Evaluation of 6 prognostic models used to calculate mortality rates in elderly heart failure patients with a fatal heart failure admission

Congest Heart Fail. Sep-Oct 2010;16(5):196-201. doi: 10.1111/j.1751-7133.2010.00180.x.

Abstract

The objective was to evaluate 6 commonly used heart failure (HF) prognostic models in an elderly, fatal HF population. Predictive models have been established to quantify risk among HF patients. The validation of these models has not been adequately studied, especially in an elderly cohort. Applying a single-center, retrospective study of serially admitted HF patients who died while in the hospital or within 30 days of discharge, the authors evaluated 6 prognostic models: the Seattle Heart Failure Model (SHFM), Heywood's model, Classification and Regression Tree (CART) Analysis, the Heart Failure Survival Score (HFSS), Heart Failure Risk Scoring System, and Pocock's score. Eighty patients were included (mean age, 82.7 ± 8.2 years). Twenty-three patients (28.75%) died in the hospital. The remainder died within 30 days of discharge. The models' predictions varied considerably from one another and underestimated the patients' actual mortality. This study demonstrates that these models underestimate the mortality risk in an elderly cohort at or approaching the end of life. Moreover, the predictions made by each model vary greatly from one another. Many of the models used were not intended for calculation during hospitalization. Development of improved models for the range of patients with HF syndromes is needed.

Publication types

  • Evaluation Study

MeSH terms

  • Aged
  • Aged, 80 and over
  • Causality
  • Disease Progression
  • Female
  • Forecasting
  • Frail Elderly / statistics & numerical data
  • Health Care Costs / trends
  • Heart Failure / economics
  • Heart Failure / epidemiology*
  • Heart Failure / therapy
  • Hospital Mortality / trends*
  • Hospitalization / statistics & numerical data
  • Humans
  • Life Expectancy / trends*
  • Life Tables*
  • Logistic Models
  • Male
  • Mortality / trends*
  • Risk Assessment / standards
  • Risk Assessment / statistics & numerical data
  • Survival Analysis