Shinnosuke Kitano, Kei Ogawa, Yutaka Igarashi, Kan Nishimura, Shuichiro Osawa, Kensuke Suzuki, Kenji Fujimoto, Satoshi Harada, Kenji Narikawa, Takashi Tagami, Hayato Ohwada, Shoji Yokobori, Satoo Ogawa, Hiroyuki Yokota
BACKGROUND: Trauma is a serious medical and economic problem worldwide, and patients with trauma injuries have a poor survival rate following cardiac arrest. This study aimed to create a prediction model specific to prehospital trauma care and to achieve greater accuracy with techniques of machine learning. METHODS: This retrospective observational study investigated data of patients who had blunt trauma injuries due to traffic accident and fall trauma from January 1, 2018, to December 31, 2019, using the National Emergency Medical Services Information System, which stores emergency medical service activity records nationwide in the United States...
February 21, 2023: Journal of Nippon Medical School