The impact of creating mathematical formula to predict cardiovascular events in patients with heart failure

Sci Rep. 2018 Mar 5;8(1):3986. doi: 10.1038/s41598-018-22347-0.

Abstract

Since our retrospective study has formed a mathematical formula, α = f(x1, …, x252), where α is the probability of cardiovascular events in patients with heart failure (HF) and x1 is each clinical parameter, we prospectively tested the predictive capability and feasibility of the mathematical formula of cardiovascular events in HF patients. First of all, to create such a mathematical formula using limited number of the parameters to predict the cardiovascular events in HF patients, we retrospectively determined f(x) that formulates the relationship between the most influential 50 clinical parameters (x) among 252 parameters using 167 patients hospitalized due to acute HF; the nonlinear optimization could provide the formula of α = f(x1, …, x50) which fitted the probability of the actual cardiovascular events per day. Secondly, we prospectively examined the predictability of f(x) in other 213 patients using 50 clinical parameters in 3 hospitals, and we found that the Kaplan-Meier curves using actual and estimated occurrence probabilities of cardiovascular events were closely correlated. We conclude that we created a mathematical formula f(x) that precisely predicted the occurrence probability of future cardiovascular outcomes of HF patients per day. Mathematical modelling may predict the occurrence probability of cardiovascular events in HF patients.

Publication types

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

MeSH terms

  • Aged
  • Algorithms*
  • Female
  • Heart Failure / diagnosis*
  • Heart Failure / physiopathology
  • Humans
  • Kaplan-Meier Estimate
  • Male
  • Middle Aged
  • Models, Cardiovascular*
  • Probability
  • Prognosis
  • Prospective Studies
  • Retrospective Studies