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Cardiodynamic variables measured by impedance cardiography during a 6-minute walk test are reliable predictors of peak oxygen consumption in young healthy adults
Accurate prediction of aerobic capacity is necessary to guide appropriate exercise prescription. It is common to use 6-minute walk distance (6MWD) to predict peak oxygen uptake (VO(2peak)) in the clinical environment. The aim of this study was to determine whether prediction of VO(2peak) can be impr...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8148309/ https://www.ncbi.nlm.nih.gov/pubmed/34032813 http://dx.doi.org/10.1371/journal.pone.0252219 |
Sumario: | Accurate prediction of aerobic capacity is necessary to guide appropriate exercise prescription. It is common to use 6-minute walk distance (6MWD) to predict peak oxygen uptake (VO(2peak)) in the clinical environment. The aim of this study was to determine whether prediction of VO(2peak) can be improved by the inclusion of cardiovascular indices derived by impedance cardiography (ICG) during the 6MWT. A total of 62 healthy university students aged 21±1 years completed in separate days, a cardiopulmonary exercise test (CPET) and two 6MWTs (30 min apart), during which heart rate (HR), stroke volume (SV) and cardiac output (CO) were measured by ICG (PhysioFlow(®) PF07 Enduro(TM)). The CPET was conducted with the Ergoselect 200 Ergoline and oxygen consumption measured by a MasterScreen(TM) CPX breath-by-breath metabolic cart. Multiple regression analyses were conducted to generate VO(2peak) prediction equations using 6MWD with, or without the cardiovascular indices recorded at the end of the best performed 6MWT as predictor variables. The mean peak HR (bpm), SV (ml) and CO (L/min) recorded during 6MWT were 156±18, 95.6±9, 15±2.8 and during CPET were 176±16, 91.3±8, 16.2±2.7, respectively. Analyses revealed the following VO(2peak) prediction equation: VO(2peak) = 100.297+(0.019x6MWD)+(-0.598xHR(6MWT))+(-1.236xSV(6MWT)) + (8.671 x CO(6MWT)). This equation has a squared multiple correlation (R(2)) of 0.866, standard error of the estimate (SEE) of 2.28 mL/kg/min and SEE:VO(2peak) (SEE%) of 7.2%. Cross-validation of equation stability using predicted residual sum of squares (PRESS) statistics showed a R(2) (R(p)(2)), SEE (SEE(p)) and SEE(p)% of 0.842, 2.38 mL/kg/min and 7.6% respectively. The minimal shrinkage of R(2) implied regression model stability. Correlation between measured and predicted VO(2peak) using this equation was strong (r = 0.931, p<0.001). When 6MWD alone was used as the predictor for VO(2peak), the generated equation had a lower R(2) (0.549), and a higher SEE (4.08 mL/kg/min) and SEE% (12.9%). This is the first study which included cardiac indices during a 6MWT as variables for VO(2peak) prediction. Our results suggest that inclusion of cardiac indices measured during the 6MWT more accurately predicts VO(2peak) than using 6MWD data alone. |
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