Abstract
BackgroundCardiac elastances are highly invasive to measure directly, but are clinically useful due to the amount of information embedded in them. Information about the cardiac elastance, which can be used to estimate it, can be found in the downstream pressure waveforms of the aortic pressure (Pao) and the pulmonary artery (Ppa). However these pressure waveforms are typically noisy and biased, and require processing in order to locate the specific information required for cardiac elastance estimations. This paper presents the method to algorithmically process the pressure waveforms.MethodsA shear transform is developed in order to help locate information in the pressure waveforms. This transform turns difficult to locate corners into easy to locate maximum or minimum points as well as providing error correction.ResultsThe method located all points on 87 out of 88 waveforms for Ppa, to within the sampling frequency. For Pao, out of 616 total points, 605 were found within 1%, 5 within 5%, 4 within 10% and 2 within 20%.ConclusionsThe presented method provides a robust, accurate and dysfunction-independent way to locate points on the aortic and pulmonary artery pressure waveforms, allowing the non-invasive estimation of the left and right cardiac elastance.
Highlights
Cardiac elastances are highly invasive to measure directly, but are clinically useful due to the amount of information embedded in them
A brief overview of the whole method is given for clarity: 1. locate points on Pao and Ppa 2. correlate points of the pressure waveforms to points on the measured cardiac elastance 3. use these correlations to estimate the points on the cardiac elastance 4. create a continuous function e(t) through the estimated points with (2)-(4) 5. compare the estimated elastance waveform to the measured elastance waveform
The failure is due to the unusual second peak of Ppa, and the early decay of the Time-varying cardiac elastance (TVE)
Summary
Cardiac elastances are highly invasive to measure directly, but are clinically useful due to the amount of information embedded in them. A lot of data currently available to ICU clinicians, that could have significant clinical value, is under utilised Using modelling techniques, this limited set of data can be expanded to estimate a much greater set of clinically relevant data to enable more accurate diagnosis. Acute cardiovascular dysfunction, like pulmonary embolism (PE) and septic shock, severely alter cardiovascular system (CVS) hemodynamics around the heart These changes can be seen by catheter measurements as a change in the balance of preload and afterload, resulting in an altered cardiac energetic state [9,10]. If the relevant energetics could be captured from a nearby catheter, the clinical potential of such measurements could be realised To date, no such method achieves this aim
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
