ObjectiveTo investigate the establishment of a risk nomogram model for predicting vagus excitatory response in patients with functional epilepsy after radiofrequency thermocoagulation.MethodsA total of 106 patients with epilepsy admitted to the neurosurgery department of our hospital from January 2016 to June 2020 were selected and divided into the Vagus excitatory response (VER) group and the non-VER group according to their occurrence or absence. Logistic regression analysis was used to screen out the risk factors of VER during SEEG-guided Percutaneous radiofrequency thermocoagulation (PRFT) in patients with functional epilepsy, and R software was used to establish a histogram model affecting VER in SEEG-guided PRFT. Bootstrap method was used for internal verification. C-index, correction curve and ROC curve were used to evaluate the prediction ability of the model.ResultsLogistic regression analysis showed that age [OR=0.235, 95%CI (0.564, 3.076)], preoperative fugl-meyer score [OR=4.356, 95%CI (1.537, 6.621)], depression [OR=0.995, 95%CI (1.068, 7.404)], and lesion range [OR=1.512, 95%CI (0.073, 3.453)] were independent risk factors for the occurrence of VER in PRFT under the guidance of SEEG (P<0.05), and were highly correlated with the occurrence of VER in PRFT. Based on the above six indicators, a SEEG-guided colograph model of VER risk in PRFT was established, and the model was validated internally. The results showed that the C-index of the modeling set and validation set were 0.779 [95%CI (0.689, 0.869)] and 0.782 [95%CI (0.692, 0.872)], respectively. The calibration curves of the two groups fit well with the standard curves. The areas under the ROC curve (AUC) of the two groups were 0.779 and 0.782 respectively, which proved that the model had good prediction accuracy.ConclusionFor patients with functional epilepsy requiring seeg-guided PRFT therapy, age, preoperative Fugl-meyer score, depression and lesion range should be taken into full consideration to comprehensively assess the incidence of VER, and early intervention measures should be taken to reduce and reduce the incidence, which has good clinical application value.