Application of the Seattle heart failure model in patients >80 years of age enrolled in a tertiary care heart failure clinic

Am J Cardiol. 2012 Dec 1;110(11):1663-6. doi: 10.1016/j.amjcard.2012.07.034. Epub 2012 Aug 22.


The Seattle Heart Failure Model (SHFM) is 1 of the most widely used tools to predict survival in patients with heart failure. However, it does not accommodate very elderly patients. We decided to assess the applicability of the SHFM in patients >80 years old enrolled in a tertiary care heart failure clinic. We evaluated the difference between observed survival and mean life expectancy as predicted by the SHFM on 261 patients >80 years old enrolled in a heart failure clinic at the Jewish General Hospital, Montreal, Quebec, Canada from January 2002 through March 2010. Average age of the patient population was 85 ± 4 years (range 80 to 105). Sixty-two percent of the population consisted of men, 63% had ischemic cardiomyopathy (ICM), and average ejection fraction was 36 ± 18%. Median observed survival was 1.91 years (interquartile range 0.68 to 5.53) for the total population (n = 261). The SHFM (predicted median survival 6.7 years, interquartile range 3.8 to 11.2) overestimated life expectancy by an average of 4.79 years. For patients with ICM (n = 164) versus non-ICM (n = 97), the score overestimated survival by 4.29 versus 5.69 years, respectively. In conclusion, the SHFM overestimates life expectancy in elderly patients followed in a tertiary care heart failure clinic. Further studies are needed to more accurately estimate prognosis in this patient population.

Publication types

  • Comparative Study

MeSH terms

  • Aged, 80 and over
  • Confidence Intervals
  • Female
  • Follow-Up Studies
  • Heart Failure / epidemiology*
  • Heart Failure / therapy
  • Heart Transplantation
  • Heart-Assist Devices
  • Humans
  • Life Expectancy
  • Male
  • Population Surveillance*
  • Prognosis
  • Quebec / epidemiology
  • Retrospective Studies
  • Survival Rate / trends
  • Tertiary Care Centers*
  • Time Factors