ArticleJournal of neurology2023
Establishing normative data for the evaluation of cognitive performance in Huntington's disease considering the impact of gender, age, language, and education.
Article in Journal of neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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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.
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Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Reliability and validity of the Huntington's Disease Everyday Functioning (Hi-DEF): A patient-reported measure of cognitive capacity on daily functioning in Huntington's disease.Journal of Huntington's disease · 2025Article
- Challenging or less challenging oral diadochokinetic tasks-what works best in Huntington disease? A cross-sectional study.Journal of neurology · 2025Article
- Normative Data for Objective ADHD Smartphone Application in a General Population.Clinical practice and epidemiology in mental health : CP & EMH · 2025Article
- Cognitive impairment predicts medication discrepancies in Huntington's Disease: patient self-report compared to pharmacy records.Journal of neurology · 2024Article
- Extracellular vesicles: biological mechanisms and emerging therapeutic opportunities in neurodegenerative diseases.Translational neurodegeneration · 2024Review
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundA declining cognitive performance is a hallmark of Huntington's disease (HD). The neuropsychological battery of the Unified HD Rating Scale (UHDRS'99) is commonly used for assessing cognition. However, there is a need to identify and minimize the impact of confounding factors, such as language, gender, age, and education level on cognitive decline.
objectivesAim is to provide appropriate, normative data to allow clinicians to identify disease-associated cognitive decline in diverse HD populations by compensating for the impact of confounding factors
methodsSample data, N = 3267 (60.5% females; mean age of 46.9 years (SD = 14.61, range 18-86) of healthy controls were used to create a normative dataset. For each neuropsychological test, a Bayesian generalized additive model with age, education, gender, and language as predictors was constructed to appropriately stratify the normative dataset.
resultsWith advancing age, there was a non-linear decline in cognitive performance. In addition, performance was dependent on educational levels and language in all tests. Gender had a more limited impact. Standardized scores have been calculated to ease the interpretation of an individual's test outcome. A web-based online tool has been created to provide free access to normative data.
conclusionFor defined neuropsychological tests, the impact of gender, age, education, and language as factors confounding disease-associated cognitive decline can be minimized at the level of a single patient examination.
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Registered trials
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