02739nas a2200241   4500000000100000008004100001100001800042700001500060700001600075700001200091700001400103700001600117700002000133700001800153700001500171700001300186245008500199250001500284300001000299490000600309520213100315020005102446       2014                            d1 aWoodward Mark1 aBennett D.1 aWilliams T.1 aBasu J.1 aDwight J.1 aMcMurray J.1 aConrad Nathalie1 aPatel Anushka1 aMacmahon S1 aRahimi K00aRisk prediction in patients with heart failure: a systematic review and analysis  a2014/09/10  a440-60 v23 a<p>
OBJECTIVES: This study sought to review the literature for risk prediction models in patients with heart failure and to identify the most consistently reported independent predictors of risk across models. BACKGROUND: Risk assessment provides information about patient prognosis, guides decision making about the type and intensity of care, and enables better understanding of provider performance. METHODS: MEDLINE and EMBASE were searched from January 1995 to March 2013, followed by hand searches of the retrieved reference lists. Studies were eligible if they reported at least 1 multivariable model for risk prediction of death, hospitalization, or both in patients with heart failure and reported model performance. We ranked reported individual risk predictors by their strength of association with the outcome and assessed the association of model performance with study characteristics. RESULTS: Sixty-four main models and 50 modifications from 48 studies met the inclusion criteria. Of the 64 main models, 43 models predicted death, 10 hospitalization, and 11 death or hospitalization. The discriminatory ability of the models for prediction of death appeared to be higher than that for prediction of death or hospitalization or prediction of hospitalization alone (p = 0.0003). A wide variation between studies in clinical settings, population characteristics, sample size, and variables used for model development was observed, but these features were not significantly associated with the discriminatory performance of the models. A few strong predictors emerged for prediction of death; the most consistently reported predictors were age, renal function, blood pressure, blood sodium level, left ventricular ejection fraction, sex, brain natriuretic peptide level, New York Heart Association functional class, diabetes, weight or body mass index, and exercise capacity. CONCLUSIONS: There are several clinically useful and well-validated death prediction models in patients with heart failure. Although the studies differed in many respects, the models largely included a few common markers of risk.
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  a2213-1787 (Electronic)<br/>2213-1779 (Linking)