Literature DB >> 16707656

Prognostic value of a novel classification scheme for heart failure: the Minnesota Heart Failure Criteria.

Joseph Kim1, David R Jacobs, Russell V Luepker, Eyal Shahar, Karen L Margolis, Mark P Becker.   

Abstract

The authors present the Minnesota Heart Failure Criteria (MHFC), derived using latent class analysis from widely available items in the Framingham Criteria. The authors used 1995 and 2000 data on hospitalized Minnesota Heart Survey subjects discharged after myocardial infarction or heart failure (N = 7,379). Selected Framingham Criteria variables (dyspnea, pulmonary rales, cardiomegaly, interstitial or pulmonary edema on chest radiograph, S(3) heart sound, tachycardia) plus left ventricular ejection fraction were used. The discriminatory power of the MHFC was evaluated using age- and sex-adjusted 2-year mortality. A five-class latent class analysis model was collapsed into cases and noncases. Mortality estimates discriminated noncases (18%) from cases (43%) (p < 0.001). The MHFC performed better than previous truncated criteria (Framingham Criteria: 26% noncases, 43% cases; Duke Criteria: 29%, 40%; Killip Score: 31%, 44%; Boston Score: 28%, 45%). In a subset of patients admitted for heart failure (n = 5,128), the MHFC identified all but 2% (116/4,746) of cases found with a nearly full version of the Framingham Criteria. In terms of prognostic value, the MHFC are as precise as or more precise than several previous sets of truncated criteria. They closely approximate a nearly full version of the Framingham Criteria but require many fewer variables and can facilitate epidemiologic case-finding for heart failure.

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Year:  2006        PMID: 16707656     DOI: 10.1093/aje/kwj168

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  7 in total

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2.  Comparative study of Kaposi's sarcoma-associated herpesvirus serological assays using clinically and serologically defined reference standards and latent class analysis.

Authors:  Maria Claudia Nascimento; Vanda Akico de Souza; Laura Masami Sumita; Wilton Freire; Fernando Munoz; Joseph Kim; Claudio S Pannuti; Philippe Mayaud
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3.  Comparing methods for identifying patients with heart failure using electronic data sources.

Authors:  Fadi Alqaisi; L Keoki Williams; Edward L Peterson; David E Lanfear
Journal:  BMC Health Serv Res       Date:  2009-12-18       Impact factor: 2.655

4.  Characterization of subgroups of heart failure patients with preserved ejection fraction with possible implications for prognosis and treatment response.

Authors:  David P Kao; James D Lewsey; Inder S Anand; Barry M Massie; Michael R Zile; Peter E Carson; Robert S McKelvie; Michel Komajda; John J V McMurray; JoAnn Lindenfeld
Journal:  Eur J Heart Fail       Date:  2015-08-06       Impact factor: 15.534

5.  Bioinformatics multivariate analysis determined a set of phase-specific biomarker candidates in a novel mouse model for viral myocarditis.

Authors:  Seiichi Omura; Eiichiro Kawai; Fumitaka Sato; Nicholas E Martinez; Ganta V Chaitanya; Phoebe A Rollyson; Urska Cvek; Marjan Trutschl; J Steven Alexander; Ikuo Tsunoda
Journal:  Circ Cardiovasc Genet       Date:  2014-07-16

6.  A personalized BEST: characterization of latent clinical classes of nonischemic heart failure that predict outcomes and response to bucindolol.

Authors:  David P Kao; Brandie D Wagner; Alastair D Robertson; Michael R Bristow; Brian D Lowes
Journal:  PLoS One       Date:  2012-11-07       Impact factor: 3.240

7.  Diagnostic value of patterns of symptoms and signs of heart failure: application of latent class analysis with concomitant variables in a cross-sectional study.

Authors:  Milton Severo; Ana Rita Gaio; Patrícia Lourenço; Margarida Alvelos; Alexandra Gonçalves; Nuno Lunet; Paulo Bettencourt; Ana Azevedo
Journal:  BMJ Open       Date:  2012-11-12       Impact factor: 2.692

  7 in total

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