About this trial
The goal of this observational study is to learn how well the Oxford Visual Perception Screening (OxVPS) tool can identify stroke survivors with visual perception difficulties.
The main aim is to determine the accuracy and utility of the OxVPS compared to the current gold standard assessment in stroke survivors. In other words, how well can the Oxford Visual Perception Screening tool (OxVPS) identify stroke patients with visual perception problems?
Participants will completed the OxVPS and the current gold standards visual perception screening tool.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Patients with a clinical diagnosis of stroke (ischemic stroke and/or intracerebral haemorrhage).
Within 6 weeks of confirmed stroke.
Disqualifiers
Insufficient understanding of English
Clinical concerns that patient is unable follow simple instructions.
Clinical concerns that patient is unable to concentrate for 15 minutes.
No capacity to provide informed consent.
Trial population
Stroke survivors on stroke rehabilitation units in the North East of England and Oxfordshire.
Trial design
Case-only
Cross-sectional
Treatments tested in this trial
OxVPS
Diagnostic testComparing a new screening tool, the Oxford visual perception screening, to the gold standard, Rivermead Perceptual Battery Assessment.
Treatment groups
Trial outcomes
Primary outcomes
Validity of OxVPS
Convergent and discriminate validity will be assessed. Convergent validity expressed as a correlation between total score on OxVPS and RPAB. Discriminate validity to be expressed as correlation between OxVPS score and scores of cognitive and sensory vision assessments. Both calculated by a non-parametric Spearman correlation and estimate a 95% confidence interval. The analysis can be completed through the cor.test function in the base package of R.
Reliability of OxVPS
The inter-rater reliability of OxVPS will be evaluated through a Bland-Altman analysis \[26\]: we will calculate the difference in OxVPS scores between raters for each patient. Subsequently, we will plot the difference in scores as a function on the average score to evaluate a bias between the raters (mean difference) that might vary based on severity of a patient's visual perceptual problems. We will report the mean difference, standard deviation, and limits of agreement within where 95% of differences between raters fall. A t-test will indicate if the mean difference is significantly different from 0. Analyses will be performed in R with the functions from blandr package (e.g. blandr.statistics and blandr.draw) or functions from a similar package.
Sponsors and contacts
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Durham University
Lead sponsor
National Institute for Health Research, United Kingdom
Collaborator
County Durham and Darlington NHS Foundation Trust
Collaborator
University of Oxford
Collaborator