Ioana Cretu
A comparison of different methods to maximise signal extraction when using central venous pressure to optimise atrioventricular delay after cardiac surgery.
Cretu, Ioana; Tindale, Alexander; Abbod, Maysam; Balachandran, Wamadeva; Khir, Ashraf W; Meng, Hongying
Authors
Alexander Tindale
Maysam Abbod
Wamadeva Balachandran
Professor Ashraf Khir ashraf.w.khir@durham.ac.uk
Professor
Hongying Meng
Abstract
Our group has shown that central venous pressure (CVP) can optimise atrioventricular (AV) delay in temporary pacing (TP) after cardiac surgery. However, the signal-to-noise ratio (SNR) is influenced both by the methods used to mitigate the pressure effects of respiration and the number of heartbeats analysed. This paper systematically studies the effect of different analysis methods on SNR to maximise the accuracy of this technique. We optimised AV delay in 16 patients with TP after cardiac surgery. Transitioning rapidly and repeatedly from a reference AV delay to different tested AV delays, we measured pressure differences before and after each transition. We analysed the resultant signals in different ways with the aim of maximising the SNR: (1) adjusting averaging window location (around versus after transition), (2) modifying window length (heartbeats analysed), and (3) applying different signal filtering methods to correct respiratory artefact. (1) The SNR was 27 % higher for averaging windows around the transition versus post-transition windows. (2) The optimal window length for CVP analysis was two respiratory cycle lengths versus one respiratory cycle length for optimising SNR for arterial blood pressure (ABP) signals. (3) Filtering with discrete wavelet transform improved SNR by 62 % for CVP measurements. When applying the optimal window length and filtering techniques, the correlation between ABP and CVP peak optima exceeded that of a single cycle length (R = 0.71 vs. R = 0.50, p < 0.001). We demonstrated that utilising a specific set of techniques maximises the signal-to-noise ratio and hence the utility of this technique. [Abstract copyright: © 2024 The Author(s).]
Citation
Cretu, I., Tindale, A., Abbod, M., Balachandran, W., Khir, A. W., & Meng, H. (2024). A comparison of different methods to maximise signal extraction when using central venous pressure to optimise atrioventricular delay after cardiac surgery. International Journal of Cardiology, 51, Article 101382. https://doi.org/10.1016/j.ijcha.2024.101382
Journal Article Type | Article |
---|---|
Acceptance Date | Mar 5, 2024 |
Online Publication Date | Mar 12, 2024 |
Publication Date | 2024-04 |
Deposit Date | May 16, 2024 |
Publicly Available Date | May 16, 2024 |
Journal | International journal of cardiology. Heart & vasculature |
Print ISSN | 0167-5273 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 51 |
Article Number | 101382 |
DOI | https://doi.org/10.1016/j.ijcha.2024.101382 |
Keywords | Atrioventricular delay, Temporary pacing, CVP, Filtering, Optimisation, CRT |
Public URL | https://durham-repository.worktribe.com/output/2378609 |
Files
Published Journal Article
(5.8 Mb)
PDF
Licence
http://creativecommons.org/licenses/by/4.0/
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
Copyright Statement
© 2024 The Author(s).
Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
You might also like
Manufacturing an Artificial Arterial Tree Using 3D printing
(2024)
Journal Article
Arterial pulse wave modeling and analysis for vascular-age studies: a review from VascAgeNet
(2023)
Journal Article
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search