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Differential diagnosis of Alzheimer’s disease using spectrochemical analysis of blood

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, September 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

news
18 news outlets
blogs
5 blogs
twitter
14 tweeters
facebook
2 Facebook pages
googleplus
1 Google+ user

Citations

dimensions_citation
30 Dimensions

Readers on

mendeley
102 Mendeley
Title
Differential diagnosis of Alzheimer’s disease using spectrochemical analysis of blood
Published in
Proceedings of the National Academy of Sciences of the United States of America, September 2017
DOI 10.1073/pnas.1701517114
Pubmed ID
Authors

Maria Paraskevaidi, Camilo L. M. Morais, Kássio M. G. Lima, Julie S. Snowden, Jennifer A. Saxon, Anna M. T. Richardson, Matthew Jones, David M. A. Mann, David Allsop, Pierre L. Martin-Hirsch, Francis L. Martin

Abstract

The progressive aging of the world's population makes a higher prevalence of neurodegenerative diseases inevitable. The necessity for an accurate, but at the same time, inexpensive and minimally invasive, diagnostic test is urgently required, not only to confirm the presence of the disease but also to discriminate between different types of dementia to provide the appropriate management and treatment. In this study, attenuated total reflection FTIR (ATR-FTIR) spectroscopy combined with chemometric techniques were used to analyze blood plasma samples from our cohort. Blood samples are easily collected by conventional venepuncture, permitting repeated measurements from the same individuals to monitor their progression throughout the years or evaluate any tested drugs. We included 549 individuals: 347 with various neurodegenerative diseases and 202 age-matched healthy individuals. Alzheimer's disease (AD; n = 164) was identified with 70% sensitivity and specificity, which after the incorporation of apolipoprotein ε4 genotype (APOE ε4) information, increased to 86% when individuals carried one or two alleles of ε4, and to 72% sensitivity and 77% specificity when individuals did not carry ε4 alleles. Early AD cases (n = 14) were identified with 80% sensitivity and 74% specificity. Segregation of AD from dementia with Lewy bodies (DLB; n = 34) was achieved with 90% sensitivity and specificity. Other neurodegenerative diseases, such as frontotemporal dementia (FTD; n = 30), Parkinson's disease (PD; n = 32), and progressive supranuclear palsy (PSP; n = 31), were included in our cohort for diagnostic purposes. Our method allows for both rapid and robust diagnosis of neurodegeneration and segregation between different dementias.

Twitter Demographics

The data shown below were collected from the profiles of 14 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 102 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 24%
Student > Master 22 22%
Student > Ph. D. Student 12 12%
Student > Bachelor 11 11%
Professor > Associate Professor 5 5%
Other 18 18%
Unknown 10 10%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 17%
Medicine and Dentistry 13 13%
Agricultural and Biological Sciences 13 13%
Neuroscience 10 10%
Physics and Astronomy 7 7%
Other 25 25%
Unknown 17 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 178. 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 27 February 2018.
All research outputs
#88,600
of 14,473,834 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#2,126
of 82,633 outputs
Outputs of similar age
#3,752
of 270,165 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#70
of 944 outputs
Altmetric has tracked 14,473,834 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 82,633 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.8. This one has done particularly well, scoring higher than 97% 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 270,165 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 98% of its contemporaries.
We're also able to compare this research output to 944 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.