# Using Quantitative Masticatory Dysfunction to Inform Pain Management in Trigeminal Neuralgia Through Electromyographic Monitoring

## TL;DR

This study uses a device to measure chewing patterns in trigeminal neuralgia patients, revealing distinct behaviors that could help tailor pain management strategies.

## Contribution

The study introduces electromyographic monitoring of masticatory dysfunction as a novel method to inform personalized treatment for trigeminal neuralgia.

## Key findings

- Two clusters of masticatory behavior were identified in TN patients, with Cluster 1 showing prolonged chewing duration and reduced force.
- Cluster 1 had a significantly higher prevalence of TN1 patients, suggesting a link between altered chewing patterns and trigeminal neuralgia.
- The 'Chewing' device effectively differentiated masticatory patterns, offering insights for personalized treatment approaches.

## Abstract

Trigeminal neuralgia (TN) is a rare and debilitating condition characterized by severe, episodic facial pain, with an incidence of about five individuals per 100 000 annually, predominantly affecting women aged 50–70 years. TN is often difficult to diagnose; leading to underestimation or misdiagnosis and prolonged patient suffering.

This study aimed to assess masticatory dysfunction in individuals with and without TN using an electromyographic device (“Chewing”) and evaluate its potential to quantify pain‐related dysfunction and inform treatment approaches.

This observational study assessed masticatory dysfunction in TN patients and healthy controls using “Chewing” device. Masticatory behavior was monitored with apple and carrot as test foods, and parameters such as chewing time, number of chews, and chewing force were recorded. Participants were clustered based on masticatory patterns using an unsupervised learning approach.

Two distinct clusters of masticatory behavior emerged from the analysis. Cluster 1, representing 27.5% of TN1 patients, was characterized by prolonged chewing duration, a greater number of chewing cycles, and reduced chewing force compared to Cluster 0. Specifically, during apple mastication, Cluster 1 showed a 24% increase in chewing time (p = 0.02), a twofold increase in the number of chews (p < 0.001), and a 50% reduction in chewing force (p < 0.001). When chewing carrots, the number of chews increased by 57% (p < 0.001), while chewing force decreased by 64% (p < 0.001). Chewing frequency was also significantly higher in Cluster 1 for both food types (p < 0.001). Furthermore, a higher prevalence of TN1 patients was found in Cluster 1 compared to Cluster 0 (χ2 = 4.53, p = 0.05), suggesting an association between altered masticatory behavior and trigeminal neuralgia. Nonetheless, the presence of some TN1 patients in Cluster 0 indicates that masticatory function may remain intact in certain individuals, possibly due to milder pain symptoms or the development of compensatory coping strategies.

“Chewing” device successfully quantified and differentiated masticatory patterns, providing valuable insights into functional adaptations. Subgrouping TN patients by masticatory behavior may guide personalized treatment strategies and improve patient outcomes.