An observational study in Healthy and Obese, sponsored by University Hospital, Montpellier. Completed at 1 site in France. Open to participants aged 6 Years to 17 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2023-10-27.
Sponsored by University Hospital, Montpellier · Observational
In most pediatric medical conditions, tremendous progress in pediatrics has significantly improved the overall prognosis and transferred the mortality from childhood to adulthood. Nevertheless, chronic diseases remain the leading cause of death and physical inactivity appears to be a major aggravating factor. Yet, a good physical activity has a positive impact on quality of life and prevents future health morbidities, such as obesity and cardiovascular disease. Therefore, after focusing on the survival of children with chronic diseases, more attention is being given to health-related quality of life and secondary prevention.
In this context, the cardio-pulmonary exercise test (CPET), which is a non-invasive and dynamic examination, has become the gold standard to identify subjects with impaired physical capacity and to identify the causes of their limitations (muscular, cardiac, respiratory, behavioral, etc.). Moreover, CPET is the key examination to enroll patients in personalized physical rehabilitation programs (muscle deconditioning, respiratory limitation, etc.).
Despite a growing interest in CPET and individualized rehabilitation programs for chronic diseases, the investigators still face the lack of reference values for pediatric CPET. In current practice, many CPET pediatric laboratories use the reference values of maximum oxygen uptake (VO2max) defined by Cooper et al. in 1984, from a cohort of 109 healthy children. However, their equations are linear and based on weight only. Non linear equations and the use of other anthropometric variables may be relevant in pediatrics. For instance, in the current era, normal CPET pediatric values should consider the prevalence of overweight and obesity in childhood general population (respectively 30% and 10% in Europa and 35% and 25% in North America), as well as in the population of children with chronic disease.
In the past decade, our group has developed a research program on physical capacity in children, with a focus on pediatric CPET and physical rehabilitation, from a cohort of nearly 1000 exercise tests in children. The lack of reliable pediatric reference values for VO2max, and all CPET variables as well, has become an important issue.
In this study, the investigators aim to define pediatric reference CPET values from a large cohort of 6 to 17 year-old children, using several anthropometric variables to define the most appropriate Z-scores equations (part 1). The investigators will also validate the Z-scores equations using an independent population (part 2).
This cross-sectional study included healthy children from 6 to 17 years old and obese children with no other comorbidities other than those due to metabolic syndrome (hypertension, dyslipidemia, type 2 diabetes sleep apnea, hepatic steatosis). Patients refuse the use of medical data will be excluded.
Part 1 - Z-score equations: After description of the study sample, the regression method will be identified (linear, polynomial, logarithmic, spline, etc.). The main anthropometric determinants (age, gender, height, weight, BMI) will be tested, and the mathematical models that best fit to the data will be identified (use of the adjusted coefficient of determination R2). The models will calculate, for each subject, the difference between the value predicted by the model and the value actually observed (residuals of the model). The occurrence of heteroscedasticity (e.g. the circumstance in which the variability of a variable is unequal across the range of values of a second variable that predicts it) will be tested. The Z-scores will be measured by the difference between predicted values and observed values divided by the calculated standard deviation.
Part 2- Validation of Z-score equations from an independent population The validity of the Z-score equations will be tested on a cohort of 100 pediatric in 6 to 18 year-old children, from pediatric CPET laboratories that did not participate in the part 1 study. The CPET variables may be retrospectively collected from existing database or prospectively collected, but no CPET should be performed for the only purpose of the research (observational study)
6,570 studies on the registry are indexed under Obesity; 1,718 are open to participants now.
This study's enrollment of 950 is above the median of 132 across 1,338 observational studies indexed under Obesity.
Browse Obesity studies →University Hospital, Montpellier is the lead sponsor of 1,261 studies on the registry; 227 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Healthy children cohort consisted of children referred to a paediatric cardiologist for a nonsevere functional symptom related to exercise (murmur, palpitation, chest pain, and dyspnoea) or for a medical sports certificate. Obese children cohort consisted of children with BMI > 85e percentile referred to a paediatric cardiologist for checkup.
