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BACKGROUND: Patients with vestibular loss have reduced wayfinding ability, but the association between vestibular loss and impaired steering spatial navigation is unclear. OBJECTIVE: To evaluate whether vestibular loss is associated with reduced steering navigation performance in a virtual reality (VR) environment containing obstacles. METHODS: 17 ambulatory adults with vestibular loss were age/sex-matched to healthy controls. Participants traversed a VR hallway with obstacles, and their navigation performance was compared using metrics such as collisions, time, total distance travelled, and speed in single and multivariate analysis. RESULTS: In univariate analysis there was no significant difference in collisions between vestibular patients and controls (1.84 vs. 2.24, p = 0.974). However, vestibular patients took more time, longer routes, and had lower speeds to complete the task (56.9 vs. 43.9 seconds, p < 0.001; 23.1 vs. 22.0 meters, p = 0.0312; 0.417 vs. 0.544 m/s, p < 0.001). These results were confirmed in multivariate analysis. CONCLUSIONS: This study found that patients with vestibular loss displayed slower gait speeds and traveled longer distances, though did not make more collisions, during a VR steering navigation task. Beyond the known influence of vestibular function on gait speed, vestibular loss may also contribute to less efficient steering navigation through an obstacle-laden environment, through neural mechanisms that remain to be elucidated.

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Objectives: To develop a novel remote head impulse test (rHIT), and to provide preliminary data validating the rHIT vestibular-ocular reflex (VOR) gains against the in-clinic vHIT. Methods: A convenience sample of 10 patients referred for vestibular assessment at our institution was recruited. In-clinic vHIT was used to quantify lateral VOR gains. Patients subsequently underwent an rHIT protocol, whereby patients performed active, lateral head rotations while their eyes and heads were recorded using a laptop camera and video-conferencing software. The vHIT and rHIT VOR gains were compared using paired t-tests, and a Pearson correlation coefficient between the gains was calculated. Absolute accuracy, sensitivity, and specificity of the rHIT were additionally calculated. Results: Of the 10 patients recruited, 4 were male, and the average ± standard deviation (SD) age was 61.4 ± 15.3 years. As determined by the vHIT, 2 patients had normal bilateral VOR gains, 6 with unilateral vestibular hypofunction, and 2 with bilateral vestibular hypofunction. The correlation between the rHIT and vHIT gains was 0.73 (p < .001). The rHIT exhibited an absolute accuracy of 75.0%, sensitivity of 70.0%, and specificity of 80.0%. When ears had a vHIT VOR gain less than 0.40, the rHIT exhibited 100.0% accuracy. Conversely, 60.0% of deficient ears with vHIT VOR gains greater than 0.40 were incorrectly categorized by the rHIT. Conclusion: The rHIT may be better suited for detecting more severe vestibular deficiencies. Future iterations of the rHIT should aim to increase the video frame-rate capabilities to detect subtler VOR impairments. Level of Evidence: 4.

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Objectives: Cochlear implants (CI) are reliable implantable devices that are highly cost-effective in reducing the burden of hearing loss at an individual and societal scale. However, only 10% of CI candidates are aware of their candidacy and receive a CI. A web-based screening tool to assess CI candidacy may make many more individuals aware of their candidacy for cochlear implantation. The objective of this study was to validate and optimize the online Cochlear Implant Candidacy Calculator against in-clinic audiometric testing. Methods: Audiogram data and word discrimination scores for 132 patients who underwent initial CI consultation at the Johns Hopkins Cochlear Implant Center in 2020 were inputted into the calculator. Candidacy results from the calculator were compared against formal clinical diagnoses provided by the audiologist at the time of visit. Receiver Operating Characteristic (ROC) and Area Under the Curve (AUC) analyses were performed to identify optimal diagnostic thresholds. Results: Of the resulting 132 patients, 54 presented with single-sided deafness (SSD), and 114 were clinically determined to be CI candidates. ROC AUC analyses identified optimal thresholds of high-frequency PTA ≥65 dB and word discrimination score ≤ 50%. To maximize sensitivity at the expense of specificity, diagnostic thresholds of high-frequency PTA ≥ 65 dB and word discrimination score ≤ 70% were chosen, which yielded accuracy, sensitivity, specificity, and ROC AUC of 0.90, 0.94, 0.82, and 0.88, respectively. Conclusion: The novel online CI Candidacy Calculator exhibits high sensitivity and accuracy, and moderate specificity. The calculator may thereby be useful in increasing awareness of potential CI candidacy, increasing prevalence of CIs, and decreasing the burden of hearing loss.

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The human oral mucosa hosts a diverse microbiome and is exposed to potentially toxic biomaterials from dental restoratives. Mucosal health is partly determined by cell and tissue responses to challenges such as dental materials and pathogenic bacteria. An in vitro model to rapidly determine potential layer-specific responses would lead to a better understanding of mucosal homeostasis and pathology. Therefore, this study aimed to develop a co-cultured microfluidic mucosal model on-a-chip to rapidly assess mucosal remodeling and the responses of epithelial and subepithelial layers to challenges typically found in the oral environment. A gingival fibroblast-laden collagen hydrogel was assembled in the central channel of a three-channel microfluidic chamber with interconnecting pores, followed by a keratinocyte layer attached to the collagen exposed in the pores. This configuration produced apical and subepithelial side channels capable of sustaining flow. Keratinocyte, fibroblast, and collagen densities were optimized to create a co-culture tissue-like construct stable over one week. Cells were stained and imaged with epifluorescence microscopy to confirm layer characteristics. As proof-of-concept, the mucosal construct was exposed separately to a dental monomer, 2-hydroxylethyl methacrylate (HEMA), and the oral bacteria Streptococcus mutans. Exposure to HEMA lowered mucosal cell viability, while exposure to the bacteria lowered trans-epithelial electrical resistance. These findings suggest that the oral mucosa-on-a-chip is useful for studying oral mucosal interactions with bacteria and biomaterials with a histology-like view of the tissue layers.