Differential Diagnosis of Vertigo in the Emergency Department: A Prospective Validation Study of the STANDING Algorithm.

Abstract:

Objective:We investigated the reliability and accuracy of a bedside diagnostic algorithm for patients presenting with vertigo/unsteadiness to the emergency department. Methods:We enrolled consecutive adult patients presenting with vertigo/unsteadiness at a tertiary hospital. STANDING, the acronym for the four-step algorithm we have previously described, based on nystagmus observation and well-known diagnostic maneuvers includes (1) the discrimination between SponTAneous and positional nystagmus, (2) the evaluation of the Nystagmus Direction, (3) the head Impulse test, and (4) the evaluation of equilibrium (staNdinG). Reliability of each step was analyzed by Fleiss' K calculation. The reference standard (central vertigo) was a composite of brain disease including stroke, demyelinating disease, neoplasm, or other brain disease diagnosed by initial imaging or during 3-month follow-up. Results:Three hundred and fifty-two patients were included. The incidence of central vertigo was 11.4% [95% confidence interval (CI) 8.2-15.2%]. The leading cause was ischemic stroke (70%). The STANDING showed a good reliability (overall Fleiss K 0.83), the second step showing the highest (0.95), and the third step the lowest (0.74) agreement. The overall accuracy of the algorithm was 88% (95% CI 85-88%), showing high sensitivity (95%, 95% CI 83-99%) and specificity (87%, 95% CI 85-87%), very high-negative predictive value (99%, 95% CI 97-100%), and a positive predictive value of 48% (95% CI 41-50%) for central vertigo. Conclusion:Using the STANDING algorithm, non-sub-specialists achieved good reliability and high accuracy in excluding stroke and other threatening causes of vertigo/unsteadiness.

journal_name

Front Neurol

journal_title

Frontiers in neurology

authors

Vanni S,Pecci R,Edlow JA,Nazerian P,Santimone R,Pepe G,Moretti M,Pavellini A,Caviglioli C,Casula C,Bigiarini S,Vannucchi P,Grifoni S

doi

10.3389/fneur.2017.00590

subject

Has Abstract

pub_date

2017-11-07 00:00:00

pages

590

issn

1664-2295

journal_volume

8

pub_type

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