A prediction model of arteriovenous fistula dysfunction in hemodialysis patients was established based on a few sample synthesis oversampling technique algorithm

• Published in: Linchuang Shenzangbing Zazhi Vol. 24; no. 5; pp. 378 - 384
• Main Authors: Jian-yu Huang, Liang-liang Duan
• Format: Journal Article
• Language: Chinese
• Published: Editorial Department of Journal of Clinical Nephrology 01.05.2024
• Subjects: arteriovenous fistula; hemodialysis; poor function; prediction model; renal dialysis; synthetic minority over-sampling technique
• ISSN: 1671-2390
• DOI: 10.3969/j.issn.1671-2390.2024.05.005

Objective To explore the risk factors of arteriovenous fistula (AVF) dysfunction in hemodialysis (HD) patients and validate a risk warning model based upon synthetic minority oversampling technique (SMOTE). Methods From January 1, 2019 to December 31, 2021, 400 HD patients with AVF as dialysis access were selected as study subjects. According to AVF function of HD, they were assigned into two groups of poor AVF function (n=81) and normal AVF function (n=319). The relevant clinical data of selected HD patients were reviewed and the risk factors of poor AVF function screened by univariate and multivariate Logistic regression. Then the above risk factors were reconstructed by SMOTE algorithm for established an early warning model of poor AVF function. The prediction efficiency of two models was compared.Results Females, diabetes mellitus (DM), albumin <35 g/L, C-reactive protein (CRP) ≥25 mg/L, blood phosphorus >2 mmol/L and AVF stenosis were the risk factors for AVF dysfunction in HD patients (P<0.05). Accordin