Analysis Of Risk Factors And Establishment Of Prediction Model For Epileptic Seizures In Brain Arteriovenous Malformation

Objectives:Seizures are common manifestations of brain arteriovenous malformations(bAVMs).This study was conducted to investigate the baseline information and angioarchitectural features of bAVMs with seizures and construct a prediction model in order to provide guidelines for the clinical management of these patients.Methods:We collected clinical and radiological data on patients with bAVMs diagnosed by digital subtraction angiography(DSA)between January2013 and December 2020 and dichotomized the patients into the seizures and non-seizures groups.We identified differences in angiographic features.Logistic regression(LR)and random forest(RF)models were developed and compared.The diagnostic capacity was assessed using receiver operating characteristic(ROC)curves.A nomogram was constructed,and the clinical impact was determined by decision curve analysis.Results:A total of 414 patients with bAVMs were included in the analysis,of which 78(18.8%)had bAVM-related seizures.In the multivariable logistic regression(MLR)model,the location and side of bAVMs were independently associated with seizures.In RF models,the maximal diameter of veins and the cross-sectional area of feeding arteries and draining veins were the most important features.ROC curves showed that the RF model was similar to the MLR in predicting seizures.Conclusions:The angioarchitecture,side and location of bAVMs are main features associated with the occurrences of seizures with bAVMs.The RF model was similar to the MLR for bAVM-related seizure prediction.