SynthesisJournal of neurology2025
Accuracy of video head impulse test in stroke diagnosis during acute vestibular syndrome: a systematic review with meta-analysis.
Synthesis in Journal of neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prevalence of vestibulo-ocular reflex dysfunction in people with neurological disorders: a systematic review and meta-analysis.Journal of neurology · 2026Pooled it
- [Vertigo and oculomotor disorders: diagnosis, anatomical classification and etiology].Die Ophthalmologie · 2026Review
- Diagnostic challenges in posterior circulation ischemic stroke presenting with acute dizziness and vertigo.Frontiers in neurology · 2026Review
- The clinical value of vHIT saccadic parameters in the diagnosis and management of central vestibular disorders: a narrative review.Frontiers in neurologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVertigo is a common symptom in people with acute stroke, leading to difficulty in the diagnostic process. This study aims to systematically report the accuracy of the video head impulse test (vHIT) for diagnosing stroke in individuals presenting to emergency departments with acute vertigo.
methodsData from MEDLINE, CENTRAL, CINAHL, SCOPUS, and gray literature were searched from inception to July 2024 without language limits. Independent researchers created a contingency table to record the number of true positives, false positives, true negatives, and false negatives. A bivariate analysis was performed to estimate the summary sensitivity and specificity. Subgroup and sensitivity analyses were conducted to explore the source of heterogeneity. A quality assessment was performed using the Quality Assessment of Diagnostic Test Accuracy Studies 2 tool.
results13 studies (905 participants) were included. EyeSeeCam (6/13) and Otometrics (6/13) were the most represented vHIT devices. The studies were of good quality, with the flow and timing being the more prevalent domain presenting a high risk of bias (7/13); however, there were no concerns about applicability. The vHIT had a specificity of 85% (95% CI, 61%-95%), sensitivity of 84% (95% CI, 70%-92%), positive likelihood ratio (LR) of 5.56 (95% CI, 2.00-15.47), negative LR of 0.18 (95% CI, 0.10-0.35), and diagnostic odd ratio of 30.23 (95% CI, 8.96-102.06), making this test particularly useful for ruling out strokes.
conclusionThis review highlights the value of vHIT as a complementary tool in early diagnosis of stroke. Thus, expertise in its use and interpretation should be promoted, and future primary studies are expected to refine and update this systematic review. Prospero registration CRD42024532776.
Indexed as
Identifiers
40447837What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.