Echocardiography and risk prediction in advanced heart failure: incremental value over clinical markers

J Card Fail. 2009 Sep;15(7):586-92. doi: 10.1016/j.cardfail.2009.03.002. Epub 2009 Apr 28.

Abstract

Background: Incremental value of echocardiography over clinical parameters for outcome prediction in advanced heart failure (HF) is not well established.

Methods and results: We evaluated 223 patients with advanced HF receiving optimal therapy (91.9% angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, 92.8% beta-blockers, 71.8% biventricular pacemaker, and/or defibrillator use). The Seattle Heart Failure Model (SHFM) was used as the reference clinical risk prediction scheme. The incremental value of echocardiographic parameters for event prediction (death or urgent heart transplantation) was measured by the improvement in fit and discrimination achieved by addition of standard echocardiographic parameters to the SHFM. After a median follow-up of 2.4 years, there were 38 (17.0%) events (35 deaths; 3 urgent transplants). The SHFM had likelihood ratio (LR) chi(2) 32.0 and C statistic 0.756 for event prediction. Left ventricular end-systolic volume, stroke volume, and severe tricuspid regurgitation were independent echocardiographic predictors of events. The addition of these parameters to SHFM improved LR chi(2) to 72.0 and C statistic to 0.866 (P < .001 and P=.019, respectively). Reclassifying the SHFM-predicted risk with use of the echocardiography-added model resulted in improved prognostic separation.

Conclusions: Addition of standard echocardiographic variables to the SHFM results in significant improvement in risk prediction for patients with advanced HF.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Biomarkers / blood*
  • Cohort Studies
  • Echocardiography / standards
  • Female
  • Follow-Up Studies
  • Heart Failure / blood*
  • Heart Failure / diagnostic imaging*
  • Heart Failure / mortality
  • Humans
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • Risk Factors
  • Survival Rate / trends

Substances

  • Biomarkers