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From Basic Cardiac Imaging to Image Fusion pp 125–134Cite as

Diagnostic Algorithms in Patients with Suspected Coronary Artery Disease: Guidelines and Evidence-Based Behaviors

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Abstract

Cardiovascular disease represents a leading cause of morbidity and mortality worldwide, despite all available diagnostic tools and innovative therapeutic approaches. Thus, the early identification of patients with suspected coronary artery disease is very important in order to treat the disease in an early stage and prevent its potentially fatal consequences. The evaluation of traditional cardiovascular risk factors and of typical symptoms is the first step to detect the suspect of coronary artery disease. If this suspect is confirmed, diagnostic algorithms may be applied to direct patients to a correct medical or invasive therapeutic management. The aim of this chapter is to describe the available evidences and to discuss the actually proposed algorithms to manage patients with suspected coronary abnormalities in order to choose the best diagnostic and therapeutic approach in such population.

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Authors and Affiliations

  1. Department of Internal Medicine, Cardiovascular and Immunological Disorders, Federico II University of Naples, Naples, Italy

    Stefania Paolillo & Pasquale Perrone Filardi

Authors
  1. Stefania Paolillo
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  2. Pasquale Perrone Filardi
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Correspondence to Pasquale Perrone Filardi .

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Editors and Affiliations

  1. Fondazione Toscana Gabriele Monasterio, Department of Nuclear Medicine, CNR Institute of Clinical Physiology, Pisa, Italy

    Paolo Marzullo

  2. Centro Regionale di Medicina Nucleare, Universita di Pisa, Via Roma 67, Pisa, 56100, Italy

    Giuliano Mariani

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Paolillo, S., Perrone Filardi, P. (2013). Diagnostic Algorithms in Patients with Suspected Coronary Artery Disease: Guidelines and Evidence-Based Behaviors. In: Marzullo, P., Mariani, G. (eds) From Basic Cardiac Imaging to Image Fusion. Springer, Milano. https://doi.org/10.1007/978-88-470-2760-2_9

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  • DOI: https://doi.org/10.1007/978-88-470-2760-2_9

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  • Publisher Name: Springer, Milano

  • Print ISBN: 978-88-470-2759-6

  • Online ISBN: 978-88-470-2760-2

  • eBook Packages: MedicineMedicine (R0)

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