Neuropsychology/computerized neuropsychological assessment

AbstractBackgroundDifferential diagnostics in dementia is challenging. To date, the basic assessment still includes imaging of the brain and cognitive testing with pen and paper. Web‐based cognitive tests however hold potential for standardized and low‐cost screening in clinical workup. How they perform when combined with imaging of the brain is unknown. We therefore evaluated the accuracy of a new web‐based cognitive battery (Muistikko [1]) detecting different types of dementia, when combined with brain MRI, and compared this to traditional cognitive testing and MRI.MethodWe included 229 subj... Mehr ...

Verfasser: Miia Kivipelto
Philip Scheltens
Sanna-Kaisa Herukka
Anne M. Remes
Patrizia Mecocci
Hanneke Fm. Rhodius Meester
Teemu Paajanen
Wiesje M. van der Flier
Steen G. Hasselbalch
Jyrki Lötjönen
Hilkka Soininen
Frederik Barkhof
Mark van Gils
Shadi Mahdiani
Tiia Ngandu
Juha Koikkalainen
Tuomo Hänninen
Dokumenttyp: Artikel
Erscheinungsdatum: 2020
Schlagwörter: Netherlands / Aurora Universities Network / Psychiatry and Mental health / Cellular and Molecular Neuroscience / Geriatrics and Gerontology / Neurology (clinical) / Developmental Neuroscience / Health Policy / Epidemiology
Sprache: Englisch
Permalink: https://search.fid-benelux.de/Record/base-26811630
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://www.openaccessrepository.it/record/77499

AbstractBackgroundDifferential diagnostics in dementia is challenging. To date, the basic assessment still includes imaging of the brain and cognitive testing with pen and paper. Web‐based cognitive tests however hold potential for standardized and low‐cost screening in clinical workup. How they perform when combined with imaging of the brain is unknown. We therefore evaluated the accuracy of a new web‐based cognitive battery (Muistikko [1]) detecting different types of dementia, when combined with brain MRI, and compared this to traditional cognitive testing and MRI.MethodWe included 229 subjects from two memory clinic cohorts (PredictND and VPH‐DARE), consisting of 188 controls, 29 patients with Alzheimer's dementia (AD), 7 with frontotemporal dementia (FTD) and 5 with vascular dementia (VaD) (Table 1). All patients performed a traditional cognitive test battery (consisting of MMSE, RAVLT, TMT‐A and B, Animal Fluency), web‐based cognitive testing and had MRI of the brain. Although Muistikko is composed of seven subtasks, only global cognitive score (GCS) was used as defined in [1]. From MRI, multiple imaging biomarkers were defined [2]. Disease‐state index classifier was developed from the predictors [2]. Cross‐validation was used to calculate balanced accuracy (BACC; average of sensitivities for each diagnostic group). Given the class imbalance, we also calculated prevalence corrected accuracy (PACC).ResultBACC was 66 % and PACC 64% when using the traditional cognitive test battery + MRI. Both BACC and PAC were 69 % when using the web‐based cognitive testing + MRI (Table 2). Of note, since we compare four diagnostic groups, BACC by guessing would be 25%.ConclusionThis study shows that combining web‐based cognitive tests with MRI data results in high accuracy when separating different types of dementia. The results were comparable with the standard traditional work‐up. Web‐based cognitive testing is therefore a promising tool to support the clinician in the daily challenge of differential diagnostics, ...