Prediction of early recovery in patients with acute peripheral facial paralysis using serial electroneuronography.

OBJECTIVES: This study aimed to determine the preferred timing and measurement sites for electroneuronography (ENoG) to predict early recovery from acute peripheral facial paralysis. METHODS: We retrospectively evaluated 42 patients with acute peripheral facial paralysis who received standard treatment with oral corticosteroids. The severity of facial paralysis was assessed at the initial visit and after 1 month using the House-Brackmann grading system. Patients were classified into recovery and non-recovery groups according to changes in the grade. ENoG was performed at the initial visit and after 2 weeks. ENoG amplitudes of four facial muscles (frontalis, nasalis, orbicularis oculi, and orbicularis oris) at the initial visit and after 2 weeks, as well as age, sex, affected side, and diagnosis, were compared between the two groups. RESULTS: No differences were observed in degeneration ratios across all subsites in the initial ENoG, which can be explained by the fact that Wallerian degeneration is not yet complete at this early stage. However, the second ENoG, performed after degeneration had progressed, showed significant differences across all subsites. Binary logistic regression analysis revealed that the degeneration ratio of the orbicularis oris muscle was the best predictor of early recovery (odds ratio, 0.961; p = 0.014). Receiver operating characteristic curve analysis also revealed that the degeneration ratios of all subsites measured in the second ENoG were useful in predicting early recovery, with the highest possibility at the orbicularis oris muscle (area under the curve = 0.789). When the degeneration ratio exceeded 60% in all subsites in the second ENoG, a favorable prognosis was not expected. CONCLUSION: This study provides the preferred testing time and measurement sites for ENoG to predict early recovery from facial paralysis. Given the personal and social impact of facial paralysis, predicting early recovery is crucial for reassuring patients, providing better treatment, and encouraging early reintegration into society.