Predicting epilepsy surgery outcome in adult patients: May psychiatric diagnosis improve predictive models?

With this study, we aimed to assess the importance of including psychiatric disorders in a comprehensive prediction model for epilepsy surgery.

Ambispective observational study with a sample of adults who underwent resective surgery. Participants were evaluated, before and one year after surgery, to collect data regarding their neurological and psychiatric history. The one-year post-surgical outcome was classified according to the Engel Outcome Scale. Previously identified predictors of post-surgical Engel Class were included in a logistic regression model. Then, the accuracy of alternative predictive models, including or excluding, past and current psychiatric diagnoses, were tried.

One hundred and forty-six people participated in this study. The inclusion of psychiatric diagnosis resulted in a model with a higher AUC curve, however, the Delong method showed no significant statistical differences between the models.

Despite the fact that presurgical psychiatric diagnoses have shown to contribute to the prediction of epilepsy surgery outcome they do not contribute to a significant improvement of predictive models.