A Novel Approach to Acute Dizziness in the Emergency Department: A Prospective Validation Study of the 'ATTEST' Algorithm

Background: The objective is to assess the diagnostic performance of the ATTEST bedside algorithm in adults presenting to the emergency department with acute dizziness and to describe the bedside patterns associated with central lesions on diffusion-weighted magnetic resonance imaging. Material and Methods: This prospective validation study analyzed thirty-four adults evaluated for acute dizziness. The index test was the ATTEST bedside classification, organized into acute vestibular syndrome, triggered episodic vestibular syndrome, and spontaneous episodic vestibular syndrome, based on symptom timing, triggers, oculomotor findings, and focal neurologic signs. Magnetic resonance imaging with diffusion-weighted imaging served as the reference standard for acute central lesions. Results: Eleven of thirty-four patients (32.4%) had acute central lesions. The ATTEST algorithm identified 9 of these cases and missed 2, while 1 false-positive classification occurred among 23 MRI-negative cases. Sensitivity was 81.82%, specificity 95.65%, positive predictive value 90.00%, negative predictive value 91.67%, and overall accuracy 91.18%. Acute vestibular syndrome, gait ataxia, skew deviation, and focal central nervous system findings were more frequent in patients with MRI-positive lesions. Conclusion: ATTEST showed high specificity and good overall accuracy for distinguishing central from non-central causes of acute dizziness. Its strongest performance appeared in continuous vestibular presentations with central oculomotor or neurologic signs, but small posterior circulation infarcts remained a potential source of false-negative bedside classification.

Keywords: Dizziness, Emergency Department, Magnetic Resonance Imaging, Stroke, Vertigo.