Literature DB >> 20424966

Use of multiple biomarkers in heart failure.

Larry A Allen1.   

Abstract

Biomarkers are becoming increasingly available for clinical use, particularly in the care of patients with heart failure. For health care providers, a major difficulty is how to interpret and apply these increasing amounts of diagnostic and prognostic information. Consequently, the scientific challenge is evolving from the discovery of biomarkers to the selection and validation of select panels of clinically useful markers that balance performance and practicality. Optimal combinations of biomarkers will vary based on the intended use (eg, diagnosis vs prognosis). The final goal must be to generate more actionable knowledge that improves patient management and outcomes, rather than merely creating greater complexity. Here we conceptually define multiple biomarker strategies, provide examples of emerging biomarker panels used in the care of patients with heart failure, and address key statistical and clinical issues for this rapidly evolving field.

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Year:  2010        PMID: 20424966     DOI: 10.1007/s11886-010-0109-6

Source DB:  PubMed          Journal:  Curr Cardiol Rep        ISSN: 1523-3782            Impact factor:   2.931


  44 in total

Review 1.  Biomarkers and surrogate endpoints: preferred definitions and conceptual framework.

Authors: 
Journal:  Clin Pharmacol Ther       Date:  2001-03       Impact factor: 6.875

2.  2009 focused update: ACCF/AHA Guidelines for the Diagnosis and Management of Heart Failure in Adults: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines: developed in collaboration with the International Society for Heart and Lung Transplantation.

Authors:  Mariell Jessup; William T Abraham; Donald E Casey; Arthur M Feldman; Gary S Francis; Theodore G Ganiats; Marvin A Konstam; Donna M Mancini; Peter S Rahko; Marc A Silver; Lynne Warner Stevenson; Clyde W Yancy
Journal:  Circulation       Date:  2009-03-26       Impact factor: 29.690

3.  One-year mortality prognosis in heart failure: a neural network approach based on echocardiographic data.

Authors:  J Ortiz; C G Ghefter; C E Silva; R M Sabbatini
Journal:  J Am Coll Cardiol       Date:  1995-12       Impact factor: 24.094

Review 4.  Neural networks in clinical medicine.

Authors:  W Penny; D Frost
Journal:  Med Decis Making       Date:  1996 Oct-Dec       Impact factor: 2.583

5.  Risk stratification after hospitalization for decompensated heart failure.

Authors:  G Michael Felker; Jeffrey D Leimberger; Robert M Califf; Michael S Cuffe; Barry M Massie; Kirkwood F Adams; Mihai Gheorghiade; Christopher M O'Connor
Journal:  J Card Fail       Date:  2004-12       Impact factor: 5.712

6.  Development and prospective validation of a clinical index to predict survival in ambulatory patients referred for cardiac transplant evaluation.

Authors:  K D Aaronson; J S Schwartz; T M Chen; K L Wong; J E Goin; D M Mancini
Journal:  Circulation       Date:  1997-06-17       Impact factor: 29.690

7.  Risk stratification in heart failure using artificial neural networks.

Authors:  F Atienza; N Martinez-Alzamora; J A De Velasco; S Dreiseitl; L Ohno-Machado
Journal:  Proc AMIA Symp       Date:  2000

8.  Use and misuse of the receiver operating characteristic curve in risk prediction.

Authors:  Nancy R Cook
Journal:  Circulation       Date:  2007-02-20       Impact factor: 29.690

9.  Advances in measuring the effect of individual predictors of cardiovascular risk: the role of reclassification measures.

Authors:  Nancy R Cook; Paul M Ridker
Journal:  Ann Intern Med       Date:  2009-06-02       Impact factor: 25.391

Review 10.  End points for clinical trials in acute heart failure syndromes.

Authors:  Larry A Allen; Adrian F Hernandez; Christopher M O'Connor; G Michael Felker
Journal:  J Am Coll Cardiol       Date:  2009-06-16       Impact factor: 24.094

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  5 in total

1.  Classification of heart failure in the atherosclerosis risk in communities (ARIC) study: a comparison of diagnostic criteria.

Authors:  Wayne D Rosamond; Patricia P Chang; Chris Baggett; Anna Johnson; Alain G Bertoni; Eyal Shahar; Anita Deswal; Gerardo Heiss; Lloyd E Chambless
Journal:  Circ Heart Fail       Date:  2012-01-23       Impact factor: 8.790

Review 2.  Charting a roadmap for heart failure biomarker studies.

Authors:  Tariq Ahmad; Mona Fiuzat; Michael J Pencina; Nancy L Geller; Faiez Zannad; John G F Cleland; James V Snider; Stephan Blankenberg; Kirkwood F Adams; Rita F Redberg; Jae B Kim; Alice Mascette; Robert J Mentz; Christopher M O'Connor; G Michael Felker; James L Januzzi
Journal:  JACC Heart Fail       Date:  2014-06-11       Impact factor: 12.035

Review 3.  Novel biomarkers in chronic heart failure.

Authors:  Tariq Ahmad; Mona Fiuzat; G Michael Felker; Christopher O'Connor
Journal:  Nat Rev Cardiol       Date:  2012-03-27       Impact factor: 32.419

Review 4.  The Current and Potential Clinical Relevance of Heart Failure Biomarkers.

Authors:  Parul U Gandhi; Jeffrey M Testani; Tariq Ahmad
Journal:  Curr Heart Fail Rep       Date:  2015-10

5.  Red cell distribution width predicts short- and long-term outcomes of acute congestive heart failure more effectively than hemoglobin.

Authors:  Yuxiang Dai; Hakuoh Konishi; Atsutoshi Takagi; Katsumi Miyauchi; Hiroyuki Daida
Journal:  Exp Ther Med       Date:  2014-06-04       Impact factor: 2.447

  5 in total

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