ArticleFrontiers in neurology2021
A Set of Eight Key Questions Helps to Classify Common Vestibular Disorders-Results From the DizzyReg Patient Registry.
Article in Frontiers in neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 17 citations in OpenAlex.
- Objective quantification of motion-induced dizziness using a proof-of-concept multimodal wearable platform.Scientific reports · 2026Article
- [The SCD diagnostic strategy, procedure and pathway for episodic vestibular syndrome].Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery · 2026Review
- Diagnostic challenges in vestibular migraine-clinical differentiation from Menière's disease and discrepancies with current classification criteria.Journal of neurology · 2025Article
- Clinical decision support for vestibular diagnosis: large-scale machine learning with lived experience coaching.NPJ digital medicine · 2025Article
- [Artificial intelligence applications in Ménière's disease].Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery · 2025Review
- Classification of Chronic Dizziness Using Large Language Models.Journal of healthcare informatics research · 2025Article
- Introducing the pictogram-based ocular motor and visual-perceptual symptom scale: a multinational, cross-cultural feasibility study.Frontiers in neurology · 2025Article
- [SCD programmatic diagnostic strategy and diagnostic pathway for vertigo disease].Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery · 2024Article
- Patients' Experiences with Management of Benign Paroxysmal Positional Vertigo: Insights from the Vestibular Disorders Association Registry.Patient related outcome measures · 2022Article
- History Taking in Non-Acute Vestibular Symptoms: A 4-Step Approach.Journal of clinical medicine · 2021Article
- Machine Learning Techniques for Differential Diagnosis of Vertigo and Dizziness: A Review.Sensors (Basel, Switzerland) · 2021Review
- Using Base-ml to Learn Classification of Common Vestibular Disorders on DizzyReg Registry Data.Frontiers in neurology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Precise history taking is the key to develop a first assumption on the diagnosis of vestibular disorders. Particularly in the primary care setting, algorithms are needed, which are based on a small number of questions and variables only to guide appropriate diagnostic decisions. The aim of this study is to identify a set of such key variables that can be used for preliminary classification of the most common vestibular disorders. A four-step approach was implemented to achieve this aim: (1) we conducted an online expert survey to collect variables that are meaningful for medical history taking, (2) we used qualitative content analysis to structure these variables, (3) we identified matching variables of the patient registry of the German Center for Vertigo and Balance Disorders, and (4) we used classification trees to build a classification model based on these identified variables and to analyze if and how these variables contribute to the classification of common vestibular disorders. We included a total of 1,066 patients with seven common vestibular disorders (mean age of 51.1 years, SD = 15.3, 56% female). Functional dizziness was the most frequent diagnosis (32.5%), followed by vestibular migraine (20.2%) and Menière's disease (13.3%). Using classification trees, we identified eight key variables which can differentiate the seven vestibular disorders with an accuracy of almost 50%. The key questions comprised attack duration, rotational vertigo, hearing problems, turning in bed as a trigger, doing sport or heavy household chores as a trigger, age, having problems with walking in the dark, and vomiting. The presented algorithm showed a high-face validity and can be helpful for taking initial medical history in patients with vertigo and dizziness. Further research is required to evaluate if the identified algorithm can be applied in the primary care setting and to evaluate its external validity.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.