Integration of five electrophysiological test results for predicting outcome of patients with Bell's Palsy.

Objective: To integrate the results from multiple electrophysiological tests, which has the potential to significantly improve outcome predictions in patients with Bell's palsy.

Methods: This retrospective study analyzed 193 patients who were diagnosed with Bell's palsy at our Department of Physical Medicine & Rehabilitation, from January 2020 to December 2022. All patients were followed for at least 6 months, with a mean follow-up duration of 6.8 months (range: 6-9 months). Clinical data, including House-Brackmann (H-B) grade and electrophysiological data from five tests, were analyzed using multiple logistic regression analysis and decision tree analysis to predict outcome at 6 months. The five electrophysiological tests were: electroneurography degeneration index (ENoG DI), compound muscle action potential (CMAP) latency, blink reflex (BR), nerve excitability test (NET), and needle electromyography (nEMG).

Results: The decision tree model identified five key predictors of recovery: ENoG DI in the orbicularis oculi, initial H-B grade, interference pattern in orbicularis oculi, NET difference, and CMAP latency in the frontalis. Patients with an ENoG DI < 71.72% and initial H-B grade ≤ 3 had a high probability of complete recovery. For higher ENoG DI values, a NET difference ≥ 4.50 mA and CMAP latency > 3.80 ms predicted incomplete recovery. This analysis led to an overall accuracy of 86.01%.

Conclusions: This study demonstrated that the combined use of initial H-B grade with the results from multiple electrophysiological results provided reliable outcome predictions in patients with Bell's palsy.