Determination of Maximal Oxygen Uptake Using Seismocardiography at Rest

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Introduction: Assessment of maximal oxygen consumption (VO2max) is an important clinical tool when examining both healthy and unhealthy populations, as a low VO2max is associated with cardiovascular disease and all-cause mortality. Aim: This study investigated the accuracy of a non-exercise test for assessment of VO2max using seismocardiography (SCG). Methods: 97 participants (20-45 years, 50 males) underwent a nonexercise test using SCG at rest in the supine position (SCG VO2max) and a graded exercise test to voluntary exhaustion on a cycle ergometer with indirect calorimetry (IC VO2max). An interim analysis was applied after 50 participants had completed testing (SCG VO2max 1.0) allowing for the algorithm to be modified (SCG VO2max 2.1). Results: SCG VO2max 2.1 (n=47, test set) estimation was 3.5 pm 1.8 mlcdot min{-1}cdot kg{-1} (p < 0.001) lower compared to IC VO2max, with a Pearson correlation of r=0.65 (p < 0.0001) and a standard error of estimate of 7.1 ml·min-1 ·kg-1. The coefficient of variation between tests was 8 pm 1%. Conclusion: The accuracy of VO2max assessment using SCG requires further optimization prior to clinical application, as SCG VO2max was systematically lower than IC VO2max, and only a moderate correlation together with considerable variation were observed between tests.

OriginalsprogEngelsk
Titel2021 Computing in Cardiology (CinC)
Vol/bind48
ForlagIEEE Press
Publikationsdato2021
DOI
StatusUdgivet - 2021
Begivenhed2021 Computing in Cardiology, CinC 2021 - Brno, Tjekkiet
Varighed: 13 sep. 202115 sep. 2021

Konference

Konference2021 Computing in Cardiology, CinC 2021
LandTjekkiet
ByBrno
Periode13/09/202115/09/2021
NavnComputing in Cardiology
Vol/bind48
ISSN2325-8861

Bibliografisk note

Funding Information:
The study was financially supported by VentriJect A/S with no restriction on publication. SES and KS holds

Publisher Copyright:
© 2021 Creative Commons.

ID: 334310774