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Predicting Alzheimer's disease development: a comparison of cognitive criteria and associated neuroimaging biomarkers

Overview of attention for article published in Alzheimer's Research & Therapy, November 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

news
2 news outlets
twitter
5 tweeters

Citations

dimensions_citation
28 Dimensions

Readers on

mendeley
92 Mendeley
citeulike
1 CiteULike
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Title
Predicting Alzheimer's disease development: a comparison of cognitive criteria and associated neuroimaging biomarkers
Published in
Alzheimer's Research & Therapy, November 2015
DOI 10.1186/s13195-015-0152-z
Pubmed ID
Authors

Brandy L. Callahan, Joel Ramirez, Courtney Berezuk, Simon Duchesne, Sandra E. Black

Abstract

The definition of "objective cognitive impairment" in current criteria for mild cognitive impairment (MCI) varies considerably between research groups and clinics. This study aims to compare different methods of defining memory impairment to improve prediction models for the development of Alzheimer's disease (AD) from baseline to 24 months. The sensitivity and specificity of six methods of defining episodic memory impairment (< -1, -1.5 or -2 standard deviations [SD] on one or two memory tests) were compared in 494 non-demented seniors from the Alzheimer's Disease Neuroimaging Initiative using the area under the curve (AUC) for receiver operating characteristic analysis. The added value of non-memory measures (language and executive function) and biomarkers (hippocampal and white-matter hyperintensity volume, brain parenchymal fraction [BPF], and APOEε4 status) was investigated using logistic regression. Baseline scores < -1 SD on two memory tests predicted AD with 75.91 % accuracy (AUC = 0.80). Only APOE ε4 status further improved prediction (B = 1.10, SE = 0.45, p = .016). A < -1.5 SD cut-off on one test had 66.60 % accuracy (AUC = 0.77). Prediction was further improved using Trails B/A ratio (B = 0.27, SE = 0.13, p = .033), BPF (B = -15.97, SE = 7.58, p = .035), and APOEε4 status (B = 1.08, SE = 0.45, p = .017). A cut-off of < -2 SD on one memory test (AUC = 0.77, SE = 0.03, 95 % CI 0.72-0.82) had 76.52 % accuracy in predicting AD. Trails B/A ratio (B = 0.31, SE = 0.13, p = .017) and APOE ε4 status (B = 1.07, SE = 0.46, p = .019) improved predictive accuracy. Episodic memory impairment in MCI should be defined as scores < -1 SD below normative references on at least two measures. Clinicians or researchers who administer a single test should opt for a more stringent cut-off and collect and analyze whole-brain volume. When feasible, ascertaining APOE ε4 status can further improve prediction.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Japan 1 1%
Turkey 1 1%
Canada 1 1%
Unknown 88 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 19 21%
Student > Ph. D. Student 16 17%
Researcher 15 16%
Student > Bachelor 7 8%
Student > Postgraduate 6 7%
Other 14 15%
Unknown 15 16%
Readers by discipline Count As %
Psychology 29 32%
Neuroscience 11 12%
Medicine and Dentistry 10 11%
Agricultural and Biological Sciences 4 4%
Chemistry 2 2%
Other 14 15%
Unknown 22 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 18. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 May 2016.
All research outputs
#1,202,583
of 16,875,777 outputs
Outputs from Alzheimer's Research & Therapy
#190
of 851 outputs
Outputs of similar age
#26,626
of 289,644 outputs
Outputs of similar age from Alzheimer's Research & Therapy
#17
of 60 outputs
Altmetric has tracked 16,875,777 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 851 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.3. This one has done well, scoring higher than 77% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 289,644 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 60 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.