Predicting high-flow arteriovenous fistulas and cardiac outcomes in hemodialysis patients.

Journal: Journal of vascular surgery
PMID: 39631475

Abstract

BACKGROUND: Heart failure is common in patients receiving hemodialysis. A high-flow arteriovenous fistula (AVF) may represent a modifiable risk factor for heart failure and death. Currently, no tools exist to assess the risk of developing a high-flow AVF (>2000 mL/min). The aim of this study was to use machine learning to develop a predictive model identifying patients at risk of developing a high-flow AVF and to examine the relationship between blood flow, heart failure, and death.

Authors

  • Nasir A Shah
    School of Clinical Medicine, Faculty of Medicine & Health, UNSW Sydney, Sydney, New South Wales, Australia; Department of Nephrology, Prince of Wales Hospital, Sydney, New South Wales, Australia. Electronic address: nasir.shah@health.nsw.gov.au.
  • Pauline Byrne
    Department of Nephrology, Wollongong Hospital, Wollongong, New South Wales, Australia.
  • Zoltan H Endre
    School of Clinical Medicine, Faculty of Medicine & Health, UNSW Sydney, Sydney, New South Wales, Australia; Department of Nephrology, Prince of Wales Hospital, Sydney, New South Wales, Australia.
  • Blake J Cochran
    School of Biomedical Sciences, Faculty of Medicine & Health, UNSW Sydney, Sydney, New South Wales, Australia.
  • Tracie J Barber
    School of Mechanical and Manufacturing Engineering, Faculty of Engineering, UNSW Sydney, Sydney, New South Wales, Australia.
  • Jonathan H Erlich
    School of Clinical Medicine, Faculty of Medicine & Health, UNSW Sydney, Sydney, New South Wales, Australia; Department of Nephrology, Prince of Wales Hospital, Sydney, New South Wales, Australia.

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