ReviewCurrent atherosclerosis reports2025
Incidental Finding of Coronary and Non-Coronary Artery Calcium: What Do Clinicians Need To Know?
Review in Current atherosclerosis reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 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
2 citing papers in PubMed.
- Artificial intelligence risk stratification from dynamic digital subtraction angiography radiomics predicts pulmonary embolism and associates with clinical outcomes in deep vein thrombosis: A retrospective cohort study.Journal of vascular surgery. Venous and lymphatic disorders · 2026Article
- Artificial Intelligence for Detecting Aortic Arch Calcification on Chest Radiographs: A Systematic Review.Diagnostics (Basel, Switzerland) · 2026Review
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purpose of reviewThis review summarizes the role of incidentally and non-incidentally discovered coronary artery calcification (CAC) and the evolving role of non-coronary artery calcification in atherosclerotic cardiovascular disease (ASCVD) risk assessment. Additionally, this review explores the emerging use of artificial intelligence (AI), machine learning (ML), radiomics, and natural language processing (NLP) for automated detection, quantification, and communication of these incidentally discovered findings. RECENT
findingsThis review summarizes recent findings in the space, including the development of various AI/ML-based approaches for automated calcification quantification and detection. Recent work leverages the use of incidentally discovered CAC and non-coronary calcification (e.g. aortic valve, aortic arch, carotid artery, breast arterial calcification) and their influence on clinical decision-making and prescribing practices. CAC and various forms of non-coronary artery calcifications are increasingly recognized as powerful and additive predictors of ASCVD risk. Advances in AI, ML, and radiomics enable scalable, automated measurement of both incidental and non-incidental CAC and non-coronary calcifications, which will facilitate more precise, personalized ASCVD risk stratification.
Indexed as
Identifiers
40650862What 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.