ArticleJournal of the American Heart Association2025
Prognostic Significance of Computed Tomography-Derived Fractional Flow Reserve for Long-Term Outcomes in Individuals With Coronary Artery Disease.
Article in Journal of the American Heart Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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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
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Efficacy and safety of Shenqi Yangxin formula in patients with stable coronary artery disease based on CCTA: rationale, design, and study protocol for a randomized, double-blind, placebo-controlled study.Frontiers in cardiovascular medicine · 2026Article
- Serial Coronary CTA for Monitoring Response to Lipid-Lowering Therapy: A Narrative Review.Current atherosclerosis reports · 2025Review
- Coronary Computed Tomography Angiography-Derived Fractional Flow Reserve: A Comprehensive Review.Reviews in cardiovascular medicine · 2025Review
- Computed Tomography and Coronary Plaque Analysis.Tomography (Ann Arbor, Mich.) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundData on the predictive value of coronary computed tomography angiography-derived fractional flow reserve (CT-FFR) for long-term outcomes are limited. METHODS AND
resultsA retrospective pooled analysis of individual patient data was performed. Deep-learning-based CT-FFR was calculated. All patients enrolled were followed-up for at least 5 years. The primary outcome was major adverse cardiovascular events. The secondary outcome was death or nonfatal myocardial infarction. Predictive abilities for outcomes were compared among 3 models (model 1, constructed using clinical variables; model 2, model 1+coronary computed tomography angiography-derived anatomical parameters; and model 3, model 2+CT-FFR). A total of 2566 patients (median age, 60 [53-65] years; 56.0% men) with coronary artery disease were included. During a median follow-up time of 2197 (2127-2386) days, 237 patients (9.2%) experienced major adverse cardiovascular events. In multivariable-adjusted Cox models, CT-FFR≤0.80 (hazard ratio [HR], 5.05 [95% CI, 3.64-7.01];
conclusionsCT-FFR provides strong and incremental prognostic information for predicting long-term outcomes. The combined models incorporating CT-FFR exhibit modest improvement of prediction abilities, which may aid in risk stratification and decision-making.
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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.