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      Current advances in digital cognitive assessment for preclinical Alzheimer's disease

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          Abstract

          There is a pressing need to capture and track subtle cognitive change at the preclinical stage of Alzheimer's disease (AD) rapidly, cost‐effectively, and with high sensitivity. Concurrently, the landscape of digital cognitive assessment is rapidly evolving as technology advances, older adult tech‐adoption increases, and external events (i.e., COVID‐19) necessitate remote digital assessment. Here, we provide a snapshot review of the current state of digital cognitive assessment for preclinical AD including different device platforms/assessment approaches, levels of validation, and implementation challenges. We focus on articles, grants, and recent conference proceedings specifically querying the relationship between digital cognitive assessments and established biomarkers for preclinical AD (e.g., amyloid beta and tau) in clinically normal (CN) individuals. Several digital assessments were identified across platforms (e.g., digital pens, smartphones). Digital assessments varied by intended setting (e.g., remote vs. in‐clinic), level of supervision (e.g., self vs. supervised), and device origin (personal vs. study‐provided). At least 11 publications characterize digital cognitive assessment against AD biomarkers among CN. First available data demonstrate promising validity of this approach against both conventional assessment methods (moderate to large effect sizes) and relevant biomarkers (predominantly weak to moderate effect sizes). We discuss levels of validation and issues relating to usability, data quality, data protection, and attrition. While still in its infancy, digital cognitive assessment, especially when administered remotely, will undoubtedly play a major future role in screening for and tracking preclinical AD.

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          Most cited references118

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          Rayyan—a web and mobile app for systematic reviews

          Background Synthesis of multiple randomized controlled trials (RCTs) in a systematic review can summarize the effects of individual outcomes and provide numerical answers about the effectiveness of interventions. Filtering of searches is time consuming, and no single method fulfills the principal requirements of speed with accuracy. Automation of systematic reviews is driven by a necessity to expedite the availability of current best evidence for policy and clinical decision-making. We developed Rayyan (http://rayyan.qcri.org), a free web and mobile app, that helps expedite the initial screening of abstracts and titles using a process of semi-automation while incorporating a high level of usability. For the beta testing phase, we used two published Cochrane reviews in which included studies had been selected manually. Their searches, with 1030 records and 273 records, were uploaded to Rayyan. Different features of Rayyan were tested using these two reviews. We also conducted a survey of Rayyan’s users and collected feedback through a built-in feature. Results Pilot testing of Rayyan focused on usability, accuracy against manual methods, and the added value of the prediction feature. The “taster” review (273 records) allowed a quick overview of Rayyan for early comments on usability. The second review (1030 records) required several iterations to identify the previously identified 11 trials. The “suggestions” and “hints,” based on the “prediction model,” appeared as testing progressed beyond five included studies. Post rollout user experiences and a reflexive response by the developers enabled real-time modifications and improvements. The survey respondents reported 40% average time savings when using Rayyan compared to others tools, with 34% of the respondents reporting more than 50% time savings. In addition, around 75% of the respondents mentioned that screening and labeling studies as well as collaborating on reviews to be the two most important features of Rayyan. As of November 2016, Rayyan users exceed 2000 from over 60 countries conducting hundreds of reviews totaling more than 1.6M citations. Feedback from users, obtained mostly through the app web site and a recent survey, has highlighted the ease in exploration of searches, the time saved, and simplicity in sharing and comparing include-exclude decisions. The strongest features of the app, identified and reported in user feedback, were its ability to help in screening and collaboration as well as the time savings it affords to users. Conclusions Rayyan is responsive and intuitive in use with significant potential to lighten the load of reviewers.
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            NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease

            In 2011, the National Institute on Aging and Alzheimer’s Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer’s disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer’s Association to update and unify the 2011 guidelines. This unifying update is labeled a “research framework” because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer’s Association Research Framework, Alzheimer’s disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six-stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker-based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker-based research should not be considered a template for all research into age-related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β-amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.
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              Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease.

