Developing a Diagnostic Algorithm for Identifying Vestibular Neuronitis in Acute Dizziness: An Overview of Epidemiology, Pathogenesis, and Evidence-Based Guidelines for Diagnostic Approaches

TL;DR

This paper proposes a diagnostic algorithm for vestibular neuronitis, a condition causing sudden vertigo, to improve accurate diagnosis and clinical decision-making.

Contribution

A new evidence-based diagnostic algorithm for vestibular neuronitis is proposed to differentiate it from similar disorders.

Findings

A literature review of 114 studies informed the development of a diagnostic algorithm for vestibular neuronitis.

The algorithm emphasizes clinical history and bedside exams, supported by ancillary tests for accurate diagnosis.

The approach aims to distinguish VN from central and other peripheral causes of vertigo.

Abstract

Vestibular neuronitis (VN) is a prevalent peripheral vestibular disorder presenting with sudden unilateral vestibular loss, leading to acute vertigo without associated cochlear or neurological symptoms. Diagnosis remains challenging due to symptom overlap with other vestibular and central disorders. This study reviews the epidemiology, pathogenesis, and diagnostic approaches for VN to propose a streamlined, evidence-based diagnostic algorithm. A comprehensive literature review was conducted, analyzing 114 studies, including randomized controlled trials, systematic reviews, and clinical guidelines. Emphasis is placed on the clinical history and bedside examinations, supported by ancillary tests to confirm the diagnosis and differentiate VN from central and other peripheral causes of vertigo. The proposed algorithm aims to enhance diagnostic precision and support clinical decision-making.

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