Evidence map›Paper›PMID 31799783›Full record

ArticleInternational journal for numerical methods in biomedical engineering2021

Personalising cardiovascular network models in pregnancy: A two-tiered parameter estimation approach.

Jason Carson, Lynne Warrander, Edward Johnstone, Raoul van Loon

Open access · hybridAbstract read
In one paragraph

Article in International journal for numerical methods in biomedical engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Inverse problems in blood flow modeling: A review.International journal for numerical methods in biomedical engineering · 2022
    Review
  8. Personalising cardiovascular network models in pregnancy: A two-tiered parameter estimation approach.International journal for numerical methods in biomedical engineering · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Jason CarsonZienkiewicz Centre for Computational Engineering, College of Engineering, Swansea University, Swansea, UK.ORCID 0000-0001-6634-9123
Lynne WarranderMaternal and Fetal Health Research Centre, Division of Developmental Biology, Faculty of Medicine Biology and Health, University of Manchester, Manchester, UK.ORCID 0000-0001-9529-8935
Edward JohnstoneMaternal and Fetal Health Research Centre, Division of Developmental Biology, Faculty of Medicine Biology and Health, University of Manchester, Manchester, UK.ORCID 0000-0001-9732-8544
Raoul van LoonZienkiewicz Centre for Computational Engineering, College of Engineering, Swansea University, Swansea, UK.ORCID 0000-0003-3581-5827
Manchester Academic Health Science Centre · GBSwansea University · GB

Funding

Medical Research Council MR/S004076/1Wellcome Trust
6 · The paper itself

Abstract

Uterine artery Doppler waveforms are often studied to determine whether a patient is at risk of developing pathologies such as pre-eclampsia. Many uterine waveform indices have been developed, which attempt to relate characteristics of the waveform with the physiological adaptation of the maternal cardiovascular system, and are often suggested to be an indicator of increased placenta resistance and arterial stiffness. Doppler waveforms of four patients, two of whom developed pre-eclampsia, are compared with a comprehensive closed-loop model of pregnancy. The closed-loop model has been previously validated but has been extended to include an improved parameter estimation technique that utilises systolic and diastolic blood pressure, cardiac output, heart rate, and pulse wave velocity measurements to adapt model resistances, compliances, blood volume, and the mean vessel areas in the main systemic arteries. The shape of the model-predicted uterine artery velocity waveforms showed good agreement with the characteristics observed in the patient Doppler waveforms. The personalised models obtained now allow a prediction of the uterine pressure waveforms in addition to the uterine velocity. This allows for a more detailed mechanistic analysis of the waveforms, eg, wave intensity analysis, to study existing clinical indices. The findings indicate that to accurately estimate arterial stiffness, both pulse pressure and pulse wave velocities are required. In addition, the results predict that patients who developed pre-eclampsia later in pregnancy have larger vessel areas in the main systemic arteries compared with the two patients who had normal pregnancy outcomes.

Indexed as

Pre-EclampsiaPulse Wave AnalysisArteriesBlood Flow VelocityFemaleHumansPregnancyUltrasonography, DopplerUterusparameter estimationpersonalised haemodynamic modelpre-eclampsiapregnancyuterine artery waveform

Identifiers

PMID31799783
PMCPMC9286682
OpenAlexW2991917471

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.