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

PURPOSE: 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%.

CONCLUSION

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.