Reference Values of Aerobic Fitness in the Contemporary Paediatric Population (SAIN&NORMES)

October 24, 2023 updated by: University Hospital, Montpellier

Reference Values of Aerobic Fitness in the Contemporary Paediatric Population: VO2max Z-scores

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).

Study Overview

Status

Completed

Conditions

Detailed Description

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)

Study Type

Observational

Enrollment (Actual)

950

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

      • Montpellier, France, 34295
        • UH Montpellier

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

6 years to 17 years (Child)

Accepts Healthy Volunteers

Yes

Sampling Method

Non-Probability Sample

Study Population

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.

Description

Part 1 - Z-score equations:

Healthy children:

Inclusion criteria

  • Child from 6 to 17 years old having performed a cardio-respiratory exercise test for chest pain, dyspnea on exertion, heart murmur and whose results do not find:
  • congenital heart disease (normal echocardiography and ECG)
  • respiratory disease (normal FEV1 and FVC)
  • Child having performed a maximal cardio-respiratory stress exercise until exhaustion.

Exclusion criteria:

  • Child taking long-term drug treatment
  • Child with chronic disease
  • Parents' refusal to use medical data.

Obese children:

Inclusion criteria

  • Child with BMI>85e percentile
  • Child from 6 to 17 years old having performed a cardio-respiratory exercise test for checkup and whose results do not find:
  • congenital heart disease (normal echocardiography and ECG)
  • Child having performed a maximal cardio-respiratory stress exercise until exhaustion.

Exclusion criteria:

  • Child taking long-term drug treatment (except for their metabolic syndrome)
  • Child with chronic disease (except their metabolic syndrome)
  • Parents' refusal to use medical data.

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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Cohort
  • Time Perspectives: Retrospective

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
identify the parameters of an equation for calculating VO2max Z-scores
Time Frame: day 1
identify the parameters of an equation for calculating VO2max Z-scores (potentially using age, sex, height, weight or skin surface area)
day 1
estimate the parameters of an equation for calculating VO2max Z-scores
Time Frame: day 1
estimate the parameters of an equation for calculating VO2max Z-scores (potentially using age, sex, height, weight or skin surface area)
day 1

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
validity of the VO2max Z-score equations
Time Frame: day 1
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)
day 1
identify the parameters of an equation for calculating ventilatory anaerobic threshold Z-scores
Time Frame: 1 day
identify the parameters of an equation for calculating ventilatory anaerobic threshold Z-scores (potentially using age, sex, height, weight or skin surface area)
1 day
estimate the parameters of an equation for calculating ventilatory anaerobic threshold Z-scores
Time Frame: 1 day
estimate the parameters of an equation for calculating ventilatory anaerobic threshold Z-scores (potentially using age, sex, height, weight or skin surface area)
1 day
identify the parameters of an equation for calculating VE/VCO2 slope Z-scores
Time Frame: 1 day
identify the parameters of an equation for calculating VE/VCO2 slope Z-scores (potentially using age, sex, height, weight or skin surface area)
1 day
estimate the parameters of an equation for calculating VE/VCO2 slope Z-scores
Time Frame: 1 day
estimate the parameters of an equation for calculating VE/VCO2 slope Z-scores (potentially using age, sex, height, weight or skin surface area)
1 day
identify the parameters of an equation for calculating oxygen uptake efficiency slope Z-scores
Time Frame: 1 day
identify the parameters of an equation for calculating oxygen uptake efficiency slope Z-scores (potentially using age, sex, height, weight or skin surface area)
1 day
estimate the parameters of an equation for calculating oxygen uptake efficiency slope Z-scores
Time Frame: 1 day
estimate the parameters of an equation for calculating oxygen uptake efficiency slope Z-scores (potentially using age, sex, height, weight or skin surface area)
1 day
identify the parameters of an equation for calculating oxygen pulse Z-scores
Time Frame: 1 day
identify the parameters of an equation for calculating oxygen pulse Z-scores (potentially using age, sex, height, weight or skin surface area)
1 day
estimate the parameters of an equation for calculating oxygen pulse Z-scores
Time Frame: 1 day
estimate the parameters of an equation for calculating oxygen pulse Z-scores (potentially using age, sex, height, weight or skin surface area)
1 day
identify the parameters of an equation for calculating maximal respiratory frequency Z-scores
Time Frame: 1 day
identify the parameters of an equation for calculating maximal respiratory frequency Z-scores (potentially using age, sex, height, weight or skin surface area)
1 day
stimate the parameters of an equation for calculating maximal respiratory frequency Z-scores
Time Frame: 1 day
estimate the parameters of an equation for calculating maximal respiratory frequency Z-scores (potentially using age, sex, height, weight or skin surface area)
1 day
identify the parameters of an equation for calculating maximal maximal tidal volume Z-scores
Time Frame: 1 day
identify the parameters of an equation for calculating maximal maximal tidal volume Z-scores (potentially using age, sex, height, weight or skin surface area)
1 day
estimate the parameters of an equation for calculating maximal maximal tidal volume Z-scores
Time Frame: 1 day
estimate the parameters of an equation for calculating maximal maximal tidal volume Z-scores (potentially using age, sex, height, weight or skin surface area)
1 day
identify the parameters of an equation for calculating breath reserve Z-scores
Time Frame: 1 day
identify the parameters of an equation for calculating breath reserve Z-scores (potentially using age, sex, height, weight or skin surface area)
1 day
estimate the parameters of an equation for calculating breath reserve Z-scores
Time Frame: 1 day
estimate the parameters of an equation for calculating breath reserve Z-scores (potentially using age, sex, height, weight or skin surface area)
1 day
estimate the parameters of an equation for calculating maximal pet end tidal CO2 Z-scores
Time Frame: 1 day
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)
1 day
identify the parameters of an equation for calculating maximal pet end tidal CO2 Z-scores
Time Frame: 1 day
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)
1 day

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Arthur GAVOTTO, MD, University Hospital, Montpellier
  • Study Director: Pascal AMEDRO, MD, PhD, University Hospital, Montpellier

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

November 1, 2019

Primary Completion (Actual)

January 1, 2021

Study Completion (Actual)

May 1, 2021

Study Registration Dates

First Submitted

May 2, 2021

First Submitted That Met QC Criteria

May 2, 2021

First Posted (Actual)

May 6, 2021

Study Record Updates

Last Update Posted (Actual)

October 27, 2023

Last Update Submitted That Met QC Criteria

October 24, 2023

Last Verified

October 1, 2023

More Information

Terms related to this study

Other Study ID Numbers

  • RECHMPL19_0475

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

IPD Plan Description

NC

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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