Analysis of the Risk Factors for De Novo Subdural Hygroma in Patients with Traumatic Brain Injury Using Predictive Modeling and Association Rule Mining

Abstract

The relationship between risk factors for de novo hygroma in patients with traumatic brain injury (TBI) was investigated. We collected data on 222 patients with TBI to determine the risk factors for de novo hygroma, including sex, age, centrum semiovale perivascular space (CSO-PVS) grade, trauma cause, hypertension, and diabetes. The importance of the risk factors was analyzed, and the feature contribution of the risk factors to all patients and each patient was analyzed using predictive modeling. Additionally, association rule mining was performed to determine the relationship between all factors, and the performance metrics of the predictive model were calculated. The overall feature importance was analyzed in the order of age, CSO-PVS, hypertension, and trauma cause. However, trauma cause, underlying disease, age, and sex as risk factors were different for a specific patient through the individual feature analysis. The mean area under the curve for the predictive model was 0.80 ± 0.04 using K-fold cross validation. We analyzed the risk factors for de novo hygroma in TBI and identified detailed relationships. Age and CSO-PVS severity were strongly correlated with de novo hygroma. Furthermore, according to the results of feature importance analysis and association rule mining, the significance of the risk factors may vary in each individual patient.