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A 45-Second Self-Test for Cardiorespiratory Fitness : Heart Rate-Based Estimation in Healthy Individuals. / Sartor, Francesco; Bonato, Matteo; Papini, Gabriele; Bosio, Andrea; Mohammed, Rahil A.; Bonomi, Alberto G.; Moore, Jonathan; Merati, Giampiero; La Torre, Antonio; Kubis, Hans-Peter.

In: PLoS ONE, Vol. 11, No. 12, e0168154, 13.12.2016.

Research output: Contribution to journalArticle

HarvardHarvard

Sartor, F, Bonato, M, Papini, G, Bosio, A, Mohammed, RA, Bonomi, AG, Moore, J, Merati, G, La Torre, A & Kubis, H-P 2016, 'A 45-Second Self-Test for Cardiorespiratory Fitness: Heart Rate-Based Estimation in Healthy Individuals', PLoS ONE, vol. 11, no. 12, e0168154. https://doi.org/10.1371/journal.pone.0168154

APA

Sartor, F., Bonato, M., Papini, G., Bosio, A., Mohammed, R. A., Bonomi, A. G., ... Kubis, H-P. (2016). A 45-Second Self-Test for Cardiorespiratory Fitness: Heart Rate-Based Estimation in Healthy Individuals. PLoS ONE, 11(12), [e0168154]. https://doi.org/10.1371/journal.pone.0168154

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MLA

VancouverVancouver

Sartor F, Bonato M, Papini G, Bosio A, Mohammed RA, Bonomi AG et al. A 45-Second Self-Test for Cardiorespiratory Fitness: Heart Rate-Based Estimation in Healthy Individuals. PLoS ONE. 2016 Dec 13;11(12). e0168154. https://doi.org/10.1371/journal.pone.0168154

Author

Sartor, Francesco ; Bonato, Matteo ; Papini, Gabriele ; Bosio, Andrea ; Mohammed, Rahil A. ; Bonomi, Alberto G. ; Moore, Jonathan ; Merati, Giampiero ; La Torre, Antonio ; Kubis, Hans-Peter. / A 45-Second Self-Test for Cardiorespiratory Fitness : Heart Rate-Based Estimation in Healthy Individuals. In: PLoS ONE. 2016 ; Vol. 11, No. 12.

RIS

TY - JOUR

T1 - A 45-Second Self-Test for Cardiorespiratory Fitness

T2 - PLoS ONE

AU - Sartor, Francesco

AU - Bonato, Matteo

AU - Papini, Gabriele

AU - Bosio, Andrea

AU - Mohammed, Rahil A.

AU - Bonomi, Alberto G.

AU - Moore, Jonathan

AU - Merati, Giampiero

AU - La Torre, Antonio

AU - Kubis, Hans-Peter

PY - 2016/12/13

Y1 - 2016/12/13

N2 - Cardio-respiratory fitness (CRF) is a widespread essential indicator in Sports Science as well as in Sports Medicine. This study aimed to develop and validate a prediction model for CRF based on a 45 second self-test, which can be conducted anywhere. Criterion validity, test re-test study was set up to accomplish our objectives. Data from 81 healthy volunteers (age: 29 ± 8 years, BMI: 24.0 ± 2.9), 18 of whom females, were used to validate this test against gold standard. Nineteen volunteers repeated this test twice in order to evaluate its repeatability. CRF estimation models were developed using heart rate (HR) features extracted from the resting, exercise, and the recovery phase. The most predictive HR feature was the intercept of the linear equation fitting the HR values during the recovery phase normalized for the height2 (r2 = 0.30). The Ruffier-Dickson Index (RDI), which was originally developed for this squat test, showed a negative significant correlation with CRF (r = -0.40), but explained only 15% of the variability in CRF. A multivariate model based on RDI and sex, age and height increased the explained variability up to 53% with a cross validation (CV) error of 0.532 L ∙ min-1 and substantial repeatability (ICC = 0.91). The best predictive multivariate model made use of the linear intercept of HR at the beginning of the recovery normalized for height2 and age2; this had an adjusted r2 = 0. 59, a CV error of 0.495 L·min-1 and substantial repeatability (ICC = 0.93). It also had a higher agreement in classifying CRF levels (κ = 0.42) than RDI-based model (κ = 0.29). In conclusion, this simple 45 s self-test can be used to estimate and classify CRF in healthy individuals with moderate accuracy and large repeatability when HR recovery features are included

AB - Cardio-respiratory fitness (CRF) is a widespread essential indicator in Sports Science as well as in Sports Medicine. This study aimed to develop and validate a prediction model for CRF based on a 45 second self-test, which can be conducted anywhere. Criterion validity, test re-test study was set up to accomplish our objectives. Data from 81 healthy volunteers (age: 29 ± 8 years, BMI: 24.0 ± 2.9), 18 of whom females, were used to validate this test against gold standard. Nineteen volunteers repeated this test twice in order to evaluate its repeatability. CRF estimation models were developed using heart rate (HR) features extracted from the resting, exercise, and the recovery phase. The most predictive HR feature was the intercept of the linear equation fitting the HR values during the recovery phase normalized for the height2 (r2 = 0.30). The Ruffier-Dickson Index (RDI), which was originally developed for this squat test, showed a negative significant correlation with CRF (r = -0.40), but explained only 15% of the variability in CRF. A multivariate model based on RDI and sex, age and height increased the explained variability up to 53% with a cross validation (CV) error of 0.532 L ∙ min-1 and substantial repeatability (ICC = 0.91). The best predictive multivariate model made use of the linear intercept of HR at the beginning of the recovery normalized for height2 and age2; this had an adjusted r2 = 0. 59, a CV error of 0.495 L·min-1 and substantial repeatability (ICC = 0.93). It also had a higher agreement in classifying CRF levels (κ = 0.42) than RDI-based model (κ = 0.29). In conclusion, this simple 45 s self-test can be used to estimate and classify CRF in healthy individuals with moderate accuracy and large repeatability when HR recovery features are included

U2 - 10.1371/journal.pone.0168154

DO - 10.1371/journal.pone.0168154

M3 - Article

VL - 11

JO - PLoS ONE

JF - PLoS ONE

SN - 1932-6203

IS - 12

M1 - e0168154

ER -