Damage Control Indication Detecting score (DECIDE score) from Japan Trauma Data Bank

DOI Open Access
  • Murata Kiyoshi
    Emergency Medical Center, Matsudo City Hospital
  • Sekiya Kosuke
    Shock Trauma and Emergency Medical Center, Tokyo Medical and Dental University Hospital Faculty of Medicine
  • Otomo Yasuhiro
    Shock Trauma and Emergency Medical Center, Tokyo Medical and Dental University Hospital Faculty of Medicine
  • Saitoh Daizoh
    Division of Traumatology, Research Institute, National Defense Medical College

Bibliographic Information

Other Title
  • Damage Control Surgeryの新しい適応基準

Description

<p>There has been much debate about the indications for damage control surgery (DCS). We analyzed the data of trauma patients who underwent laparotomy from the Japan Trauma Data Bank, and discovered many differences in the vital signs on arrival at the ER between the DCS group (n=532) and the no -DCS group (n=3915). The positivity rate of FAST, the blood transfusion rate, and the mortality rate were also significantly different between the groups. Logistic regression analysis identified the heart rate, level of consciousness, body temperature and injury mechanism as independent predictors of DCS. By categorizing and weighting of these predictors, we developed a prediction score for DCS, named the damage control indication detecting score (DECIDE score). The DECIDE score consists of three predictors (body temperature, level of consciousness and injury mechanism) and was found to be correlated with the mortality. With a cutoff value of the score of 5, the mortality rate, sensitivity and specificity were calculated to be 30.8%, 64.8% and 70.0%, respectively. The DECIDE scale enables prediction of DCS in the pre -hospital condition also, because only physical findings and clinical information are needed to calculate the score. Further validation study is warranted for the DECIDE score.</p>

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Details 詳細情報について

  • CRID
    1390282679713539456
  • NII Article ID
    130005290469
  • DOI
    10.11231/jaem.36.1023
  • ISSN
    18824781
    13402242
  • Text Lang
    ja
  • Article Type
    journal article
  • Data Source
    • JaLC
    • CiNii Articles
    • KAKEN
  • Abstract License Flag
    Disallowed

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