Evidence map›Paper›PMID 35178112›Full record

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.

Jia Wang, Yiwei Lai, Chao Jiang, Yu Bai, Baolei Xu, Xin Du, Jianzeng Dong, Changsheng Ma

RetractedOpen access · hybridAbstract readRandomized Controlled TrialRetracted Publication
In one paragraph

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 It has been retracted, and should not be counted.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.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 25% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 2 countries.

Jia WangDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China.
Yiwei LaiDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China.
Chao JiangDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China.ORCID https://orcid.org/0000-0003-1138-7960
Yu BaiFaculty of Science, The University of Sydney, Sydney, Australia.
Baolei XuDepartment of Neurology, Beijing Anzhen Hospital, China.
Xin DuDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China.
Jianzeng DongDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China.
Changsheng MaDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University, National Clinical Research Centre for Cardiovascular Diseases, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine for Cardiovascular Diseases, Beijing, China.ORCID https://orcid.org/0000-0002-5387-5957
Capital Medical University · CNBeijing Anzhen Hospital · CNThe University of Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Neuropsychological TestsAgedAtrial FibrillationCognitive DysfunctionComputational BiologyDiagnosis, Computer-AssistedFeasibility StudiesFemaleHumansMaleMiddle AgedReproducibility of ResultsSensitivity and Specificity

Identifiers

PMID35178112
PMCPMC8847012
OpenAlexW4210906757

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.