Analysis of factors influencing the efficacy of vagus nerve stimulation for the treatment of drug-resistant epilepsy in children and prediction model for efficacy evaluation.

OBJECTIVE: Vagus nerve stimulation (VNS) has been widely used in the treatment of drug-resistant epilepsy (DRE) in children. We aimed to explore the efficacy and safety of VNS, focusing on factors that can influence the efficacy of VNS, and construct a prediction model for the efficacy of VNS in the treatment of DRE children.

METHODS: Retrospectively analyzed 45 DRE children who underwent VNS at Qilu Hospital of Shandong University from June 2016 to November 2022. A ≥50% reduction in seizure frequency was defined as responder, logistic regression analyses were performed to analyze factors affecting the efficacy of VNS, and a predictive model was constructed. The predictive model was evaluated by receiver operating characteristic curve (ROC), calibration curves, and decision curve analyses (DCA).

RESULTS: A total of 45 DRE children were included in this study, and the frequency of seizures was significantly reduced after VNS treatment, with 25 responders (55.6%), of whom 6 (13.3%) achieved seizure freedom. There was a significant improvement in the Quality of Life in Childhood Epilepsy Questionnaire (15.5%) and Seizure Severity Score (46.2%). 16 potential factors affecting the efficacy of VNS were included, and three statistically significant positive predictors were ultimately screened: shorter seizure duration, focal seizure, and absence of intellectual disability. We developed a nomogram for predicting the efficacy of VNS in the treatment of DRE children. The ROC curve confirmed that the predictive model has good diagnostic performance (AUC = 0.864, P < 0.05), and the nomogram can be further validated by bootstrapping for 1,000 repetitions, with a C-index of 0.837. Besides, this model showed good fitting and calibration and positive net benefits in decision curve analysis.

CONCLUSION: VNS is a safe and effective treatment for DRE children. We developed a predictive nomogram for the efficacy of VNS, which provides a basis for more accurate selection of VNS patients.