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Biomarkers in heart failure--better than history or echocardiography?

Abstract
The management of heart failure patients (diagnosis, treatment monitoring, assessment of prognosis) crucially depends on the accuracy of the tools used for patient evaluation. While the diagnostic accuracy of anamnesis, clinical signs and symptoms is poor, "classic" tools like chest X-ray or electrocardiogram show reasonable specificity but poor sensitivity. Transthoracic echocardiography is well suited for the diagnosis of heart failure, but is relatively costly and depends on availability and the skills of the investigator. Over the last 2 decades, numerous biomarkers have emerged that potentially might aid in the complex decisionmaking processes for diagnosis, treatment and monitoring of heart failure. The ideal biomarker would possess a favorable diagnostic test profile and deliver pivotal information. In this respect, the currently best evidence base has been accumulated for the natriuretic peptide family. A large array of other heart failure biomarkers (i.e., markers of inflammation, extracellular matrix remodeling, and myocyte damage and stress) are still in earlier phases of testing. This short review will provide a balanced comparison of those "classic tools" and natriuretic peptides focusing on their diagnostic capacity in various clinical settings, factors influencing test values, cutoff values and their interpretation, and the capacity of these biomarkers to guide the diagnostic and therapeutic decision-making processes in patients with suspected and established heart failure.
AuthorsDominik Berliner, Christiane E Angermann, Georg Ertl, Stefan Störk
JournalHerz (Herz) Vol. 34 Issue 8 Pg. 581-8 (Dec 2009) ISSN: 1615-6692 [Electronic] Germany
PMID20024636 (Publication Type: Comparative Study, Evaluation Study, Journal Article, Meta-Analysis, Research Support, Non-U.S. Gov't)
Chemical References
  • Biomarkers
Topics
  • Biomarkers (blood)
  • Echocardiography (statistics & numerical data)
  • Heart Failure (blood, diagnosis, epidemiology)
  • Humans
  • Medical History Taking (statistics & numerical data)
  • Prevalence
  • Risk Assessment (methods)
  • Risk Factors
  • Sensitivity and Specificity

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