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内容記述 |
Objective: We aimed to create a new prognostic prediction score model for severe trauma patients: by using the Japanese nationwide trauma registry, which is focused on patient transportation time,: the treatment provided by emergency medical services, and the variations in the vital signs of the: patients before and after arrival at the hospital.: Methods: A multicenter retrospective cohort study was conducted in Japan. We collected data from: the Japan Trauma Data Bank (JTDB) . We included the words “adult” and “shock” (systolic blood: pressure < 90 mmHg) in our search, and then considered age, sex, treatment before hospital arrival,: variations in the vital signs and transportation time. The outcome was the status at hospital discharge: (dead/alive). A stepwise logistic regression model was constructed for the model development and: the bootstrapping method was used for internal validation.: Results: A total of 4,881 patients were included, and mortality was 10.5%. According to: multivariate analysis, predictors for death included age (4 categories), type of injury (2 categories),: treatment before hospital arrival (2 categories), variation in systolic blood pressure (6 categories),: variation in respiratory rate (5 categories) and transportation time (2 categories). The AUC (area: under the receiver operating characteristic curve) was 0.726 (95% CI, 0.702 – 0.749). Our prediction: model was validated internally by a bootstrapping method.: Conclusion: We suggest a new prognostic prediction model for severe trauma patients that consists: of six predictors and is focused on variations in vital signs. This score can be calculated just after the: patient’s arrival at the hospital. |
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論文要旨 (93.1 kB)
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