Baseline patient-reported and demographic predictors of gait response after vestibular implantation in adults with bilateral vestibulopathy

Introduction: Bilateral vestibulopathy (BVP) is characterized by bilateral loss of vestibular function which severely impacts gait, balance, and quality of life (Strupp et al., 2017). As a result, patients receive little to no input from the vestibular organs, which leads to ongoing problems with balance, instability, and oscillopsia. The prevalence of BVP was estimated at 28 per 100,000 individuals in the United States in 2008 (Ward et al., 2013). This corresponds to approximately 126,000 individuals with BVP in the European Union and an estimated 2,240,000 people worldwide, based on EU-stats (Eurostat, n.d.) and UN data (United Nations Population Fund, n.d.).Vestibular rehabilitation therapy (VRT) is currently the standard treatment for BVP; however, patient outcomes vary considerably. Individuals with severe bilateral vestibular loss often achieve only limited functional improvement (Grill et al., 2018; Herdman et al., 2015). Consequently, several studies have highlighted the need to identify baseline characteristics that can predict response to VRT. In patients with bilateral vestibular hypofunction, factors such as age, baseline Dynamic Gait Index (DGI), gait speed, and perceived imbalance have been linked to rehabilitation outcomes (Herdman et al., 2015). In real-world clinical settings, higher baseline scores on the Dizziness Handicap Inventory (DHI) and the Vestibular Disorders Activities of Daily Living scale have been associated with better outcomes, while elevated levels of psychological distress have been linked to poorer results (Kim et al., 2024).In addition, fear of falling and confidence in maintaining balance are important considerations in vestibular rehabilitation. The Falls Efficacy Scale–International (FES-I) is a widely used 16-item questionnaire that assesses concerns about falling during everyday activities (Shirley Ryan AbilityLab, 2017). Given that demographic factors, DHI and FES-I play a role in predicting or interpreting outcomes of VRT, it is relevant to investigate whether these variables may also help explain improvements in functional gait following vestibular implantation.Methods: Data is used from the completed BionicVEST study (Ramos-de-Miguel et al., 2025), combined with the ongoing BionicVEST2 study; a prospective, multicentric, staged feasibility clinical trial evaluating a second-generation otolith-targeted vestibular implant in adults with BVP (Cochlear, 2026). The implant system is designed to provide continuous electrical pulse trains to the inferior vestibular nerve through a dedicated vestibular electrode array and is evaluated using clinical, vestibular, hearing, safety and patient-reported outcome measures.The objective of this exploratory analysis framework is to evaluate whether baseline patient-reported outcomes and demographics may serve as predictors of functional gait response after otolith-targeted vestibular implantation in adults with BVP. Candidate predictors include demographic variables such as age, sex and duration of BVP, baseline DHI and baseline FES-I. Functional gait response is assessed using the DGI as a primary functional gait endpoint in the BionicVEST clinical trials (Cochlear, 2026; Ramos-de-Miguel et al., 2025).Results: While data acquisition is ongoing, data is available from 11 participants with a mean age of 57 ± 15 years from the BionicVEST study and partly available from 12 participants with a mean age of 64 ± 10 years from the BionicVEST2 study. 17 out of the 23 participants in total have 2- (BionicVEST) to 3-month (BionicVEST2) post-implant activation data which are pooled for this analysis. Of those, 9/17 participants (53 %) are “responders” (i.e., ≥ 4 points improvement on the DGI). Excluding three patients who are at risk for ceiling effect (baseline DGI score ≥ 20) and one wheelchair bound participant gives a response rate of 69 %. While age (r = −0.39, R² = 0.15), sex (r = 0.36, R² = 0.13), BVP duration (r = −0.42, R² = 0.17), and baseline FES-I (r = 0.28, R² = 0.08) were not statistically significant, baseline DHI was statistically significant correlated with DGI change at 2 to 3 months (r = 0.57, R² = 0.32, p<0.05).Conclusions: If demographic variables such as age, sex and duration of BVP, baseline DHI and baseline FES-I are associated with DGI change after vestibular implantation, these measures could support responder characterization, patient counselling, expectation management and future study design. Conversely, if predictors established or considered relevant in VRT do not translate to vestibular implantation, this may suggest that implant-mediated gait improvement is influenced by different mechanisms than rehabilitation response alone. Evaluating these parameters in the BionicVEST cohorts may help identify factors associated with improvement in DGI and support the development of more personalized approaches to vestibular implant counselling, rehabilitation and outcome interpretation.Acknowledgements: The BionicVEST projects received funding from the European Union under the H2020 project grant 801127 and EIC Transition grant 101112779.