QRS micro-fragmentation as a mortality predictor

  • Katerina Hnatkova
    National Heart and Lung Institute, Imperial College, ICTEM , Hammersmith Campus, 72 Du Cane Road, Shepherd’s Bush, London W12 0NN , UK
  • Irena Andršová
    Department of Internal Medicine and Cardiology, University Hospital Brno , Brno , Czech Republic
  • Tomáš Novotný
    Department of Internal Medicine and Cardiology, University Hospital Brno , Brno , Czech Republic
  • Annie Britton
    Research Department of Epidemiology and Public Health, University College London , UK
  • Martin Shipley
    Research Department of Epidemiology and Public Health, University College London , UK
  • Bert Vandenberk
    Department of Cardiovascular Sciences, University of Leuven , Leuven , Belgium
  • David J Sprenkeler
    Department of Medical Physiology, University Medical Center Utrecht , Utrecht , The Netherlands
  • Juhani Junttila
    Medical Research Center Oulu, University Central Hospital of Oulu and University of Oulu , Oulu , Finland
  • Tobias Reichlin
    Department of Cardiology, Inselspital, Bern University Hospital , Bern , Switzerland
  • Simon Schlögl
    Department of Cardiology and Pneumology, University Medical Center , Göttingen , Germany
  • Marc A Vos
    Department of Medical Physiology, University Medical Center Utrecht , Utrecht , The Netherlands
  • Tim Friede
    German Center of Cardiovascular Research (DZHK), Partner Site Göttingen , Göttingen , Germany
  • Axel Bauer
    University Hospital for Internal Medicine III, Medical University Innsbruck , Innsbruck , Austria
  • Heikki V Huikuri
    Medical Research Center Oulu, University Central Hospital of Oulu and University of Oulu , Oulu , Finland
  • Rik Willems
    Department of Cardiovascular Sciences, University of Leuven , Leuven , Belgium
  • Georg Schmidt
    Klinikum rechts der Isar, Technical University of Munich , Munich , Germany
  • Michael R Franz
    Veteran Affairs and Georgetown University Medical Centers , Washington, DC , USA
  • Christian Sticherling
    Department of Cardiology, University Hospital of Basel , Basel , Switzerland
  • Markus Zabel
    Department of Cardiology and Pneumology, University Medical Center , Göttingen , Germany
  • Marek Malik
    National Heart and Lung Institute, Imperial College, ICTEM , Hammersmith Campus, 72 Du Cane Road, Shepherd’s Bush, London W12 0NN , UK

抄録

<jats:title>Abstract</jats:title> <jats:sec> <jats:title>Aims</jats:title> <jats:p>Fragmented QRS complex with visible notching on standard 12-lead electrocardiogram (ECG) is understood to represent depolarization abnormalities and to signify risk of cardiac events. Depolarization abnormalities with similar prognostic implications likely exist beyond visual recognition but no technology is presently suitable for quantification of such invisible ECG abnormalities. We present such a technology.</jats:p> </jats:sec> <jats:sec> <jats:title>Methods and results</jats:title> <jats:p>A signal processing method projects all ECG leads of the QRS complex into optimized three perpendicular dimensions, reconstructs the ECG back from this three-dimensional projection, and quantifies the difference (QRS ‘micro’-fragmentation, QRS-μf) between the original and reconstructed signals. QRS ‘micro’-fragmentation was assessed in three different populations: cardiac patients with automatic implantable cardioverter-defibrillators, cardiac patients with severe abnormalities, and general public. The predictive value of QRS-μf for mortality was investigated both univariably and in multivariable comparisons with other risk factors including visible QRS ‘macro’-fragmentation, QRS-Mf. The analysis was made in a total of 7779 subjects of whom 504 have not survived the first 5 years of follow-up. In all three populations, QRS-μf was strongly predictive of survival (P &lt; 0.001 univariably, and P &lt; 0.001 to P = 0.024 in multivariable regression analyses). A similar strong association with outcome was found when dichotomizing QRS-μf prospectively at 3.5%. When QRS-μf was used in multivariable analyses, QRS-Mf and QRS duration lost their predictive value.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusion</jats:title> <jats:p>In three populations with different clinical characteristics, QRS-μf was a powerful mortality risk factor independent of several previously established risk indices. Electrophysiologic abnormalities that contribute to increased QRS-μf values are likely responsible for the predictive power of visible QRS-Mf.</jats:p> </jats:sec>

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