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- W2386500645 abstract "Objective To develop a simple and easy predictive model with a high predictive accuracy,which involves variables that can be rapidly and easily achieved in daily routine practice for outcome after severe head injury. Methods C classification and regression tree (CART) technique were employed in the analysis of data from 331 patients with severe brain injury. A total of 8 prognostic indicators were selected, while Glasgow Outcome Scale(GOS) at 6 months after head injury as prognostic criterion. Results Our results indicated that Glasgow Coma Scale(GCS) was the best predictor of outcome. Glucose level,computed tomographic findings and age were proven to be strong predictors, leukocytosis on the 2nd day was found to correlate significantly with prognosis, too. The overall predictive accuracy of CART model for these data was 87.9%. All variables included in this tree have been shown to be related to outcome. Conclusion The CART were proven useful in developing a simple and effective predictive model for outcome after severe head injury,with the variables simply and easily to get." @default.
- W2386500645 created "2016-06-24" @default.
- W2386500645 creator A5046980709 @default.
- W2386500645 date "2007-01-01" @default.
- W2386500645 modified "2023-09-24" @default.
- W2386500645 title "Classification and regression tree(CART)for prediction of outcome after severe head injury." @default.
- W2386500645 hasPublicationYear "2007" @default.
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