| Literature DB >> 34244842 |
Athanasia Korda1, Ewa Zamaro1, Franca Wagner2, Miranda Morrison1, Marco Domenico Caversaccio1, Thomas C Sauter3, Erich Schneider4, Georgios Mantokoudis5.
Abstract
OBJECTIVE: Skew deviation results from a dysfunction of the graviceptive pathways in patients with an acute vestibular syndrome (AVS) leading to vertical diplopia due to vertical ocular misalignment. It is considered as a central sign, however, the prevalence of skew and the accuracy of its test is not well known .Entities:
Keywords: Acute stroke; Acute unilateral vestibulopathy; Test of skew; VOG; Vertigo; Video-oculography
Mesh:
Year: 2021 PMID: 34244842 PMCID: PMC8857098 DOI: 10.1007/s00415-021-10692-6
Source DB: PubMed Journal: J Neurol ISSN: 0340-5354 Impact factor: 4.849
Fig. 1The box-plots whiskers and the outliers of vertical eye misalignment of normal subjects stratified by age groups. The circles represent the outliers (1.5 times of the interquartile range (IQR) above the upper quartile) and the asterisks the extreme outliers (3 times IQR above the upper quartile). The dotted line represents two standard deviations from the mean
Fig. 2The eye recordings of VOG Test-of-Skew in a patient with acute stroke and an average of 11.49 deg skew (A) and in a patient with acute unilateral vestibulopathy and an average of 2.81 deg skew (B). The gray area represents the time that the eye is uncovered and fixing the target (y achse shows the eye position and x achse the time)
Fig. 3The box-plots whiskers and the outliers of vertical eye misalignment in patients with acute unilateral vestibulopathy and stroke. The circles represent the outliers and the asterisks the extreme outliers. Stroke group includes an outlier with 11.49° vertical misalignment, which is not represented graphically
Fig. 4The sensitivity and specificity of ‘HINTS’ and its combinations: clinical head impulse alone, clinical head impulse and nystagmus combined, clinical ‘HINTS’ (three-step test) and clinical HINTS with integrated video test of skew
Fig. 5A density plot for skew deviations in patients with AUVP versus strokes. The vertical dotted lines illustrate the chosen optimal cut points to discriminate AUVP from stroke. A lower cut-off (0.81°) favored the sensitivity for stroke diagnosis while a higher cut-off (3.3°) favored the specificity for stroke detection