ReviewHerz2017
[Computed tomography in patients with chronic stable angina : Fractional flow reserve measurement].
Review in Herz, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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.
Who cites it
8 citing papers in PubMed.
- [Morphological and functional diagnostics of coronary artery disease by computed tomography].Herz · 2023Review
- Review
- Review
- Correlation of machine learning computed tomography-based fractional flow reserve with instantaneous wave free ratio to detect hemodynamically significant coronary stenosis.Clinical research in cardiology : official journal of the German Cardiac Society · 2020Article
- Comparison of Machine Learning Computed Tomography-Based Fractional Flow Reserve and Coronary CT Angiography-Derived Plaque Characteristics with Invasive Resting Full-Cycle Ratio.Journal of clinical medicine · 2020Article
- Percutaneous Coronary Intervention in Stable Coronary Heart Disease -Is Less More?Deutsches Arzteblatt international · 2020Review
- Cardiac CT: why, when, and how : Update 2019.Der Radiologe · 2019Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Coronary computed tomography angiography (cCTA) has been established for the non-invasive diagnosis of coronary artery disease (CAD). Previous studies demonstrated the high diagnostic accuracy of cCTA, particularly for ruling out CAD. As a known limitation of cCTA a large number of visually significant coronary stenoses are found to be hemodynamically not relevant by invasive fractional flow reserve (FFR). CT-based FFR (CT-FFR) builds on recent advances in computational fluid dynamics and image simulation techniques. Along with CT myocardial perfusion imaging, CT-FFR is a promising approach towards a more accurate estimation of the hemodynamic relevance of coronary artery stenoses. CT-FFR is derived from regular CT datasets without additional image acquisitions, contrast material, or medication. Two CT-FFR techniques can be differentiated. The initial method requires external use of supercomputers and has gained approval for clinical use in the USA. Furthermore, a prototype-software has been introduced which is less computationally demanding via integration of reduced-order models for on-site calculation of CT-FFR. The present article reviews these methods in the context of available study results and meta-analyses. Furthermore, limitations and future concepts of CT-FFR are discussed.
Indexed as
Identifiers
27255115What Socratic holds
Registered trials
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.