| Literature DB >> 35309564 |
Peter Müller-Barna1, Christina Leinweber1, Julia Pfaffenrath1, Nina Schütt-Becker1, Rascha von Martial1, Susanne Greck1, Nikolai Hubert1, Holger Rambold2,3,4, Roman Haberl1, Gordian Jan Hubert1.
Abstract
Background: Acute dizziness, vertigo, and imbalance are frequent and difficult to interpret symptoms in the emergency department (ED). Primary care hospitals often lack the expertise to identify stroke or TIA as underlying causes. A telemedical approach based on telestroke networks may offer adequate diagnostics and treatment. Aim: The aim of this study is to evaluate the accuracy of a novel ED algorithm in differentiating between peripheral and central vestibular causes.Entities:
Keywords: acute vestibular syndrome; diagnostic method; dizziness; emergency medicine; stroke; telemedicine; vertigo
Year: 2022 PMID: 35309564 PMCID: PMC8924543 DOI: 10.3389/fneur.2022.766685
Source DB: PubMed Journal: Front Neurol ISSN: 1664-2295 Impact factor: 4.003
Figure 1Map of the southeastern part of Bavaria, Germany with all TeleVertigo hospitals.
Figure 2Overview of the major components of the TeleVertigo project.
Figure 3ED triage algorithm for all cases of acute dizziness, vertigo, or imbalance.
Number of cases per hospital and evaluation month with acute (<72 h from onset) dizziness, vertigo, or imbalance of unknown cause (ADVIUC) as a leading symptom for ED admission.
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|---|---|---|---|---|
| Agatharied | 10 | 12 | 14 | 144 |
| Bad Reichenhall | 9 | 8 | 7 | 96 |
| Bad Tölz | 7 | 11 | 13 | 124 |
| Burglengenfeld | 8 | 12 | 120 | |
| Cham | 12 | 144 | ||
| Ebersberg | 10 | 5 | 90 | |
| Eggenfelden | 25 | 300 | ||
| Erding | 12 | 144 | ||
| Freising | 12 | 16 | 168 | |
| Mühldorf | 7 | 12 | 114 | |
| Rosenheim | 16 | 17 | 17 | 200 |
| Rotthalmünster | 12 | 6 | 108 | |
| Traunstein | 18 | 20 | 24 | 248 |
| Vilsbiburg | 8 | 96 | ||
| Wasserburg | 13 | 9 | 6 | 112 |
| Total | 73 | 138 | 177 | 2,208 |
| Median (IQR) | 12 (8–14.5) | 124 (110–184) |
Annual number of cases are extrapolated from monthly numbers.
Baseline characteristics of all cases with an acute leading symptom of dizziness, vertigo, or imbalance of unknown cause (ADVIUC).
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| |
|---|---|---|---|
| Age [median; IQR (years)] | 65 (54–78) | ||
| Female sex | 210 | 388 | 54.1% |
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| |||
| Arterial hypertension | 224 | 388 | 57.7% |
| Diabetes mellitus | 68 | 388 | 17.5% |
| Hypercholesterinemia | 146 | 388 | 37.6% |
| (ex-)smoker | 59 | 388 | 15.2% |
| Atrial fibrilation | 46 | 376 | 12.2% |
| Osteoporosis | 17 | 359 | 4.7% |
| History of dizziness/vertigo | 43 | 360 | 11.9% |
|
| |||
| Hyperacute onset | 340 | 387 | 87.9% |
| Dizziness or vertigo | 386 | 388 | 99.5% |
| Vertigo only | 206 | 370 | 55.7% |
| Imbalance | 235 | 359 | 65.5% |
| Nystagmus | 197 | 386 | 51.0% |
| Nausea | 246 | 343 | 71.7% |
| Vomiting | 153 | 340 | 45.0% |
| New neck pain or headache | 49 | 263 | 18.6% |
| Known headache | 22 | 388 | 5.7% |
| New tinnitus | 21 | 214 | 9.8% |
| New hearing disturbance | 14 | 211 | 6.6% |
| New ear symptoms (others) | 20 | 211 | 9.5% |
| New phono- or photophobia | 8 | 163 | 4.9% |
Missing cases are due to missing information in available hospital discharge letters.
Distribution of hospital discharge diagnoses of all cases (n = 388) with an acute leading symptom of dizziness, vertigo, or imbalance of unknown cause (ADVIUC).
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|
|---|---|---|
| Vestibular neuritis | 87 | 22.4% |
| Vertebrobasilar stroke or TIA | 68 | 17.5% |
| BPPV | 68 | 17.5% |
| Dizziness of internal medicine cause | 57 | 14.7% |
| Meniere's disease | 26 | 6.7% |
| Functional disorder | 7 | 1.8% |
| Vestibular migraine | 7 | 1.8% |
| Inflammatory CNS disease | 6 | 1.5% |
| Others | 3 | 0.8% |
| Unclear | 59 | 15.2% |
Others include one case of bilateral vestibulopathy, vestibular paroxysm, and polyneuropathy each.
Figure 4Flowchart of the study cohort.
Accuracy of ED triage algorithm in vestibular cases.
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|---|---|---|---|
| Central or unclear | 73 | 98 | 171 |
| Peripheral | 1 | 83 | 84 |
| Total | 74 | 181 | 255 |
| Sensitivity: | 98.6% | ||
| Specificity: | 45.9% | ||
| Positive predictive value: | 42.7% | ||
| Negative predictive value: | 98.8% |
ED diagnoses compared to final discharge diagnoses.
Figure 5Subjective user assessment for acute and elective videooculographies. Rates of positive answers.
Figure 6Results of online survey in November 2020. Rates of positive answers.