Artificial Intelligence-based Prediction of Radio-cephalic Arteriovenous Fistula Maturation Using Preoperative Duplex Examination

Brief summary (registry, in English)

The goal of this observational study is to assess the efficacy of AI-driven models in analyzing comprehensive ultrasonographic variables across multiple forearm locations to predict successful AVF maturation. The main question it aims to answer is: Can AI-driven models analyzing comprehensive ultrasonographic variables accurately predict the successful maturation of arteriovenous fistulas (AVFs)? Participants who underwent radiocephalic arteriovenous fistula (AVF) creation had their preoperative ultrasonographic data analyzed using AI-driven models to predict successful AVF maturation over a four-year retrospective period.

What you commit to

• Study type: Observational
• Participants enrolled: 494
• From 1 Jan 2018 to the primary completion date, 31 Dec 2022
• 1 site in 1 country
• Visits and tests: ask the trial team, the registry does not list them

Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.

Who cannot take part

Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.

Who the study is looking for

Sex: All

Full criteria on ClinicalTrials.gov

Sites (1)

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