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Development of a Decision Tree Analysis model that predicts recovery from acute brain injury
Author(s) -
OH Hyun Soo,
SEO Wha Sook
Publication year - 2013
Publication title -
japan journal of nursing science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.363
H-Index - 17
eISSN - 1742-7924
pISSN - 1742-7932
DOI - 10.1111/j.1742-7924.2012.00215.x
Subject(s) - glasgow coma scale , medicine , intensive care unit , traumatic brain injury , emergency medicine , glasgow outcome scale , blood pressure , intensive care medicine , anesthesia , psychiatry
Aim: The present study was conducted to identify significant demographic, illness‐related, and physiological factors associated with recovery at 1 month after brain injury, and to develop and evaluate a Decision Tree Analysis‐based prediction model. Methods: This study was conducted using a prospective study design. The study subjects were 190 adult patients with brain injury admitted to the neurological intensive care unit of a university hospital located in Incheon, South Korea. Degree of recovery from brain injury was evaluated 1 month after admission using the Glasgow Outcome Scale. Results: A prediction model was developed using Decision Tree Analysis. The most significant predictor of recovery at 1 month after brain injury using the devised model was Glasgow Coma Scale score on admission, and its optimum cut‐off value for the differentiation of good and poor recovery was 8.5. The next best predictors were age and blood glucose level on admission, which had cut‐off values of 49.5 years and 155 mg/dL, respectively. In addition, hematoma volume, systolic blood pressure, and respiratory rate on admission were also found to predict 1 month recovery significantly, with corresponding cut‐off values of 44 cc, 168 mmHg, and 29/min, respectively. Conclusion: The developed model includes common and routinely used monitoring parameters as significant predictors, and proposes cut‐off values for these predictors. This model appears to be useful for predicting 1 month recovery in various brain injury types. The authors believe that the devised model provides a basis for the evidence‐based nursing care of brain injured patients during the acute stage.