ArticleSystematic reviews2020
Neuroimaging and analytical methods for studying the pathways from mild cognitive impairment to Alzheimer's disease: protocol for a rapid systematic review.
Article in Systematic reviews, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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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.
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Who cites it
6 citing papers in PubMed, 18 citations in OpenAlex.
- Relationship Between Depression and Neurodegeneration: Risk Factor, Prodrome, Consequence, or Something Else? A Scoping Review.Biomedicines · 2025Review
- Research Progress and Trends in Exercise Interventions for Mild Cognitive Impairment: A Bibliometric Visualization Analysis Using CiteSpace.Journal of multidisciplinary healthcare · 2025Review
- Prediction of Alzheimer's disease progression within 6 years using speech: A novel approach leveraging language models.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Online COVID-19 diagnosis prediction using complete blood count: an innovative tool for public health.BMC public health · 2023Article
- Article
- Association of Perceived Neighborhood Environments With Cognitive Function in Older Adults.Journal of gerontological nursing · 2023Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAlzheimer's disease (AD) is a neurodegenerative disorder commonly associated with deficits of cognition and changes in behavior. Mild cognitive impairment (MCI) is the prodromal stage of AD that is defined by slight cognitive decline. Not all with MCI progress to AD dementia. Thus, the accurate prediction of progression to Alzheimer's, particularly in the stage of MCI could potentially offer developing treatments to delay or prevent the transition process. The objective of the present study is to investigate the most recent neuroimaging procedures in the domain of prediction of transition from MCI to AD dementia for clinical applications and to systematically discuss the machine learning techniques used for the prediction of MCI conversion.
methodsElectronic databases including PubMed, SCOPUS, and Web of Science will be searched from January 1, 2017, to the date of search commencement to provide a rapid review of the most recent studies that have investigated the prediction of conversion from MCI to Alzheimer's using neuroimaging modalities in randomized trial or observational studies. Two reviewers will screen full texts of included papers using predefined eligibility criteria. Studies will be included if addressed research on AD dementia and MCI, explained the results in a way that would be able to report the performance measures such as the accuracy, sensitivity, and specificity. Only studies addressed Alzheimer's type of dementia and its early-stage MCI using neuroimaging modalities will be included. We will exclude other forms of dementia such as vascular dementia, frontotemporal dementia, and Parkinson's disease. The risk of bias in individual studies will be appraised using an appropriate tool. If feasible, we will conduct a random effects meta-analysis. Sensitivity analyses will be conducted to explore the potential sources of heterogeneity. DISCUSSION: The information gathered in our study will establish the extent of the evidence underlying the prediction of conversion to AD dementia from its early stage and will provide a rigorous and updated synthesis of neuroimaging modalities allied with the data analysis techniques used to measure the brain changes during the conversion process. SYSTEMATIC REVIEW REGISTRATION: PROSPERO,CRD42019133402.
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