Angiology: Open Access
Open Access

Abstract

Risk Prediction Models for Autogenous Arteriovenous Fistula Maturation Failure in Patients with End-Stage Renal Disease: A Systematic Review and Meta-Analysis

Jinhong Miao*, Jiajia Jia, Yujie Zhu, Juan Du, Yutian Lei, Qingyang Zhang

Background: Autogenous Arteriovenous Fistula (AVF) is the preferred vascular access for maintenance hemodialysis in patients with End-Stage Renal Disease (ESRD), but its clinical utility is limited by high rates of maturation failure. Although multiple predictive models have been developed, their reliability and methodological quality remain uncertain.

Objective: To systematically review and evaluate the predictive performance and risk of bias of existing models for AVF maturation failure in ESRD patients.

Methods: A systematic search of nine databases (including PubMed, Embase, Web of Science, and Cochrane Library) was conducted from inception to November 14, 2024. Studies involving adult ESRD patients undergoing new AVF creation and reporting prediction models for AVF maturation failure were included. Data extraction followed the CHARMS framework, and methodological quality was assessed using the PROBAST tool. Meta-analysis of model performance was conducted using AUC values, with heterogeneity assessed via I² statistics and Cochran’s Q test.

Results: Eighteen studies comprising 18 prediction models (sample sizes 66–14,892) across eight countries were included. The incidence of AVF maturation failure ranged from 11.0% to 69.7%. Common predictors included preoperative vein diameter, age, sex, diabetes, and peripheral vascular disease. Model performance showed moderate to good discrimination, with AUC values ranging from 0.629 to 0.886. However, only three studies conducted external validation, and most relied on internal validation methods. Seventeen models were assessed as having a high risk of bias, primarily due to limitations in study design, predictor measurement, outcome assessment, and statistical analysis.

Conclusions: Existing prediction models for AVF maturation failure demonstrate variable performance and are generally limited by high risk of bias and insufficient external validation. Future research should focus on improving methodological rigor, standardizing predictor and outcome definitions, and conducting robust external validations to enhance clinical applicability.

Published Date: 2026-02-16; Received Date: 2024-12-17