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Evaluation of a research diagnostic algorithm for DSM-5 neurocognitive disorders in a population-based cohort of older adults

Overview of attention for article published in Alzheimer's Research & Therapy, March 2017
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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 (82nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

Mentioned by

news
1 news outlet
twitter
2 tweeters

Citations

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28 Dimensions

Readers on

mendeley
104 Mendeley
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Title
Evaluation of a research diagnostic algorithm for DSM-5 neurocognitive disorders in a population-based cohort of older adults
Published in
Alzheimer's Research & Therapy, March 2017
DOI 10.1186/s13195-017-0246-x
Pubmed ID
Authors

Ranmalee Eramudugolla, Moyra E. Mortby, Perminder Sachdev, Chantal Meslin, Rajeev Kumar, Kaarin J. Anstey

Abstract

There is little information on the application and impact of revised criteria for diagnosing dementia and mild cognitive impairment (MCI), now termed major and mild neurocognitive disorders (NCDs) in the DSM-5. We evaluate a psychometric algorithm for diagnosing DSM-5 NCDs in a community-dwelling sample, and characterize the neuropsychological and functional profile of expert-diagnosed DSM-5 NCDs relative to DSM-IV dementia and International Working Group criteria for MCI. A population-based sample of 1644 adults aged 72-78 years was assessed. Algorithmic diagnostic criteria used detailed neuropsychological data, medical history, longitudinal cognitive performance, and informant interview. Those meeting all criteria for at least one diagnosis had data reviewed by a neurologist (expert diagnosis) who achieved consensus with a psychiatrist for complex cases. The algorithm accurately classified DSM-5 major NCD (area under the curve (AUC) = 0.95, 95% confidence interval (CI) 0.92-0.97), DSM-IV dementia (AUC = 0.91, 95% CI 0.85-0.97), DSM-5 mild NCD (AUC = 0.75, 95% CI 0.70-0.80), and MCI (AUC = 0.76, 95% CI 0.72-0.81) when compared to expert diagnosis. Expert diagnosis of dementia using DSM-5 criteria overlapped with 90% of DSM-IV dementia cases, but resulted in a 127% increase in diagnosis relative to DSM-IV. Additional cases had less severe memory, language impairment, and instrumental activities of daily living (IADL) impairments compared to cases meeting DSM-IV criteria for dementia. DSM-5 mild NCD overlapped with 83% of MCI cases and resulted in a 19% increase in diagnosis. These additional cases had a subtly different neurocognitive profile to MCI cases, including poorer social cognition. DSM-5 NCD criteria can be operationalized in a psychometric algorithm in a population setting. Expert diagnosis using DSM-5 NCD criteria captured most cases with DSM-IV dementia and MCI in our sample, but included many additional cases suggesting that DSM-5 criteria are broader in their categorization.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 104 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Unknown 103 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 17 16%
Student > Ph. D. Student 12 12%
Student > Bachelor 11 11%
Researcher 8 8%
Other 8 8%
Other 24 23%
Unknown 24 23%
Readers by discipline Count As %
Medicine and Dentistry 22 21%
Psychology 20 19%
Nursing and Health Professions 12 12%
Neuroscience 8 8%
Business, Management and Accounting 3 3%
Other 14 13%
Unknown 25 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 02 April 2017.
All research outputs
#2,841,643
of 22,958,253 outputs
Outputs from Alzheimer's Research & Therapy
#680
of 1,238 outputs
Outputs of similar age
#54,855
of 310,371 outputs
Outputs of similar age from Alzheimer's Research & Therapy
#12
of 25 outputs
Altmetric has tracked 22,958,253 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,238 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.0. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
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 310,371 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 25 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 52% of its contemporaries.