Trial reportComputational and mathematical methods in medicine2022
Feasibility and Validity of Cambridge Neuropsychological Test Automated Battery in Mild Cognitive Impairment Screening for Patients with Atrial Fibrillation.
Trial report in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Validation of an Application-Based Cognitive Screening Test for Older Thai Adults.Dementia and geriatric cognitive disorders · 2025Article
- The Functional-Cognitive and Sensory Treatment (F-CaST) to improve rehabilitation outcomes of individuals with substance use disorder: a study protocol for a mixed-method randomized controlled trial.Addiction science & clinical practice · 2024Article
- Risk factors of atrial fibrillation complicated with cognitive impairment and the relationship between cardiac function parameters and the degree of cognitive impairment.Clinics (Sao Paulo, Brazil) · 2024Article
- Retracted: Feasibility and Validity of Cambridge Neuropsychological Test Automated Battery in Mild Cognitive Impairment Screening for Patients with Atrial Fibrillation.Computational and mathematical methods in medicine · 2023Article
Corrections and comments
- Retraction · 2023-11-01Concerns/Issues about Data · Concerns/Issues about Results and/or Conclusions · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Paper Mill · Computer-Aided Content or Computer-Generated Content · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAtrial fibrillation (AF) is associated with the worsening of cognitive function. Strategies that are both convenient and reliable for cognitive screening of AF patients remain underdeveloped. We aimed to analyze the sensitivity and specificity of computerized cognitive screening strategies using subtests from Cambridge Neuropsychological Test Automated Battery (CANTAB) in AF patients.
methodsThe Multitasking Test (MTT), Rapid Visual Information Processing (RVP), and Paired Associates Learning (PAL) subtests from CANTAB were performed in 105 AF patients. Traditional standard neuropsychological tests were used as a reference standard. Cognitive screening models using different CANTAB subtests were established using multivariable logistic regression. Further stepwise regression using the Akaike Information Criterion (AIC) was applied to optimize the models. Receiver operating characteristic curve analyses were used to study the sensitivity and specificity of these models.
resultsFifty-eight (55%) patients were diagnosed with mild cognitive impairment (MCI). MTT alone had reasonable sensitivity (82.8%) and specificity (74.5%) for MCI screening, while RVP (sensitivity 72.4%, specificity 70.2%) and PAL (sensitivity 70.7%, specificity 57.4%) were less effective. Stepwise regression of all available variables revealed that a combination of MTT and RVP brought about higher specificity (sensitivity 82.8%, specificity 85.8%), while PAL was not included in the optimal model. Moreover, adding education to the models did not result in improved validity for MCI screening.
conclusionThe CANTAB subtests are feasible and effective strategies for MCI screening among AF patients independent of patients' education levels. Hence, they are practical for cardiologists or general practitioners.
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