論文

査読有り 国際誌
2018年12月1日

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

Scientific Reports
  • Mari Sakamoto
  • Hiroki Fukuda
  • Jiyoong Kim
  • Tomomi Ide
  • Shintaro Kinugawa
  • Arata Fukushima
  • Hiroyuki Tsutsui
  • Akira Ishii
  • Shin Ito
  • Hiroshi Asanuma
  • Masanori Asakura
  • Takashi Washio
  • Masafumi Kitakaze
  • 全て表示

8
1
開始ページ
3986
終了ページ
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1038/s41598-018-22347-0
出版者・発行元
Nature Publishing Group

Since our retrospective study has formed a mathematical formula, α = f(x 1, .., x 252), where α is the probability of cardiovascular events in patients with heart failure (HF) and x 1 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(x 1, .., x 50) 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.

リンク情報
DOI
https://doi.org/10.1038/s41598-018-22347-0
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/29507373
ID情報
  • DOI : 10.1038/s41598-018-22347-0
  • ISSN : 2045-2322
  • PubMed ID : 29507373
  • SCOPUS ID : 85043265996

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