ArticleBiomedical engineering online2017
Minimally invasive, patient specific, beat-by-beat estimation of left ventricular time varying elastance.
Article in Biomedical engineering online, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Article
- Shortening the thick filament by partial deletion of titin's C-zone alters cardiac function by reducing the operating sarcomere length range.Journal of molecular and cellular cardiology · 2022Article
- A guide for assessment of myocardial stiffness in health and disease.Nature cardiovascular research · 2022Review
- Blood pressure waveform contour analysis for assessing peripheral resistance changes in sepsis.Biomedical engineering online · 2018Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe aim of this paper was to establish a minimally invasive method for deriving the left ventricular time varying elastance (TVE) curve beat-by-beat, the monitoring of which's inter-beat evolution could add significant new data and insight to improve diagnosis and treatment. The method developed uses the clinically available inputs of aortic pressure, heart rate and baseline end-systolic volume (via echocardiography) to determine the outputs of left ventricular pressure, volume and dead space volume, and thus the TVE curve. This approach avoids directly assuming the shape of the TVE curve, allowing more effective capture of intra- and inter-patient variability.
resultsThe resulting TVE curve was experimentally validated against the TVE curve as derived from experimentally measured left ventricular pressure and volume in animal models, a data set encompassing 46,318 heartbeats across 5 Piétrain pigs. This simulated TVE curve was able to effectively approximate the measured TVE curve, with an overall median absolute error of 11.4% and overall median signed error of -2.5%.
conclusionsThe use of clinically available inputs means there is potential for real-time implementation of the method at the patient bedside. Thus the method could be used to provide additional, patient specific information on intra- and inter-beat variation in heart function.
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