Development of non-invasive biomarkers for pre-eclampsia through data-driven cardiovascular network models.

ABSTRACT: Computational models can be at the basis of new powerful technologies for studying and classifying disorders like pre-eclampsia, where it is difficult to distinguish pre-eclamptic patients from non-pre-eclamptic based on pressure when patients have a track record of hypertension. Computational models now enable a detailed analysis of how pregnancy affects the cardiovascular system. Therefore, new non-invasive biomarkers were developed that can aid the classification of pre-eclampsia through the integration of six different measured non-invasive cardiovascular signals. Datasets of 21 pregnant women (no early onset pre-eclampsia, n = 12; early onset pre-eclampsia, n = 9) were used to create personalised cardiovascular models through computational modelling resulting in predictions of blood p

SUBMITTER: Popp C 

PROVIDER: S-EPMC11452701 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature