Evidence mapPaperPMID 39654943Full record

ReviewFrontiers in cardiovascular medicine2024

Coronary angiography: a review of the state of the art and the evolution of angiography in cardio therapeutics.

Aishwarya Gurav, Pruthvi C Revaiah, Tsung-Ying Tsai, Kotaro Miyashita, Akihiro Tobe, Asahi Oshima, Emelyne Sevestre, Scot Garg, Jean-Paul Aben, Johan H C Reiber and 9 more

Abstract readReview
In one paragraph

Review in Frontiers in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

19 authors.

Aishwarya Gurav *CORRIB Research Centre for Advanced Imaging and Core Laboratory, University of Galway, Galway, Ireland.
Pruthvi C Revaiah *CORRIB Research Centre for Advanced Imaging and Core Laboratory, University of Galway, Galway, Ireland.
Tsung-Ying TsaiCORRIB Research Centre for Advanced Imaging and Core Laboratory, University of Galway, Galway, Ireland.
Kotaro MiyashitaCORRIB Research Centre for Advanced Imaging and Core Laboratory, University of Galway, Galway, Ireland.
Akihiro TobeCORRIB Research Centre for Advanced Imaging and Core Laboratory, University of Galway, Galway, Ireland.
Asahi OshimaCORRIB Research Centre for Advanced Imaging and Core Laboratory, University of Galway, Galway, Ireland.
Emelyne SevestreCORRIB Research Centre for Advanced Imaging and Core Laboratory, University of Galway, Galway, Ireland.
Scot GargDepartment of Cardiology, Royal Blackburn Hospital, Blackburn, United Kingdom.
Jean-Paul AbenPie Medical Imaging BV, Maastricht, Netherlands.
Johan H C ReiberDepartment of Radiology, Leiden University Medical Center, Leiden, Netherlands.
Marie Angele MorelCORRIB Research Centre for Advanced Imaging and Core Laboratory, University of Galway, Galway, Ireland.
Cheol Whan LeeDivision of Cardiology, Department of Internal Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Bon-Kwon KooDepartment of Internal Medicine and Cardiovascular Center, Seoul National University Hospital, Seoul, Republic of Korea.
Simone BiscagliaCardiology Unit, Azienda Ospedaliero Universitaria di Ferrara, Ferrara, Italy.
Carlos ColletCardiovascular Center Aalst, OLV Clinic, Aalst, Belgium.
Christos BourantasDepartment of Cardiology, Barts Heart Center, Barts Health NHS Trust, London, United Kingdom.
Javier EscanedHospital Clínico San Carlos IDISSC, Complutense University of Madrid and CIBER-CV, Madrid, Spain.
Yoshinobu OnumaCORRIB Research Centre for Advanced Imaging and Core Laboratory, University of Galway, Galway, Ireland.
Patrick W SerruysCORRIB Research Centre for Advanced Imaging and Core Laboratory, University of Galway, Galway, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditionally, coronary angiography was restricted to visual estimation of contrast-filled lumen in coronary obstructive diseases. Over the previous decades, considerable development has been made in quantitatively analyzing coronary angiography, significantly improving its accuracy and reproducibility.  Notably, the integration of artificial intelligence (AI) and machine learning into quantitative coronary angiography (QCA) holds promise for further enhancing diagnostic accuracy and predictive capabilities. In addition, non-invasive fractional flow reserve (FFR) indices, including computed tomography-FFR, have emerged as valuable tools, offering precise physiological assessment of coronary artery disease without the need for invasive procedures. These innovations allow for a more comprehensive evaluation of disease severity and aid in guiding revascularization decisions. This review traces the development of QCA technologies over the years, highlighting key milestones and current advancements. It also explores prospects that could revolutionize the field, such as AI integration and improved imaging techniques. By addressing both historical context and future directions, the article underscores the ongoing evolution of QCA and its critical role in the accurate assessment and management of coronary artery diseases. Through continuous innovation, QCA is poised to remain at the forefront of cardiovascular diagnostics, offering clinicians invaluable tools for improving patient care.

Indexed as

angiography-based fractional flow reservecomputed tomography coronary angiographycoronary angiographypercutaneous coronary interventionpullback pressure gradientwall shear stress (WSS)

Identifiers

PMID39654943
PMCPMC11625592

What Socratic holds

Textmetadata
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.