TY - JOUR

T1 - Accuracy of a Clinical Applicable Method for Prediction of VO2max Using Seismocardiography

AU - Hansen, Mikkel Thunestvedt

AU - Husted, Karina Louise Skov

AU - Fogelstrøm, Mathilde

AU - Rømer, Tue

AU - Schmidt, Samuel Emil

AU - Sørensen, Kasper

AU - Helge, Jørn

N1 - Publisher Copyright: © 2022 Georg Thieme Verlag. All rights reserved.

PY - 2023

Y1 - 2023

N2 - Cardiorespiratory fitness measured as VO2max is considered an important variable in the risk prediction of cardiovascular disease and all-cause mortality. Non-exercise VO2max prediction models are applicable, but lack accuracy. Here a model for the prediction of VO2max using seismocardiography (SCG) was investigated. 97 healthy participants (18-65 yrs., 51 females) underwent measurement of SCG at rest in the supine position combined with demographic data to predict VO2max before performing a graded exercise test (GET) on a cycle ergometer for determination of VO2max using pulmonary gas exchange measurements for comparison. Accuracy assessment revealed no significant difference between SCG and GET VO2max (mean±95% CI; 38.3±1.6 and 39.3±1.6 ml·min -1·kg -1, respectively. P=0.075). Further, a Pearson correlation of r=0.73, a standard error of estimate (SEE) of 5.9 ml·min -1·kg -1, and a coefficient of variation (CV) of 8±1% were found. The SCG VO2max showed higher accuracy than the non-exercise model based on the FRIENDS study when this was applied to the present population (bias=-3.7±1.3 ml·min -1·kg -1, p<0.0001. r=0.70. SEE=7.4 ml·min-1·kg-1, and CV=12±2%). The SCG VO2max prediction model is an accurate method for the determination of VO2max in a healthy adult population. However, further investigation on the validity and reliability of the SCG VO2max prediction model in different populations is needed for consideration of clinical applicability.

AB - Cardiorespiratory fitness measured as VO2max is considered an important variable in the risk prediction of cardiovascular disease and all-cause mortality. Non-exercise VO2max prediction models are applicable, but lack accuracy. Here a model for the prediction of VO2max using seismocardiography (SCG) was investigated. 97 healthy participants (18-65 yrs., 51 females) underwent measurement of SCG at rest in the supine position combined with demographic data to predict VO2max before performing a graded exercise test (GET) on a cycle ergometer for determination of VO2max using pulmonary gas exchange measurements for comparison. Accuracy assessment revealed no significant difference between SCG and GET VO2max (mean±95% CI; 38.3±1.6 and 39.3±1.6 ml·min -1·kg -1, respectively. P=0.075). Further, a Pearson correlation of r=0.73, a standard error of estimate (SEE) of 5.9 ml·min -1·kg -1, and a coefficient of variation (CV) of 8±1% were found. The SCG VO2max showed higher accuracy than the non-exercise model based on the FRIENDS study when this was applied to the present population (bias=-3.7±1.3 ml·min -1·kg -1, p<0.0001. r=0.70. SEE=7.4 ml·min-1·kg-1, and CV=12±2%). The SCG VO2max prediction model is an accurate method for the determination of VO2max in a healthy adult population. However, further investigation on the validity and reliability of the SCG VO2max prediction model in different populations is needed for consideration of clinical applicability.

U2 - 10.1055/a-2004-4669

DO - 10.1055/a-2004-4669

M3 - Journal article

C2 - 36577438

AN - SCOPUS:85146638490

VL - 44

SP - 650

EP - 656

JO - International Journal of Sports Medicine

JF - International Journal of Sports Medicine

SN - 0172-4622

IS - 9

ER -