Evidence map›Paper›PMID 32241302›Full record

ArticleSystematic reviews2020

Neuroimaging and analytical methods for studying the pathways from mild cognitive impairment to Alzheimer's disease: protocol for a rapid systematic review.

Maryam Ahmadzadeh, Gregory J Christie, Theodore D Cosco, Sylvain Moreno

Open access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

6 citing papers in PubMed, 18 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 2 countries.

Maryam AhmadzadehDigital Health Hub, Simon Fraser University, 4190 Galleria 4, 250 - 13450 102 Ave, Surrey, BC, V3T 0A3, Canada.
Gregory J ChristieDigital Health Hub, Simon Fraser University, 4190 Galleria 4, 250 - 13450 102 Ave, Surrey, BC, V3T 0A3, Canada.
Theodore D CoscoGerontology Research Center, Simon Fraser University, 2800-515 West Hastings St, Vancouver, V6B 5 K3, Canada.
Sylvain MorenoDigital Health Hub, Simon Fraser University, 4190 Galleria 4, 250 - 13450 102 Ave, Surrey, BC, V3T 0A3, Canada. sylvain_moreno@sfu.ca.
Simon Fraser University · CAUniversity of Oxford · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Alzheimer DiseaseCognitive DysfunctionBrainCognitionDisease ProgressionHumansMeta-Analysis as TopicNeuroimagingSystematic Reviews as TopicAlzheimerConversionData analysisMachine learningMild cognitive impairmentModalityNeuroimagingPredictionSystematic review

Identifiers

PMID32241302
PMCPMC7118884
OpenAlexW3014472732

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.