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

NCT ID: NCT06600750

Last Updated: 2024-09-26

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

494 participants

Study Classification

OBSERVATIONAL

Study Start Date

2018-01-01

Study Completion Date

2023-12-31

Brief Summary

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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.

Detailed Description

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Conditions

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Renal Insufficiency, Chronic Arteriovenous Fistula Artificial Intelligence (AI) Machine Learning

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Study Groups

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Patients who underwent radiocephalic arteriovenous fistula due to advanced chronic kidney disease

Patients who underwent radiocephalic arteriovenous fistula due to advanced chronic kidney disease

Arteriovenous fistula

Intervention Type PROCEDURE

Patients who underwent Radiocephalic arteriovenous fistula surgery

Interventions

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Arteriovenous fistula

Patients who underwent Radiocephalic arteriovenous fistula surgery

Intervention Type PROCEDURE

Eligibility Criteria

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Inclusion Criteria

* patients who underwent RCAVF due to advanced chronic kidney disease from 2018 to 2022

Exclusion Criteria

* Patients who did not have follow-up data available
Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Seoul National University Hospital

OTHER

Sponsor Role lead

Responsible Party

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Ara Cho

Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Seoul National University Hospital

Seoul, Seoul, South Korea

Site Status

Countries

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South Korea

References

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Georgiadis GS, Charalampidis DG, Argyriou C, Georgakarakos EI, Lazarides MK. The Necessity for Routine Pre-operative Ultrasound Mapping Before Arteriovenous Fistula Creation: A Meta-analysis. Eur J Vasc Endovasc Surg. 2015 May;49(5):600-5. doi: 10.1016/j.ejvs.2015.01.012. Epub 2015 Feb 27.

Reference Type BACKGROUND
PMID: 25736517 (View on PubMed)

Vascular Access Work Group. Clinical practice guidelines for vascular access. Am J Kidney Dis. 2006 Jul;48 Suppl 1:S248-73. doi: 10.1053/j.ajkd.2006.04.040. No abstract available.

Reference Type BACKGROUND
PMID: 16813991 (View on PubMed)

Perera GB, Mueller MP, Kubaska SM, Wilson SE, Lawrence PF, Fujitani RM. Superiority of autogenous arteriovenous hemodialysis access: maintenance of function with fewer secondary interventions. Ann Vasc Surg. 2004 Jan;18(1):66-73. doi: 10.1007/s10016-003-0094-y. Epub 2004 Jan 20.

Reference Type BACKGROUND
PMID: 14727162 (View on PubMed)

Other Identifiers

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S2020-3118-0001

Identifier Type: -

Identifier Source: org_study_id

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