Browse by author
Lookup NU author(s): Professor Dame Louise Robinson
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
BACKGROUND: Cognitive impairment is a growing public health concern, and is one of the most distinctive characteristics of all dementias. The timely recognition of dementia syndromes can be beneficial, as some causes of dementia are treatable and are fully or partially reversible. Several automated cognitive assessment tools for assessing mild cognitive impairment (MCI) and early dementia are now available. Proponents of these tests cite as benefits the tests' repeatability and robustness and the saving of clinicians' time. However, the use of these tools to diagnose and/or monitor progressive cognitive impairment or response to treatment has not yet been evaluated. OBJECTIVES: The aim of this review was to determine whether or not automated computerised tests could accurately identify patients with progressive cognitive impairment in MCI and dementia and, if so, to investigate their role in monitoring disease progression and/or response to treatment. DATA SOURCES: Five electronic databases (MEDLINE, EMBASE, The Cochrane Library, ISI Web of Science and PsycINFO), plus ProQuest, were searched from 2005 to August 2015. The bibliographies of retrieved citations were also examined. Trial and research registers were searched for ongoing studies and reviews. A second search was run to identify individual test costs and acquisition costs for the various tools identified in the review. REVIEW METHODS: Two reviewers independently screened all titles and abstracts to identify potentially relevant studies for inclusion in the review. Full-text copies were assessed independently by two reviewers. Data were extracted and assessed for risk of bias by one reviewer and independently checked for accuracy by a second. The results of the data extraction and quality assessment for each study are presented in structured tables and as a narrative summary. RESULTS: The electronic searching of databases, including ProQuest, resulted in 13,542 unique citations. The titles and abstracts of these were screened and 399 articles were shortlisted for full-text assessment. Sixteen studies were included in the diagnostic accuracy review. No studies were eligible for inclusion in the review of tools for monitoring progressive disease. Eleven automated computerised tests were assessed in the 16 included studies. The overall quality of the studies was good; however, the wide range of tests assessed and the non-standardised reporting of diagnostic accuracy outcomes meant that meaningful synthesis or statistical analysis was not possible. LIMITATIONS: The main limitation of this review is the substantial heterogeneity of the tests assessed in the included studies. As a result, no meta-analyses could be undertaken. CONCLUSION: The quantity of information available is insufficient to be able to make recommendations on the clinical use of the computerised tests for diagnosing and monitoring MCI and early dementia progression. The value of these tests also depends on the costs of acquisition, training, administration and scoring. FUTURE WORK: Research is required to establish stable cut-off points for automated computerised tests that are used to diagnose patients with MCI or early dementia. Additionally, the costs associated with acquiring and using these tests in clinical practice should be estimated. STUDY REGISTRATION: The study is registered as PROSPERO CRD42015025410. FUNDING: The National Institute for Health Research Health Technology Assessment programme.
Author(s): Aslam RW, Bates V, Dundar Y, Hounsome J, Richardson M, Krishan A, Dickson R, Boland A, Kotas E, Fisher J, Sikdar S, Robinson L
Publication type: Review
Publication status: Published
Journal: Health Technology Assessment
Online publication date: 01/10/2016
Acceptance date: 02/04/2016
ISSN (print): 1366-5278
ISSN (electronic): 2046-4924
PubMed id: 27767932