Background: Artificial intelligence models can learn from medical literature and clinical cases and generate answers that rival human experts. However, challenges remain in the analysis of complex data containing images and diagrams. Objective: This study aims to assess the answering capabilities and accuracy of ChatGPT-4 Vision (GPT-4V) for a set of 100 questions, including image-based questions, from the 2023 otolaryngology board certification examination. Methods: Answers to 100 questions from the 2023 otolaryngology board certification examination, including image-based questions, were generated using GPT-4V. The accuracy rate was evaluated using different prompts, and the presence of images, clinical area of the questions, and variations in the answer content were examined. Results: The accuracy rate for text-only input was, on average, 24.7% but improved to 47.3% with the addition of English translation and prompts (P<.001). The average nonresponse rate for text-only input was 46.3%; this decreased to 2.7% with the addition of English translation and prompts (P<.001). The accuracy rate was lower for image-based questions than for text-only questions across all types of input, with a relatively high nonresponse rate. General questions and questions from the fields of head and neck allergies and nasal allergies had relatively high accuracy rates, which increased with the addition of translation and prompts. In terms of content, questions related to anatomy had the highest accuracy rate. For all content types, the addition of translation and prompts increased the accuracy rate. As for the performance based on image-based questions, the average of correct answer rate with text-only input was 30.4%, and that with text-plus-image input was 41.3% (P=.02). Conclusions: Examination of artificial intelligence’s answering capabilities for the otolaryngology board certification examination improves our understanding of its potential and limitations in this field. Although the improvement was noted with the addition of translation and prompts, the accuracy rate for image-based questions was lower than that for text-based questions, suggesting room for improvement in GPT-4V at this stage. Furthermore, text-plus-image input answers a higher rate in image-based questions. Our findings imply the usefulness and potential of GPT-4V in medicine; however, future consideration of safe use methods is needed.

Background: Dizziness and vertigo can be caused by various factors, such as peripheral vestibular and central disorders. Although consultations with specialists are advisable when necessary, patients with severe vertigo symptoms may have limited mobility, which may interfere with hospital visits. The spread of COVID-19 has further limited the number of hospital visits for patients with dizziness; therefore, a method of medical care that enables more accurate treatment under time and geographical constraints is needed. Telemedicine has become widespread, owing to the popularity of smartphone and tablet devices in recent years, and the use of devices and systems has made it possible to provide efficient medical care. However, no previous scoping review has mapped existing studies on telemedicine for vertigo and dizziness, and no recommendations have been made regarding which devices and systems should be used for specific diseases.Objective: The aim of this review was to map and assess previous studies on the use of information communications technology, smartphones, and apps for treating patients with vertigo and discuss the added value of introducing telemedicine to improve the quality of medical care and create an environment that builds security and trust among patients.Methods: A scoping review was conducted with the methodological framework of Arksey and O’Malley and in accordance with the of the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews) guidelines. The PubMed, MEDLINE, and Cochrane Library databases were searched to retrieve previous reports on smartphone-assisted telemedicine treatment for vertigo published between January 2000 and May 2023. Two authors independently assessed eligibility and extracted data.Results: This review included 20 papers that reported devices or systems for telemedicine for vestibular dysfunction. Among studies that reported the use of a device or app, 2 were related to anamnesis and subjective symptoms, 12 were related to objective examination, 7 were related to remote diagnosis, and 7 were related to treatment and rehabilitation.Conclusions: With the advancement of technology, the use of telemedicine in patients with dizziness may be feasible. In the future, it will be necessary to consider how telemedicine can be used in dizziness treatment and develop an effective treatment system combining in-person medical care and the effective use of devices for the management of severe vertigo and related diseases. The smooth introduction of telemedicine in vertigo treatment is expected to improve the quality of treatment, increase opportunities for patients to receive medical care, and reduce time and travel costs, leading to a sense of security and trust among patients.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: The subjective visual vertical (SVV) test can evaluate otolith function and spatial awareness and is performed in dedicated vertigo centers using specialized equipment; however, it is not otherwise widely used because of the specific equipment and space requirements. An SVV test smartphone app was developed to easily perform assessments in outpatient facilities. Objective: This study aimed to verify whether the SVV test smartphone app with commercially available virtual reality goggles can be used in a clinical setting. Methods: The reference range was calculated for 15 healthy participants. We included 14 adult patients with unilateral vestibular neuritis, sudden sensorineural hearing loss with vertigo, and Meniere disease and investigated the correlation between the SVV test results and vestibular evoked myogenic potential (VEMP) results. Results: The SVV reference range of healthy participants for the sitting front-facing position was small, ranging from –2.6º to 2.3º. Among the 14 patients, 6 (43%) exceeded the reference range for healthy participants. The SVV of patients with vestibular neuritis and sudden sensorineural hearing loss tended to deviate to the affected side. A total of 9 (64%) had abnormal cervical VEMP (cVEMP) values and 6 (43%) had abnormal ocular VEMP (oVEMP) values. No significant difference was found between the presence or absence of abnormal SVV values and the presence or absence of abnormal cVEMP and oVEMP values; however, the odds ratios (ORs) suggested a higher likelihood of abnormal SVV values among those with abnormal cVEMP and oVEMP responses (OR 2.40, 95% CI 0.18-32.88; P>.99; and OR 2, 95% CI 0.90-4.45; P=.46, respectively). Conclusions: The SVV app can be used anywhere and in a short period while reducing directional bias by using virtual reality goggles, thus making it highly versatile and useful as a practical otolith dysfunction screening tool.

