ArticleComputer methods in applied mechanics and engineering2017
A Predictive Framework to Elucidate Venous Stenosis: CFD & Shape Optimization.
Article in Computer methods in applied mechanics and engineering, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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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.
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Who cites it
6 citing papers in PubMed, 13 citations in OpenAlex.
- Computational Frontiers in Arteriovenous Fistula Maturation: A Review of Fluid Dynamics and Machine Learning Models.Journal of the American Society of Nephrology : JASN · 2026Review
- Quantitative evaluation of computational fluid dynamics application development in the cardiovascular field through literature retrieval and bibliometric analysis.Biomedical engineering online · 2026Review
- Quantitative hemodynamics of draining veins in brain arteriovenous malformation: a preliminary study based on computational fluid dynamics.Frontiers in neurology · 2024Article
- Measuring the palpable pulsatility length as a physical examination test in defining the severity of inflow stenosis for hemodialysis fistulas.BMC nephrology · 2019Article
- Cerebral arteriovenous malformation venous stenosis is associated with hemodynamic changes at the draining vein-venous sinus junction.Medical hypotheses · 2019Article
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Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
The surgical creation of vascular accesses for renal failure patients provides an abnormally high flow rate conduit in the patient's upper arm vasculature that facilitates the hemodialysis treatment. These vascular accesses, however, are very often associated with complications that lead to access failure and thrombotic incidents, mainly due to excessive neointimal hyperplasia (NH) and subsequently stenosis. Development of a framework to monitor and predict the evolution of the venous system post access creation can greatly contribute to maintaining access patency. Computational fluid dynamics (CFD) has been exploited to inspect the non-homeostatic wall shear stress (WSS) distribution that is speculated to trigger NH in the patient cohort under investigation. Thereafter, CFD in liaison with a gradient-free shape optimization method has been employed to analyze the deformation modes of the venous system enduring non-physiological hemodynamics. It is observed that the optimally evolved shapes and their corresponding hemodynamics strive to restore the homeostatic state of the venous system to a normal, pre-surgery condition. It is concluded that a CFD-shape optimization coupling that seeks to regulate the WSS back to a well-defined physiological WSS target range can accurately predict the mode of patient-specific access failure.
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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 OpenQuestion graph.