Predicting one-month survival after out-of-hospital cardiac arrest with/without defibrillation: Bivariate probit model using the Utstein style data

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  • Takimoto Taro
    Associate Professor, Faculty of Economics, Kyushu University
  • Sakata Kazuya
    Lecturer, Department of Civil Engineering, Utsunomiya University
  • Nakajima Kazunori
    Associate Professor, School of Human Science and Environment, University of Hyogo
  • Narukawa Masaki
    Associate Professor, Faculty of Economics, Okayama University
  • Sakamoto Naoki
    Associate Professor, Faculty of Policy Management, Tohoku Bunka Gakuen University
  • Abe Masahiro
    Doctor Student, Graduate School of Economics and Management, Tohoku University

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Other Title
  • 救急活動における病院収容時間と除細動実施が救命率に与える影響について：ウツタイン統計データによる2方程式プロビット・モデル分析
  • キュウキュウ カツドウ ニ オケル ビョウイン シュウヨウ ジカン ト ジョサイドウ ジッシ ガ キュウメイリツ ニ アタエル エイキョウ ニ ツイテ : ウツタイン トウケイ データ ニ ヨル 2 ホウテイシキ プロビット ・ モデル ブンセキ

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<p>This paper analyzes the one-month survival of patients with out-of-hospital cardiac arrest in Japan using the Utstein style data from April 2008 through March 2009, where the number of sample cases was 110,233. Based on the bivariate probit model, this paper derives the golden hour principle provided by Cara (1977), which describes the relationship between mortality and the time after out-of-hospital cardiac arrest, and identifies the effect of the presence of return of spontaneous circulation (ROSC). Also, the golden hour principle is drawn to each cause of cardiac arrest. By taking the presence of ROSC into account, the prediction of one-month survival improves well, compared to cases with no ROSC variable. Furthermore, the effect of defibrillation by citizens and the ambulance crew is evaluated with/without witnesses. It concludes that the effect of defibrillation by citizens is about twice than by the ambulance crew, since the timing of defibrillation by citizens is earlier than by the ambulance crew.</p>

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