ReviewInternational journal of molecular sciences2025
Residual Traditional Risk in Non-Traditional Atherosclerotic Diseases.
Review in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Prognostic value of lipoprotein(a) for cardiovascular events after lower limb revascularization in diabetic patients with chronic limb-threatening ischemia.Cardiovascular diabetology · 2025Observational
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
Individuals with chronic inflammatory and immune disorders are at an increased risk of atherosclerotic events and premature cardiovascular (CV) disease. Despite extensive literature exploring the relationship between "non-traditional" atherosclerotic conditions and CV risk, many aspects remain unresolved, including the underlying mechanisms promoting the "non-traditional CV risk", the development of an innovative and comprehensive CV risk assessment tool, and recommendations for tailored interventions. This review aims to evaluate the available evidence on key "non-traditional" CV risk-enhancer conditions, with a focus on assessing and managing CV risk factors. We conducted a comprehensive review of 412 original articles, narrative and systematic reviews, and meta-analyses addressing the CV risk associated with "non-traditional" atherosclerotic conditions. The analysis examined the underlying mechanisms of these relationships and identified strategies for assessing and mitigating elevated risk. A major challenge highlighted is the difficulty in quantifying the contribution of individual risk factors and disease-specific elements to CV risk. While evidence supports the cardiovascular benefits of statins beyond lipid lowering, such as pleiotropic and endothelial effects, current guidelines lack specific recommendations for the use of statins or other therapies targeting non-traditional CV risk factors. Additionally, the absence of validated cardiovascular risk scores that incorporate non-traditional risk factors hinders accurate CV risk evaluation and management. The growing prevalence of "non-traditional CV risk-enhancer conditions" underscores the need for improved awareness of CV risk assessment and management. A thorough understanding of all contributing factors, including disease-specific elements, is crucial for accurate prediction of cardiovascular disease (CVD) risk. This represents an essential foundation for informed decision-making in primary and secondary prevention. We advocate for future research to focus on developing innovative, disease-specific CV risk assessment tools that incorporate non-traditional risk factors, recognizing this as a promising avenue for translational and clinical outcome research.
Indexed as
Identifiers
What 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.