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Validity and Cultural Generalisability of a 5-Minute AI-Based, Computerised Cognitive Assessment in Mild Cognitive Impairment and Alzheimer's Dementia
Kalafatis C, Modarres MH, Apostolou P, Marefat H, Khanbagi M, Karimi H, Vahabi Z, Aarsland D et al.. Frontiers in psychiatry, 2021-07-22
Topic: Brain imaging, connectivity and assessment
The ICA demonstrated convergent validity with MoCA (Pearson r=0.58, p<0.0001) and ACE (r=0.62, p<0.0001). The ICA AI model was able to detect cognitive impairment with an AUC of 81% for MCI patients, and 88% for mild AD patients. The AI model demonstrated improved performance with increased training data and showed generalisability in performance from one population to another. The ICA correlation of 0.17 ( p = 0.01) with education years is considerably smaller than that of MoCA ( r = 0.34, p < 0.0001) and ACE ( r = 0.41, p < 0.0001) which displayed significant correlations. In a separate study the ICA demonstrated no significant practise effect over the duration of the study. The ICA can support clinicians by aiding accurate diagnosis of MCI and AD and is appropriate for large-scale screening of cognitive impairment. The ICA is unbiased by differences in language, culture, and education.
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APA 7th
Kalafatis, C., Modarres, M. H., Apostolou, P., Marefat, H., Khanbagi, M., Karimi, H., et al. (2021). Validity and Cultural Generalisability of a 5-Minute AI-Based, Computerised Cognitive Assessment in Mild Cognitive Impairment and Alzheimer's Dementia. Frontiers in psychiatry. https://doi.org/10.3389/fpsyt.2021.706695
Vancouver
Kalafatis C, Modarres MH, Apostolou P, Marefat H, Khanbagi M, Karimi H, et al. Validity and Cultural Generalisability of a 5-Minute AI-Based, Computerised Cognitive Assessment in Mild Cognitive Impairment and Alzheimer's Dementia. Frontiers in psychiatry. 2021. doi:10.3389/fpsyt.2021.706695. PMID: 34366938.
BibTeX
@article{kalafatis2021-34366938,
author = {Kalafatis, C. and Modarres, M. H. and Apostolou, P. and Marefat, H. and Khanbagi, M. and Karimi, H. and Vahabi, Z. and Aarsland, D. and others},
title = {{Validity and Cultural Generalisability of a 5-Minute AI-Based, Computerised Cognitive Assessment in Mild Cognitive Impairment and Alzheimer's Dementia}},
journal = {Frontiers in psychiatry},
year = {2021},
doi = {10.3389/fpsyt.2021.706695},
pmid = {34366938},
url = {https://doi.org/10.3389/fpsyt.2021.706695}
}
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
Key findings
- The ICA demonstrated convergent validity with MoCA (Pearson r=0.58, p<0.0001) and ACE (r=0.62, p<0.0001).
- The ICA AI model was able to detect cognitive impairment with an AUC of 81% for MCI patients, and 88% for mild AD patients.
- The AI model demonstrated improved performance with increased training data and showed generalisability in performance from one population to another.
- The ICA correlation of 0.17 ( p = 0.01) with education years is considerably smaller than that of MoCA ( r = 0.34, p < 0.0001) and ACE ( r = 0.41, p < 0.0001) which displayed significant correlations.
- In a separate study the ICA demonstrated no significant practise effect over the duration of the study.
Study details
- Participants230
- Evidence strengthLow
How this study scored 52/100
Published in a peer-reviewed journal. Scored zero for study design, effect reported 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 and multi-centre collaboration, so those were left out: it earned 30 of the 58 points we could judge it on, which is 52 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Frontiers in psychiatry) |
| 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 | 3 / 5 | 2021 — within 6 year(s) of the newest study here |
| Sample size | 2 / 4 | 230 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| 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 34366938) |
| Free to read | 2 / 2 | Free to read |
| Points | 30 / 58 | Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 30 of the 58 points we could judge it on is 52 out of 100. |
| Total | 52 / 100 | — |
What each of these 20 components measures, and what this score is not →
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