ArticleScientific reports2021
Wada test results contribute to the prediction of change in verbal learning and verbal memory function after temporal lobe epilepsy surgery.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Moscow Wada protocol: an optimised protocol for language and memory lateralization.Brain structure & function · 2026Article
- Neural (re)organisation of language and memory: implications for neuroplasticity and cognition.Journal of neurology, neurosurgery, and psychiatry · 2025Article
- Verbal Memory Localized in Non-language-dominant Hemisphere: Atypical Lateralization Revealed by Material-specific Memory Evaluation Using Super-selective Wada Test.NMC case report journal · 2025Article
- Memory and language risk assessment with Wada test in patients candidates for epilepsy surgery.Revista de neurologia · 2024Observational
- Determination of language areas in patients with epilepsy using the super-selective Wada test.IBRO neuroscience reports · 2022Article
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Authors and funding
18 authors.
Funding
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Abstract
In recent years, the clinical usefulness of the Wada test (WT) has been debated among researchers in the field. Therefore, we aimed to assess its contribution to the prediction of change in verbal learning and verbal memory function after epilepsy surgery. Data from 56 patients with temporal lobe epilepsy who underwent WT and subsequent surgery were analyzed retrospectively. Additionally, a standard neuropsychological assessment evaluating attentional, learning and memory, visuospatial, language, and executive function was performed both before and 12 months after surgery. Hierarchical linear regression analyses were used to determine the incremental value of WT results over socio-demographic, clinical, and neuropsychological characteristics in predicting postsurgical change in patients' verbal learning and verbal memory function. The incorporation of WT results significantly improved the prediction models of postsurgical change in verbal learning (∆R
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