Effectiveness and reliability of the four-step STANDING algorithm performed by interns and senior emergency physicians for predicting central causes of vertigo
- PMID: 36628557
- DOI: 10.1111/acem.14659
Effectiveness and reliability of the four-step STANDING algorithm performed by interns and senior emergency physicians for predicting central causes of vertigo
Abstract
Background: For emergency physicians (EPs), acute vertigo is a challenging complaint and learning a reliable clinical approach is needed. STANDING is a four-step bedside algorithm that requires (1) identifying spontaneous nystagmus with Frenzel glasses or, alternatively, a positional nystagmus; (2) characterizing the nystagmus direction; (3) assessing the vestibuloocular reflex (head impulse test); and (4) assessing the gait. The objective was to determine its accuracy for diagnosing central vertigo when using by naïve examiners as such as interns and its agreement with senior EPs.
Methods: This was a prospective 1-year diagnostic cohort study among patients with vertigo, vestibulovisual symptoms, or postural symptoms seen by 20 interns trained in the four-step examination. The algorithm was performed first by an intern and second by a senior EP and categorized as either worrisome when indicating a central diagnosis and benign or inconclusive when indicating a peripheral diagnosis. The reference test was diffusion-weighted brain magnetic resonance imaging.
Results: Among 312 patients included, 57 had a central diagnosis including 33 ischemic strokes (10.5%). The main etiology was benign paroxysmal positional vertigo (32.7%). The likelihood ratios were 4.63 and 10.33 for a worrisome STANDING, 0.09 and 0.01 for a benign STANDING, and 0.21 and 0.35 for an inconclusive STANDING, for interns and senior EPs, respectively. The algorithm showed sensitivities of 84.8% (95% CI 75.6%-93.9%) and 89.8% (95% CI 82.1%-97.5%), negative predictive values of 96.2% (95% CI 93.7%-98.6%) and 97.5% (95% CI 95.5%-99.5%), specificities of 88.9% (95% CI 85.1%-92.8%) and 91.3% (95% CI 87.8%-94.8%), and positive predictive values of 64.1% (95% CI 53.5%-74.8%) and 70.7% (95% CI 60.4%-81.0%), respectively. The agreement between interns and senior EPs was very substantial (B-statistic coefficient: 0.77) and almost perfect for each step: (1) 0.87, (2) 0.98, (3) 0.95, and (4) 0.99.
Conclusions: With a single training session, the algorithm reached high accuracy and reliability for ruling out central causes of vertigo in the hands of both novices and experienced EPs. A future multicenter randomized controlled trial should further its impact on unnecessary neuroimaging use and patient's satisfaction.
Trial registration: ClinicalTrials.gov NCT04919187.
Keywords: emergency department; eye movements; magnetic resonance imaging; validation study; vertigo.
© 2023 Society for Academic Emergency Medicine.
Comment in
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The 4-step STANDING algorithm for predicting central causes of vertigo: Methodologic issues on reliability, validity and prediction.Acad Emerg Med. 2023 May;30(5):606-607. doi: 10.1111/acem.14674. Epub 2023 Feb 24. Acad Emerg Med. 2023. PMID: 36727819 No abstract available.
References
REFERENCES
-
- Newman-Toker DE, Hsieh YH, Camargo CA, Pelletier AJ, Butchy GT, Edlow JA. Spectrum of dizziness visits to US emergency departments: cross-sectional analysis from a nationally representative sample. Mayo Clin Proc. 2008;83(7):765-775.
-
- Newman-Toker DE, Edlow JA. TiTrATE: a novel, evidence-based approach to diagnosing acute dizziness and vertigo. Neurol Clin. 2015;33(3):577-599. viii.
-
- Bisdorff A, Von Brevern M, Lempert T, Newman-Toker DE. Classification of vestibular symptoms: towards an international classification of vestibular disorders. J Vestib Res. 2009;19(1-2):1-13.
-
- Parker IG, Hartel G, Paratz J, Choy NL, Rahmann A. A systematic review of the reported proportions of diagnoses for dizziness and vertigo. Otol Neurotol. 2019;40(1):6-15.
-
- Saber Tehrani AS, Kattah JC, Kerber KA, et al. Diagnosing stroke in acute dizziness and vertigo: pitfalls and pearls. Stroke. 2018;49(3):788-795.
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