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Updated: May 6, 2026

Facial Nerve Surgery in the Rat Model to Study Axonal Inhibition and Regeneration
Published on: May 5, 2020
Optimizing total facial nerve patient management for effective clinical outcomes research
Prabhat Bhama1, Richard E Gliklich2, Julie S Weinberg3
1Division of Facial Plastic and Reconstructive Surgery, Department of Otology and Laryngology, Harvard Medical School/Massachusetts Eye and Ear Infirmary, Boston2Harvard School of Public Health, Boston, Massachusetts4Facial Nerve Center, Massachusetts Eye.
Importance:
Assessment of outcomes in patients with facial paralysis is challenging owing to the lack of objective tools to evaluate facial function and suboptimal data collection.
Objective:
To describe a methodology for prospective evaluation of patients with facial paralysis that permits optimal assessment of clinical outcomes.
Design, Setting, And Participants:
At the Massachusetts Eye and Ear Infirmary, we have treated over 2000 patients with facial nerve injury since 2002. To better quantify and improve our outcomes, we have developed what we now believe represents a systematic method for the previsit evaluation, intake, management, and follow-up of our facial nerve patients to optimize data collection for the purposes of clinical outcome studies, as detailed in this retrospective descriptive study.
Results:
Data collection is often poor if there is not a specific individual delegated to the task and is particularly challenging in the intraoperative setting. Retrospective acquisition of data are inherently less accurate and time consuming. A user-friendly searchable database is required to use the collected data.
Conclusions And Relevance:
Clinical outcomes research in the field of facial paralysis requires meticulous attention to comprehensive data collection at appropriate time points, precision photography, and the use of available quality of life and objective measurement tools. Ideally, a standardized approach for data collection would be adopted that would permit multi-institutional data analysis to improve the quality of outcomes research currently available.
Level Of Evidence:
NA.
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