Evidence map›Paper›PMID 37719972›Full record

ArticleFrontiers in cardiovascular medicine2023

Computational fluid dynamics as supporting technology for coronary artery disease diagnosis and treatment: an international survey.

Claudio Chiastra, Marco Zuin, Gianluca Rigatelli, Fabrizio D'Ascenzo, Gaetano Maria De Ferrari, Carlos Collet, Yiannis S Chatzizisis, Diego Gallo, Umberto Morbiducci

Abstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
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

9 authors.

Claudio Chiastra *PoliToBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy.
Marco Zuin *Department of Translational Medicine, University of Ferrara, Ferrara, Italy.
Gianluca Rigatelli *Interventional Cardiology Unit, Department of Cardiology, Madre Teresa Hospital, Padova, Italy.
Fabrizio D'AscenzoDivision of Cardiology, Department of Medical Sciences, Città Della Salute e Della Scienza Hospital, Turin, Italy.
Gaetano Maria De FerrariDivision of Cardiology, Department of Medical Sciences, Città Della Salute e Della Scienza Hospital, Turin, Italy.
Carlos ColletCardiovascular Center of Aalst, Aalst, Belgium.
Yiannis S ChatzizisisDivision of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, United States.
Diego GalloPoliToBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy.
Umberto MorbiducciPoliToBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Computational fluid dynamics (CFD) is emerging as an effective technology able to improve procedural outcomes and enhance clinical decision-making in patients with coronary artery disease (CAD). The present study aims to assess the state of knowledge, use and clinical acceptability of CFD in the diagnosis and treatment of CAD. Methods: We realized a 20-questions international, anonymous, cross-sectional survey to cardiologists to test their knowledge and confidence on CFD as a technology applied to patients suffering from CAD. Responses were recorded between May 18, 2022, and June 12, 2022. Results: A total of 466 interventional cardiologists (mean age 48.4 ± 8.3 years, males 362), from 42 different countries completed the survey, for a response rate of 45.9%. Of these, 66.6% declared to be familiar with the term CFD, especially for optimization of existing interventional techniques (16.1%) and assessment of hemodynamic quantities related with CAD (13.7%). About 30% of respondents correctly answered to the questions exploring their knowledge on the pathophysiological role of some CFD-derived quantities such as wall shear stress and helical flow in coronary arteries. Among respondents, 85.9% would consider patient-specific CFD-based analysis in daily interventional practice while 94.2% declared to be interested in receiving a brief foundation course on the basic CFD principles. Finally, 87.7% of respondents declared to be interested in a cath-lab software able to conduct affordable CFD-based analyses at the point-of-care. Conclusions: Interventional cardiologists reported to be profoundly interested in adopting CFD simulations as a technology supporting decision making in the treatment of CAD in daily practice.

Indexed as

computational fluid dynamicscoronary artery diseasehelical flowhemodynamicsmodeling and simulationprecision medicinetechnologywall shear stress

Identifiers

PMID37719972
PMCPMC10501454

What Socratic holds

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LicenceCC BY
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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 Socratic graph.