A systematic review of prediction models on arteriovenous fistula: Risk scores and machine learning approaches.
Journal:
The journal of vascular access
Published Date:
Apr 24, 2024
Abstract
OBJECTIVE: Failure-to-mature and early stenosis remains the Achille's heel of hemodialysis arteriovenous fistula (AVF) creation. The maturation and patency of an AVF can be influenced by a variety of demographic, comorbidity, and anatomical factors. This study aims to review the prediction models of AVF maturation and patency with various risk scores and machine learning models.
Authors
Keywords
Aged
Arteriovenous Shunt, Surgical
Clinical Decision-Making
Decision Support Techniques
Female
Graft Occlusion, Vascular
Humans
Machine Learning
Male
Middle Aged
Predictive Value of Tests
Renal Dialysis
Reproducibility of Results
Risk Assessment
Risk Factors
Time Factors
Treatment Outcome
Vascular Patency