Literature DB >> 29692203

A new generalized cycle ergometry equation for predicting maximal oxygen uptake: The Fitness Registry and the Importance of Exercise National Database (FRIEND).

Peter Kokkinos1,2,3,4, Leonard A Kaminsky5, Ross Arena6, Jiajia Zhang7, Jonathan Myers8,9.   

Abstract

Background To develop a clinically applicable equation derived from direct assessment of maximal oxygen uptake (VO2max) to predict VO2max assessed indirectly during cycle ergometry. Design VO2max was assessed by open-circuit spirometry during a graded maximal exercise test using cycle ergometry. Multivariable linear regression analysis was applied to identify the most relevant variables and construct the best prediction model for VO2max using a random sample of 70% from each of the following age categories: <40, 40-50, 50-70 and >70 years; the remaining 30% was used for validation. Work rate (Watts*6.12/kg of body weight) and gender were considered in the final regression model as predictors of measured VO2max and the resulting equation was compared to the traditional American College of Sports Medicine (ACSM) equation. Methods Participants were part of the Fitness Registry and the Importance of Exercise National Database (FRIEND), a multi-institutional initiative with the primary objective of establishing normative VO2max values across the adult lifespan. The final cohort consisted of 5100 (3378 men; mean age 35.9 ± 12.1 years and 1722 women; mean age 47.5 ± 14.0 years). Results The following equation was generated: VO2max in ml O2·kg-1·min-1 = 1.74* (Watts*6.12/kg of body weight) + 3.5. The derived FRIEND-ergometry equation predicted VO2max with an overall relative bias of 0.51% ± 0.11 compared to a 15.46% ± 0.13 associated with the traditional ACSM equations ( P < 0.001). This predictive value was independent of gender, race, cardiac risk factors and cardiac, antihypertensive, metabolic and/or lipid-lowering medication. Conclusion The FRIEND-ergometry equation is considerably more precise than the traditional ACSM equation with an overall error over 30 times lower than that associated with the ACSM equation.

Entities:  

Keywords:  FRIEND database; VO2max prediction; ergometry equation

Mesh:

Year:  2018        PMID: 29692203     DOI: 10.1177/2047487318772667

Source DB:  PubMed          Journal:  Eur J Prev Cardiol        ISSN: 2047-4873            Impact factor:   7.804


  12 in total

1.  Fitness and Body Mass Index During Adolescence and Disability Later in Life: A Cohort Study.

Authors:  Pontus Henriksson; Hanna Henriksson; Per Tynelius; Daniel Berglind; Marie Löf; I-Min Lee; Eric J Shiroma; Francisco B Ortega
Journal:  Ann Intern Med       Date:  2019-02-12       Impact factor: 25.391

2.  Age-Related Differences for Cardiorespiratory Fitness Improvement in Patients Undergoing Cardiac Rehabilitation.

Authors:  Jenna L Taylor; Jose R Medina-Inojosa; Audry Chacin-Suarez; Joshua R Smith; Ray W Squires; Randal J Thomas; Bruce D Johnson; Thomas P Olson; Amanda R Bonikowske
Journal:  Front Cardiovasc Med       Date:  2022-04-14

3.  Impact of unhealthy lifestyle on cardiorespiratory fitness and heart rate recovery of medical science students.

Authors:  Lampson M Fan; Adam Collins; Li Geng; Jian-Mei Li
Journal:  BMC Public Health       Date:  2020-06-26       Impact factor: 3.295

4.  Birth Weight and Cardiorespiratory Fitness Among Young Men Born at Term: The Role of Genetic and Environmental Factors.

Authors:  Viktor H Ahlqvist; Margareta Persson; Francisco B Ortega; Per Tynelius; Cecilia Magnusson; Daniel Berglind
Journal:  J Am Heart Assoc       Date:  2020-01-31       Impact factor: 5.501

5.  Reference values for maximum oxygen uptake relative to body mass in Dutch/Flemish subjects aged 6-65 years: the LowLands Fitness Registry.

Authors:  Geertje E van der Steeg; Tim Takken
Journal:  Eur J Appl Physiol       Date:  2021-02-01       Impact factor: 3.078

6.  Cardiodynamic variables measured by impedance cardiography during a 6-minute walk test are reliable predictors of peak oxygen consumption in young healthy adults.

Authors:  Fang Liu; Raymond C C Tsang; Alice Y M Jones; Mingchao Zhou; Kaiwen Xue; Miaoling Chen; Yulong Wang
Journal:  PLoS One       Date:  2021-05-25       Impact factor: 3.240

7.  Submaximal Exercise Testing in Cardiovascular Rehabilitation Settings (BEST Study).

Authors:  Jennifer L Reed; Lisa M Cotie; Christie A Cole; Jennifer Harris; Bruce Moran; Kyle Scott; Tasuku Terada; John P Buckley; Andrew L Pipe
Journal:  Front Physiol       Date:  2020-01-08       Impact factor: 4.566

8.  Monitoring functional capacity in heart failure.

Authors:  Massimo F Piepoli; Ilaria Spoletini; Giuseppe Rosano
Journal:  Eur Heart J Suppl       Date:  2019-12-31       Impact factor: 1.803

9.  Predictors for one-year outcomes of cardiorespiratory fitness and cardiovascular risk factor control after cardiac rehabilitation in elderly patients: The EU-CaRE study.

Authors:  Prisca Eser; Thimo Marcin; Eva Prescott; Leonie F Prins; Evelien Kolkman; Wendy Bruins; Astrid E van der Velde; Carlos Peña Gil; Marie-Christine Iliou; Diego Ardissino; Uwe Zeymer; Esther P Meindersma; Arnoud W J Van'tHof; Ed P de Kluiver; Matthias Wilhelm
Journal:  PLoS One       Date:  2021-08-05       Impact factor: 3.752

10.  Cardiorespiratory fitness assessment using risk-stratified exercise testing and dose-response relationships with disease outcomes.

Authors:  Tomas I Gonzales; Kate Westgate; Tessa Strain; Stefanie Hollidge; Justin Jeon; Dirk L Christensen; Jorgen Jensen; Nicholas J Wareham; Søren Brage
Journal:  Sci Rep       Date:  2021-07-28       Impact factor: 4.379

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