Scientific Reports (Sep 2023)

Prehospital predicting factors using a decision tree model for patients with witnessed out-of-hospital cardiac arrest and an initial shockable rhythm

  • Kazuya Tateishi,
  • Yuichi Saito,
  • Yuichi Yasufuku,
  • Atsushi Nakagomi,
  • Hideki Kitahara,
  • Yoshio Kobayashi,
  • Yoshio Tahara,
  • Naohiro Yonemoto,
  • Takanori Ikeda,
  • Naoki Sato,
  • Hiroyuki Okura

DOI
https://doi.org/10.1038/s41598-023-43106-w
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 8

Abstract

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Abstract The effect of prehospital factors on favorable neurological outcomes remains unclear in patients with witnessed out-of-hospital cardiac arrest (OHCA) and a shockable rhythm. We developed a decision tree model for these patients by using prehospital factors. Using a nationwide OHCA registry database between 2005 and 2020, we retrospectively analyzed a cohort of 1,930,273 patients, of whom 86,495 with witnessed OHCA and an initial shockable rhythm were included. The primary endpoint was defined as favorable neurological survival (cerebral performance category score of 1 or 2 at 1 month). A decision tree model was developed from randomly selected 77,845 patients (development cohort) and validated in 8650 patients (validation cohort). In the development cohort, the presence of prehospital return of spontaneous circulation was the best predictor of favorable neurological survival, followed by the absence of adrenaline administration and age. The patients were categorized into 9 groups with probabilities of favorable neurological survival ranging from 5.7 to 70.8% (areas under the receiver operating characteristic curve of 0.851 and 0.844 in the development and validation cohorts, respectively). Our model is potentially helpful in stratifying the probability of favorable neurological survival in patients with witnessed OHCA and an initial shockable rhythm.