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Predictive models for arteriovenous fistula maturation

Predictive models for arteriovenous fistula maturation

forthcoming

Article Type: ORIGINAL ARTICLE

Article Subject: Dialysis

DOI:10.5301/jva.5000500

Authors

Al Shakarchi, Julien McGrogan, Damian Van der Veer, Sabine Sperrin, Matthew Inston, Nicholas

Abstract

Haemodialysis (HD) is a lifeline therapy for patients with end-stage renal disease (ESRD). A critical factor in the survival of renal dialysis patients is the surgical creation of vascular access, and international guidelines recommend arteriovenous fistulas (AVF) as the gold standard of vascular access for haemodialysis. Despite this, AVFs have been associated with high failure rates. Although risk factors for AVF failure have been identified, their utility for predicting AVF failure through predictive models remains unclear. The objectives of this review are to systematically and critically assess the methodology and reporting of studies developing prognostic predictive models for AVF outcomes and assess them for suitability in clinical practice.

Electronic databases were searched for studies reporting prognostic predictive models for AVF outcomes. Dual review was conducted to identify studies that reported on the development or validation of a model constructed to predict AVF outcome following creation. Data were extracted on study characteristics, risk predictors, statistical methodology, model type, as well as validation process.

We included four different studies reporting five different predictive models. Parameters identified that were common to all scoring system were age and cardiovascular disease.

This review has found a small number of predictive models in vascular access. The disparity between each study limits the development of a unified predictive model.

Article History

Disclosures

Financial support: None declared.
Conflicts of interest: None declared.

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Authors

  • Al Shakarchi, Julien [PubMed] [Google Scholar] 1, * Corresponding Author (j.alshakarchi@nhs.net)
  • McGrogan, Damian [PubMed] [Google Scholar] 1
  • Van der Veer, Sabine [PubMed] [Google Scholar] 2
  • Sperrin, Matthew [PubMed] [Google Scholar] 2
  • Inston, Nicholas [PubMed] [Google Scholar] 1

Affiliations

  • Department of Renal Surgery, University Hospital Birmingham, Birmingham - UK
  • Centre for Health Informatics, University of Manchester, Manchester - UK

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