Part 1 - Z-score equations:
Healthy children:
Inclusion criteria
Exclusion criteria:
Obese children:
Inclusion criteria
Exclusion criteria:
Part 2 : Validation of Z-score equations from an independent population The same criteria will be used for the patients of the Munich center and the Boston center to test our equations
identify the parameters of an equation for calculating VO2max Z-scores
identify the parameters of an equation for calculating VO2max Z-scores (potentially using age, sex, height, weight or skin surface area)
Time frame: day 1
estimate the parameters of an equation for calculating VO2max Z-scores
estimate the parameters of an equation for calculating VO2max Z-scores (potentially using age, sex, height, weight or skin surface area)
Time frame: day 1
validity of the VO2max Z-score equations
validity of the VO2max Z-score equations will be tested from cohort from pediatric CPET laboratories that did not participate in the part 1 study. To analyze this, we will compare the difference between the measured VO2max and the VO2max predicted by the Wassermann equation (Wassermann's predicted value - observed value) and the difference between the measured VO2max and the VO2max predicted by our equation (Gavotto's predicted value - observed value)
Time frame: day 1
identify the parameters of an equation for calculating ventilatory anaerobic threshold Z-scores
identify the parameters of an equation for calculating ventilatory anaerobic threshold Z-scores (potentially using age, sex, height, weight or skin surface area)
Time frame: 1 day
estimate the parameters of an equation for calculating ventilatory anaerobic threshold Z-scores
estimate the parameters of an equation for calculating ventilatory anaerobic threshold Z-scores (potentially using age, sex, height, weight or skin surface area)
Time frame: 1 day
identify the parameters of an equation for calculating VE/VCO2 slope Z-scores
identify the parameters of an equation for calculating VE/VCO2 slope Z-scores (potentially using age, sex, height, weight or skin surface area)
Time frame: 1 day
estimate the parameters of an equation for calculating VE/VCO2 slope Z-scores
estimate the parameters of an equation for calculating VE/VCO2 slope Z-scores (potentially using age, sex, height, weight or skin surface area)
Time frame: 1 day
identify the parameters of an equation for calculating oxygen uptake efficiency slope Z-scores
identify the parameters of an equation for calculating oxygen uptake efficiency slope Z-scores (potentially using age, sex, height, weight or skin surface area)
Time frame: 1 day
estimate the parameters of an equation for calculating oxygen uptake efficiency slope Z-scores
estimate the parameters of an equation for calculating oxygen uptake efficiency slope Z-scores (potentially using age, sex, height, weight or skin surface area)
Time frame: 1 day
identify the parameters of an equation for calculating oxygen pulse Z-scores
identify the parameters of an equation for calculating oxygen pulse Z-scores (potentially using age, sex, height, weight or skin surface area)
Time frame: 1 day
estimate the parameters of an equation for calculating oxygen pulse Z-scores
estimate the parameters of an equation for calculating oxygen pulse Z-scores (potentially using age, sex, height, weight or skin surface area)
Time frame: 1 day
identify the parameters of an equation for calculating maximal respiratory frequency Z-scores
identify the parameters of an equation for calculating maximal respiratory frequency Z-scores (potentially using age, sex, height, weight or skin surface area)
Time frame: 1 day
stimate the parameters of an equation for calculating maximal respiratory frequency Z-scores
estimate the parameters of an equation for calculating maximal respiratory frequency Z-scores (potentially using age, sex, height, weight or skin surface area)
Time frame: 1 day
identify the parameters of an equation for calculating maximal maximal tidal volume Z-scores
identify the parameters of an equation for calculating maximal maximal tidal volume Z-scores (potentially using age, sex, height, weight or skin surface area)
Time frame: 1 day
estimate the parameters of an equation for calculating maximal maximal tidal volume Z-scores
estimate the parameters of an equation for calculating maximal maximal tidal volume Z-scores (potentially using age, sex, height, weight or skin surface area)
Time frame: 1 day
identify the parameters of an equation for calculating breath reserve Z-scores
identify the parameters of an equation for calculating breath reserve Z-scores (potentially using age, sex, height, weight or skin surface area)
Time frame: 1 day
estimate the parameters of an equation for calculating breath reserve Z-scores
estimate the parameters of an equation for calculating breath reserve Z-scores (potentially using age, sex, height, weight or skin surface area)
Time frame: 1 day
estimate the parameters of an equation for calculating maximal pet end tidal CO2 Z-scores
estimate the parameters of an equation for calculating maximal pet end tidal CO2 Z-scores (potentially using age, sex, height, weight or skin surface area)
Time frame: 1 day
identify the parameters of an equation for calculating maximal pet end tidal CO2 Z-scores
identify the parameters of an equation for calculating maximal pet end tidal CO2 Z-scores (potentially using age, sex, height, weight or skin surface area)
Time frame: 1 day
Plan to share: Undecided — NC
Ran from Nov 2019 to primary completion in Jan 2021, 14 months.
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