Redefining β-blocker response in heart failure patients with sinus rhythm and atrial fibrillation: a machine learning cluster analysis.

Journal: Lancet (London, England)
PMID:

Abstract

BACKGROUND: Mortality remains unacceptably high in patients with heart failure and reduced left ventricular ejection fraction (LVEF) despite advances in therapeutics. We hypothesised that a novel artificial intelligence approach could better assess multiple and higher-dimension interactions of comorbidities, and define clusters of β-blocker efficacy in patients with sinus rhythm and atrial fibrillation.

Authors

  • Andreas Karwath
    Institute of Cancer and Genomic Sciences, University of Birmingham, UK; University Hospitals Birmingham NHS Foundation Trust, UK; Health Data Research, UK.
  • Karina V Bunting
    University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK; Health Data Research UK Midlands Site, Birmingham, UK.
  • Simrat K Gill
    Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK.
  • Otilia Tica
    Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK; Health Data Research UK Midlands Site, Birmingham, UK.
  • Samantha Pendleton
    Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK.
  • Furqan Aziz
    IMSciences, Phase 7, Hayatabad, Peshawar 25000, Pakistan.
  • Andrey D Barsky
    Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK; Health Data Research UK Midlands Site, Birmingham, UK.
  • Saisakul Chernbumroong
  • Jinming Duan
    School of Computer Science University of Birmingham Birmingham UK.
  • Alastair R Mobley
    University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK; Health Data Research UK Midlands Site, Birmingham, UK.
  • Victor Roth Cardoso
    College of Medical and Dental Sciences, Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, B15 2TT, UK.
  • Karin Slater
    Institute of Cancer and Genomic Sciences, University of Birmingham, UK; University Hospitals Birmingham NHS Foundation Trust, UK.
  • John A Williams
    Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, United Kingdom; Medical Research Council Harwell Institute, Harwell Campus, Oxfordshire, United Kingdom.
  • Emma-Jane Bruce
    University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK; Health Data Research UK Midlands Site, Birmingham, UK.
  • Xiaoxia Wang
    School of Control and Computer Engineering, North China Electric Power University, Baoding, Hebei Province, China.
  • Marcus D Flather
    Norwich Medical School, University of East Anglia, Norwich, UK.
  • Andrew J S Coats
    Warwick Medical School, University of Warwick, Warwick, UK.
  • Georgios V Gkoutos
    Institute of Cancer and Genomic Sciences, Centre for Computational Biology, University of Birmingham, Birmingham, United Kingdom; Institute of Translational Medicine, University of Birmingham, Birmingham, United Kingdom; NIHR Surgical Reconstruction and Microbiology Research Centre, University Hospital Birmingham, Birmingham, United Kingdom; MRC Health Data Research UK (HDR UK), London, United Kingdom; NIHR Experimental Cancer Medicine Centre, Birmingham, United Kingdom; NIHR Biomedical Research Centre, University Hospital Birmingham, Birmingham, United Kingdom.
  • Dipak Kotecha
    University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK; Health Data Research UK Midlands Site, Birmingham, UK. Electronic address: d.kotecha@bham.ac.uk.