Microvascular Decompression and Trigeminal Neuralgia: Patient Sentiment Analysis Using Natural Language Processing.

Objective: Microvascular decompression (MVD) as a treatment for trigeminal neuralgia (TGN) has high success rate but is associated with risks of complication. This study analyzes Twitter to provide insights into discussions surrounding MVD for patients with TGN.

Methods: A Twitter search performed in April 2022 yielded 491 tweets from 426 accounts. Tweets and accounts were classified thematically, and descriptive statistics were used for various social media metrics. Using a natural language processing machine learning algorithm, sentiment analysis (SA) was performed to evaluate patient perspectives before and after surgery, and a multivariate regression model was used to identify predictors of higher engagement metrics (likes, retweets, quote tweets, replies).

Results: Most accounts were patients, caregivers, and other members of the public (70%). The most encountered themes were research (47%) and personal experiences (33.4%). SA of tweets about patient experiences showed that 40.2% of tweets were positive, 31.1% were neutral and 28.7% were negative. Negative tweets decreased significantly in postoperative tweets and mostly discussed complications or failure of surgery (63%). On multivariate analysis, only inclusion of media (photo or video) in a Tweet was associated with higher engagement metrics.

Conclusions: This study provides a comprehensive review of Twitter use discussing MVD in TGN and is the first to assess patient satisfaction after treatment using SA. The data presented on patient perspectives on social media could help physicians establish direct lines of communication with patients, fostering a more patient-focused care.