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Variability in biological markers for prediction of adverse cardiovascular events
  1. Thomas Senoner,
  2. Wolfgang Dichtl
  1. University Hospital for Internal Medicine III (Cardiology and Angiology), Medical University Innsbruck, Innsbruck, Austria
  1. Correspondence to Dr Wolfgang Dichtl, University Hospital for Internal Medicine III (Cardiology and Angiology), Medical University Innsbruck, Innsbruck 6020, Austria; dichtl{at}me.com

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Clinical cardiologists are trained from the start of their career to focus on risk factor assessment and treatment according to current guidelines. Risk factors are traditionally defined by absolute cut-off limits, for example, target levels of low-density lipoprotein (LDL) cholesterol to be reached in patients with atherosclerotic cardiovascular disease.

Whereas debates on absolute numbers are ongoing, for example, between European and American experts about adequate definition of arterial hypertension, other aspects of optimal risk factor assessment are still largely ignored. Basically, a holistic longitudinal rather than a single-shot interpretation of risk parameters measured in one individual should come more into our focus. Obviously, this trend is based on and will further depend on the possibilities of digital medicine with the increasing use of artificial intelligence like deep learning methods.

With a complete database of more …

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Footnotes

  • Twitter @ThomasSenoner

  • Contributors Both TS and WD have contributed equally in writing this editorial.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Patient consent for publication Not required.

  • Provenance and peer review Commissioned; internally peer reviewed.

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