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Effective differentiation of mild cognitive impairment by functional brain graph analysis and computerized testing
Rok Požar, Bruno Giordani, Voyko Kavcic. PloS one, 2020-03-16
Topic: Brain imaging, connectivity and assessment
Community-dwelling African American elders are twice as likely to develop mild cognitive impairment (MCI) or Alzheimer's disease and related dementias than older white Americans and therefore represent a significant at-risk group in need of early monitoring. More extensive imaging or cerebrospinal fluid studies represent significant barriers due to cost and burden. We combined functional connectivity and graph theoretical measures, derived from resting-state electroencephalography (EEG) recordings, with computerized cognitive testing to identify differences between persons with MCI and healthy controls based on a sample of community-dwelling African American elders. We found a significant decrease in functional connectivity and a less integrated graph topology in persons with MCI. A combination of functional connectivity, topological and cognition measurements is powerful for prediction of MCI and combined measures are clearly more effective for prediction than using a single approach. Specifically, by combining cognition features with functional connectivity and topological features the prediction improved compared with the classification using features from single cognitive or EEG domains, with an accuracy of 86.5%, compared with the accuracy of 77.5% of the best single approach. Community-dwelling African American elders find EEG and computerized testing acceptable and results are promising in terms of differentiating between healthy controls and persons with MCI living in the community.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Požar, R., Giordani, B., & Kavcic, V. (2020). Effective differentiation of mild cognitive impairment by functional brain graph analysis and computerized testing. PloS one. https://doi.org/10.1371/journal.pone.0230099
Vancouver
Požar R, Giordani B, Kavcic V. Effective differentiation of mild cognitive impairment by functional brain graph analysis and computerized testing. PloS one. 2020. doi:10.1371/journal.pone.0230099. PMID: 32176709.
BibTeX
@article{pozar2020-32176709,
author = {Požar, Rok and Giordani, Bruno and Kavcic, Voyko},
title = {{Effective differentiation of mild cognitive impairment by functional brain graph analysis and computerized testing}},
journal = {PloS one},
year = {2020},
doi = {10.1371/journal.pone.0230099},
pmid = {32176709},
url = {https://doi.org/10.1371/journal.pone.0230099}
}
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
Key findings
- Community-dwelling African American elders are twice as likely to develop mild cognitive impairment (MCI) or Alzheimer's disease and related dementias than older white Americans and therefore represent a significant at-risk group in need of early monitoring.
- More extensive imaging or cerebrospinal fluid studies represent significant barriers due to cost and burden.
- We found a significant decrease in functional connectivity and a less integrated graph topology in persons with MCI.
- Specifically, by combining cognition features with functional connectivity and topological features the prediction improved compared with the classification using features from single cognitive or EEG domains, with an accuracy of 86.5%, compared with the accuracy of 77.5% of the best single approach.
- Community-dwelling African American elders find EEG and computerized testing acceptable and results are promising in terms of differentiating between healthy controls and persons with MCI living in the community.
Study details
- Effect size86.5%; 77.5%
- Evidence strengthLow
How this study scored 43/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, studied in people and randomised / blinded because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record, multi-centre collaboration and free to read, so those were left out: it earned 24 of the 56 points we could judge it on, which is 43 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (PloS one) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 2 / 5 | 2020 — within 10 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 2 / 3 | Effect reported as a number, without an interval or test |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 32176709) |
| Free to read | — / 2 | Access not recorded — left out of this score |
| Points | 24 / 56 | Scored on 10 of 20 parts. We have no data for the rest, so they are left out: 24 of the 56 points we could judge it on is 43 out of 100. |
| Total | 43 / 100 | — |
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