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Identification of cardiac afterload dynamics from data

Identification of cardiac afterload dynamics from data

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2507927891

Identification of cardiac afterload dynamics from data

About this item

Full title

Identification of cardiac afterload dynamics from data

Publisher

Cold Spring Harbor: Cold Spring Harbor Laboratory Press

Journal title

bioRxiv, 2021-04

Language

English

Formats

Publication information

Publisher

Cold Spring Harbor: Cold Spring Harbor Laboratory Press

More information

Scope and Contents

Contents

The prospect of ex vivo functional evaluation of donor hearts is considered. Particularly, the dynamics of a synthetic cardiac afterload model are compared to those of normal physiology. A method for identification of continuous-time transfer functions from sampled data is developed and verified against results from the literature. The method relies on exact gradients and Hessians obtained through automatic differentiation. This also enables straightforward sensitivity analyses. Such analyses reveal that the 4-element Windkessel model is not practically identifiable from representative data while the 3-element model underfits the data. Pressure–volume (PV) loops are therefore suggested as an alternative for comparing afterload dynamics. Competing Interest Statement The authors have declared no competing interest. Footnotes * https://github.com/hpigot/windkessel-id/releases/tag/v1.0...

Alternative Titles

Full title

Identification of cardiac afterload dynamics from data

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_journals_2507927891

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2507927891

Other Identifiers

E-ISSN

2692-8205

DOI

10.1101/2021.03.31.437920