Evidence map›Paper›PMID 31469943›Full record

ArticleInternational journal for numerical methods in biomedical engineering2019

Computational instantaneous wave-free ratio (IFR) for patient-specific coronary artery stenoses using 1D network models.

Jason M Carson, Carl Roobottom, Robin Alcock, Perumal Nithiarasu

Abstract read
In one paragraph

Article in International journal for numerical methods in biomedical engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
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

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3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Artificial intelligence approaches to predict coronary stenosis severity using non-invasive fractional flow reserve.Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine · 2020
    Article
  10. Article
  11. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Jason M CarsonZienkiewicz Centre for Computational Engineering, College of Engineering, Swansea University, Swansea, UK.ORCID 0000-0001-6634-9123
Carl RoobottomDerriford Hospital and Peninsula Medical School, Plymouth Hospitals NHS Trust, Plymouth, UK.
Robin AlcockDerriford Hospital and Peninsula Medical School, Plymouth Hospitals NHS Trust, Plymouth, UK.
Perumal NithiarasuZienkiewicz Centre for Computational Engineering, College of Engineering, Swansea University, Swansea, UK.

Funding

British Heart FoundationChief Scientist OfficeDepartment of HealthMedical Research Council MR/S004076/1Wellcome Trust
6 · The paper itself

Abstract

In this work, we estimate the diagnostic threshold of the instantaneous wave-free ratio (iFR) through the use of a one-dimensional haemodynamic framework. To this end, we first compared the computed fractional flow reserve (cFFR) predicted from a 1D computational framework with invasive clinical measurements. The framework shows excellent promise and utilises minimal patient data from a cohort of 52 patients with a total of 66 stenoses. The diagnostic accuracy of the cFFR model was 75.76%, with a sensitivity of 71.43%, a specificity of 77.78%, a positive predictive value of 60%, and a negative predictive value of 85.37%. The validated model was then used to estimate the diagnostic threshold of iFR. The model determined a quadratic relationship between cFFR and the ciFR. The iFR diagnostic threshold was determined to be 0.8910 from a receiver operating characteristic curve that is in the range of 0.89 to 0.9 that is normally reported in clinical studies.

Indexed as

Fractional Flow Reserve, MyocardialModels, CardiovascularArea Under CurveBlood PressureCoronary AngiographyCoronary StenosisHemodynamicsHumansMonte Carlo MethodRetrospective StudiesROC Curvecoronary arteriesFFRhaemodynamic modellingiFR

Identifiers

PMID31469943
PMCPMC7003475

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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.