragile pediatric population. Early detection of the interrelated variables and intervention on these modifiable risk factors for metabolic disturbances play a central role in pediatric health and life expectancy in patients with a severe disability.
Authors: G Biganzoli; D Dilillo; E Biganzoli; G Zuccotti; V Calcaterra; S Mannarino; L Fiori; G Pelizzo; E Zoia; V Fabiano; P Carlucci; A Camporesi; C Corti; G Mercurio; F Izzo Journal: J Endocrinol Invest Date: 2021-07-26 Impact factor: 4.256