              The pathophysiological process of Alzheimer's disease (AD) is thought to begin many years before the diagnosis of AD dementia. This long "preclinical" phase of AD would provide a critical opportunity for therapeutic intervention; however, we need to further elucidate the link between the pathological cascade of AD and the emergence of clinical symptoms. The National Institute on Aging and the Alzheimer's Association convened an international workgroup to review the biomarker, epidemiological, and neuropsychological evidence, and to develop recommendations to determine the factors which best predict the risk of progression from "normal" cognition to mild cognitive impairment and AD dementia. We propose a conceptual framework and operational research criteria, based on the prevailing scientific evidence to date, to test and refine these models with longitudinal clinical research studies. These recommendations are solely intended for research purposes and do not have any clinical implications at this time. It is hoped that these recommendations will provide a common rubric to advance the study of preclinical AD, and ultimately, aid the field in moving toward earlier intervention at a stage of AD when some disease-modifying therapies may be most efficacious. Copyright © 2011. Published by Elsevier Inc.
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                Author and article information

                Contributors
                michael.scholl@neuro.gu.se
                Journal
                Alzheimers Dement (Amst)
                Alzheimers Dement (Amst)
                10.1002/(ISSN)2352-8729
                DAD2
                Alzheimer's & Dementia : Diagnosis, Assessment & Disease Monitoring
                John Wiley and Sons Inc. (Hoboken )
                2352-8729
                20 July 2021
                2021
                : 13
                : 1 ( doiID: 10.1002/dad2.v13.1 )
                : e12217
                Affiliations
                [ 1 ] Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy University of Gothenburg Gothenburg Sweden
                [ 2 ] Wallenberg Centre for Molecular and Translational Medicine University of Gothenburg Gothenburg Sweden
                [ 3 ] Department of Neurology Washington University in St. Louis St. Louis Missouri USA
                [ 4 ] Department of Psychological & Brain Sciences Washington University in St. Louis St. Louis Missouri USA
                [ 5 ] German Center for Neurodegenerative Diseases (DZNE) Magdeburg Germany
                [ 6 ] Clinical Memory Research Unit, Department of Clinical Sciences Malmö Lund University Lund Sweden
                [ 7 ] Dementia Research Centre, Queen Square Institute of Neurology University College London London UK
                [ 8 ] Center for Alzheimer Research and Treatment Department of Neurology, Brigham and Women's Hospital Harvard Medical School Boston Massachusetts USA
                [ 9 ] Department of Neurology, Massachusetts General Hospital Harvard Medical School Boston Massachusetts USA
                Author notes
                [*] [* ] Correspondence

                Michael Schöll, Sahlgrenska University Hospital, MedTech West, Röda Stråket 10B, Gothenburg 413 45, Sweden.

                Email: michael.scholl@ 123456neuro.gu.se

                Author information
                https://orcid.org/0000-0001-7800-1781
                Article
                DAD212217
                10.1002/dad2.12217
                8290833
                34295959
                3f39ce47-915a-4c8c-94ac-39c814603fac
                © 2021 The Authors. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 30 May 2021
                : 15 February 2021
                : 04 June 2021
                Page count
                Figures: 4, Tables: 2, Pages: 19, Words: 12566
                Funding
                Funded by: National Institutes of Health , doi 10.13039/100000002;
                Award ID: R01 AG057840
                Award ID: P01 AG003991
                Funded by: Sahlgrenska Academy , doi 10.13039/501100005761;
                Funded by: Anna‐Lisa och Bror Björnssons Foundation
                Funded by: Handlanden Hjalmar Svensson Foundation
                Funded by: Carin Mannheimers Prize for Junior Researchers
                Funded by: Gun & Bertil Stohnes Foundation
                Funded by: Fredrik och Ingrid Thurings Foundation
                Funded by: Swedish Neuropsychological Society
                Funded by: BrightFocus Foundation , doi 10.13039/100006312;
                Award ID: A2018202S
                Funded by: Knut and Alice Wallenberg Foundation (Wallenberg Centre for Molecular and Translational Medicine Fellow
                Award ID: KAW 2014.0363
                Funded by: Swedish Research Council
                Award ID: #2017‐02869
                Funded by: Swedish government and the County Councils ALF‐agreement
                Award ID: #ALFGBG‐813971
                Funded by: European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska‐Curie
                Award ID: 843074
                Funded by: Kockska Foundation
                Funded by: Alzheimerfonden , doi 10.13039/501100008599;
                Funded by: National Institute on Aging , doi 10.13039/100000049;
                Award ID: K23 Award
                Categories
                Review Article
                Cognitive & Behavioral Assessment
                Custom metadata
                2.0
                2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.4 mode:remove_FC converted:20.07.2021

                clinical assessment,clinical trials,cognition,computerized assessment,digital cognitive biomarkers,home‐based assessment,preclinical alzheimer's disease,smartphone‐based assessment

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