↓ Skip to main content

Improved pressure contour analysis for estimating cardiac stroke volume using pulse wave velocity measurement

Overview of attention for article published in BioMedical Engineering OnLine, April 2017
Altmetric Badge

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
18 Dimensions

Readers on

mendeley
34 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Improved pressure contour analysis for estimating cardiac stroke volume using pulse wave velocity measurement
Published in
BioMedical Engineering OnLine, April 2017
DOI 10.1186/s12938-017-0341-z
Pubmed ID
Authors

Shun Kamoi, Christopher Pretty, Joel Balmer, Shaun Davidson, Antoine Pironet, Thomas Desaive, Geoffrey M. Shaw, J. Geoffrey Chase

Abstract

Pressure contour analysis is commonly used to estimate cardiac performance for patients suffering from cardiovascular dysfunction in the intensive care unit. However, the existing techniques for continuous estimation of stroke volume (SV) from pressure measurement can be unreliable during hemodynamic instability, which is inevitable for patients requiring significant treatment. For this reason, pressure contour methods must be improved to capture changes in vascular properties and thus provide accurate conversion from pressure to flow. This paper presents a novel pressure contour method utilizing pulse wave velocity (PWV) measurement to capture vascular properties. A three-element Windkessel model combined with the reservoir-wave concept are used to decompose the pressure contour into components related to storage and flow. The model parameters are identified beat-to-beat from the water-hammer equation using measured PWV, wave component of the pressure, and an estimate of subject-specific aortic dimension. SV is then calculated by converting pressure to flow using identified model parameters. The accuracy of this novel method is investigated using data from porcine experiments (N = 4 Pietrain pigs, 20-24.5 kg), where hemodynamic properties were significantly altered using dobutamine, fluid administration, and mechanical ventilation. In the experiment, left ventricular volume was measured using admittance catheter, and aortic pressure waveforms were measured at two locations, the aortic arch and abdominal aorta. Bland-Altman analysis comparing gold-standard SV measured by the admittance catheter and estimated SV from the novel method showed average limits of agreement of ±26% across significant hemodynamic alterations. This result shows the method is capable of estimating clinically acceptable absolute SV values according to Critchely and Critchely. The novel pressure contour method presented can accurately estimate and track SV even when hemodynamic properties are significantly altered. Integrating PWV measurements into pressure contour analysis improves identification of beat-to-beat changes in Windkessel model parameters, and thus, provides accurate estimate of blood flow from measured pressure contour. The method has great potential for overcoming weaknesses associated with current pressure contour methods for estimating SV.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 18%
Researcher 5 15%
Student > Bachelor 3 9%
Other 3 9%
Student > Doctoral Student 2 6%
Other 7 21%
Unknown 8 24%
Readers by discipline Count As %
Engineering 8 24%
Medicine and Dentistry 8 24%
Business, Management and Accounting 3 9%
Agricultural and Biological Sciences 1 3%
Unspecified 1 3%
Other 2 6%
Unknown 11 32%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 July 2017.
All research outputs
#10,133,047
of 11,419,765 outputs
Outputs from BioMedical Engineering OnLine
#427
of 515 outputs
Outputs of similar age
#218,615
of 260,536 outputs
Outputs of similar age from BioMedical Engineering OnLine
#15
of 16 outputs
Altmetric has tracked 11,419,765 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 515 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 260,536 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.