Background: Persistent postural-perceptual dizziness (PPPD) is a relatively new disease entity, with diagnostic criteria published by the Bárány Society. PPPD is often preceded by a peripheral or central vestibular disorder. It is not clear how coexisting deficits due to preceding vestibular disorders affect PPPD symptoms.Objective: This study aimed to characterize the clinical features of PPPD with or without isolated otolith dysfunction using vestibular function tests.Methods: The study included 43 patients (12 males and 31 females) who were diagnosed with PPPD and completed oculomotor-vestibular function tests. The Dizziness Handicap Inventory (DHI), Hospital Anxiety and Depression Scale (HADS), Niigata PPPD Questionnaire (NPQ), and Romberg test for stabilometry were examined. The 43 patients with PPPD were classified into four categories based on vestibular evoked myogenic potential (VEMP) and video head impulse test (vHIT) results: normal function for both semicircular canals and otoliths (normal), isolated otolith dysfunction (iOtoDys), isolated semicircular canal dysfunction (iCanalDys), and dysfunction of both otoliths and semicircular canals (OtoCanalDys).Results: Among the 43 patients with PPPD, the iOtoDys group was the largest (44.2%), followed by the normal group (37.2%), iCanalDys group (9.3%), and OtoCanalDys group (9.3%). Eight of the 19 iOtoDys patients showed both abnormal cVEMP and oVEMP responses unilaterally or bilaterally (both sacculus and utriculus damage type), whereas 11 showed either an abnormal cVEMP or an abnormal oVEMP response (either sacculus or utriculus damage type). In a three-group comparison of the both sacculus and utriculus damage type, the either sacculus or utriculus damage type, and the normal group, the mean total, functional, and emotional DHI scores were significantly higher for the both sacculus and utriculus damage type than for the either sacculus or utriculus damage type. The Romberg ratio, a measure of stabilometry, was significantly higher for the normal group than for the both sacculus and utriculus damage type and the sacculus or utriculus damage type in the iOtoDys group.Conclusions: The coexistence of sacculus and utriculus damage may exacerbate dizziness symptoms in patients with PPPD. Determining the presence and extent of otolith damage in PPPD may provide useful information on the pathophysiology and treatment strategies of PPPD.

Background: Conventional nystagmus classification methods often rely on subjective observation by specialists, which is time-consuming and variable among clinicians. Recently, deep learning techniques have been used to automate nystagmus classification using convolutional and recurrent neural networks. These networks can accurately classify nystagmus patterns using video data. However, associated challenges including the need for large datasets when creating models, limited applicability to address specific image conditions, and the complexity associated with using these models. Objective: This study aimed to evaluate a novel approach for nystagmus classification that used the Generative Pre-trained Transformer 4 Vision (GPT-4V) model, which is a state-of-the-art large-scale language model with powerful image recognition capabilities. Methods: We developed a pupil-tracking process using a nystagmus-recording video and verified the optimization model’s accuracy using GPT-4V classification and nystagmus recording. We tested whether the created optimization model could be evaluated in six categories of nystagmus: right horizontal, left horizontal, upward, downward, right torsional, and left torsional. The traced trajectory was input as two-dimensional coordinate data or an image, and multiple in-context learning methods were evaluated. Results: The developed model showed an overall classification accuracy of 37% when using pupil-traced images and a maximum accuracy of 24.6% when pupil coordinates were used as input. Regarding orientation, we achieved a maximum accuracy of 69% for the classification of horizontal nystagmus patterns but a lower accuracy for the vertical and torsional components. Conclusions: We demonstrated the potential of versatile vertigo management in a generative artificial intelligence model that improves the accuracy and efficiency of nystagmus classification. We also highlighted areas for further improvement, such as expanding the dataset size and enhancing input modalities, to improve classification performance across all nystagmus types. The GPT-4V model validated only for recognizing still images can be linked to video classification and proposed as a novel method.

Although dizziness is one of the most common symptoms of menopause, the underlying mechanism is not precisely known. Therefore, this study aimed to investigate the prevalence of, and the factors associated with, dizziness in peri- and postmenopausal women. We conducted a cross-sectional study in which we analyzed the first-visit records of 471 Japanese women aged 40 to 65 years who enrolled in a health and nutrition education program at a menopause clinic. The prevalence of dizziness was estimated according to the participants’ responses to the Menopausal Health-Related Quality of Life Questionnaire. The background characteristics of age, menopause status, body composition, cardiovascular parameters, basal metabolism, and physical fitness; other menopausal symptoms, including vasomotor, insomnia, depression, and anxiety symptoms; and lifestyle characteristics were assessed for their associations with dizziness. The percentage of women who suffered from dizziness once a week or more frequently was 35.7%. Compared to the women without dizziness, those with the symptom were younger; had a higher body weight, body mass index, body fat percentage, muscle mass, and waist-to-hip ratio; had higher systolic pressure; were slower in reaction time; had higher physical and psychological symptom scores of menopause; exercised less regularly; and consumed less alcohol. A multivariate logistic regression analysis revealed that the anxiety symptom, which was evaluated by the Hospital Anxiety and Depression Scale, was the sole factor that was independently associated with dizziness (adjusted odds ratio 1.14; 95% confidence interval 1.08–1.20). Dizziness is highly prevalent in Japanese peri- and postmenopausal women and it is associated with anxiety. The treatment of anxiety in this population might improve the symptom.