Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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University Hospital of Bern

in Cooperation with on an Cooperation-Score of 37%

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Publications (1/1 displayed)

  • 2022QRS micro-fragmentation as a mortality predictor23citations

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Shipley, Martin
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Britton, Annie
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Vandenberk, Bert
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Willems, Rik
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Schmidt, Georg
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Sticherling, Christian
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2022

Co-Authors (by relevance)

  • Shipley, Martin
  • Britton, Annie
  • Vandenberk, Bert
  • Willems, Rik
  • Schmidt, Georg
  • Bauer, Axel
  • Vos, Marc A.
  • Junttila, Juhani
  • Huikuri, Heikki V.
  • Franz, Michael R.
  • Malik, Marek
  • Andršová, Irena
  • Schlögl, Simon
  • Zabel, Markus
  • Sprenkeler, David
  • Novotny, Tomas
  • Friede, Tim
  • Sticherling, Christian
  • Hnatkova, Katerina
OrganizationsLocationPeople

article

QRS micro-fragmentation as a mortality predictor

  • Shipley, Martin
  • Britton, Annie
  • Vandenberk, Bert
  • Willems, Rik
  • Schmidt, Georg
  • Bauer, Axel
  • Vos, Marc A.
  • Junttila, Juhani
  • Huikuri, Heikki V.
  • Franz, Michael R.
  • Malik, Marek
  • Andršová, Irena
  • Schlögl, Simon
  • Zabel, Markus
  • Sprenkeler, David
  • Novotny, Tomas
  • Reichlin, Tobias
  • Friede, Tim
  • Sticherling, Christian
  • Hnatkova, Katerina
Abstract

<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 &amp;lt; 0.001 univariably, and P &amp;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>

Topics
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