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A remote digital memory composite to detect cognitive impairment in memory clinic samples in unsupervised settings using mobile devices
Berron D, Glanz W, Clark L, Basche K, Grande X, Güsten J, Billette OV, Hempen I et al.. NPJ digital medicine, 2024-03-26
Topic: Brain imaging, connectivity and assessment
Remote monitoring of cognition holds the promise to facilitate case-finding in clinical care and the individual detection of cognitive impairment in clinical and research settings. In the context of Alzheimer's disease, this is particularly relevant for patients who seek medical advice due to memory problems. Here, we develop a remote digital memory composite (RDMC) score from an unsupervised remote cognitive assessment battery focused on episodic memory and long-term recall and assess its construct validity, retest reliability, and diagnostic accuracy when predicting MCI-grade impairment in a memory clinic sample and healthy controls. A total of 199 participants were recruited from three cohorts and included as healthy controls (n = 97), individuals with subjective cognitive decline (n = 59), or patients with mild cognitive impairment (n = 43). Participants performed cognitive assessments in a fully remote and unsupervised setting via a smartphone app. The derived RDMC score is significantly correlated with the PACC5 score across participants and demonstrates good retest reliability. Diagnostic accuracy for discriminating memory impairment from no impairment is high (cross-validated AUC = 0.83, 95% CI [0.66, 0.99]) with a sensitivity of 0.82 and a specificity of 0.72. Thus, unsupervised remote cognitive assessments implemented in the neotiv digital platform show good discrimination between cognitively impaired and unimpaired individuals, further demonstrating that it is feasible to complement the neuropsychological assessment of episodic memory with unsupervised and remote assessments on mobile devices. This contributes to recent efforts to implement remote assessment of episodic memory for case-finding and monitoring in large research studies and clinical care.
Key findings
- The derived RDMC score is significantly correlated with the PACC5 score across participants and demonstrates good retest reliability.
Study details
- Participants97
- Effect sizeAUC = 0.83
- Evidence strengthLow
How this study scored 57/100
Published in a peer-reviewed journal. Scored zero for study design 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 33 of the 58 points we could judge it on, which is 57 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (NPJ digital medicine) |
| 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 | 4 / 5 | 2024 — within 3 year(s) of the newest study here |
| Sample size | 1 / 4 | 97 participants |
| Effect reported | 3 / 3 | Effect reported with a statistic (interval, p-value, ratio or similar) |
| 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 38532080) |
| Free to read | 2 / 2 | Free to read |
| Points | 33 / 58 | Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 33 of the 58 points we could judge it on is 57 out of 100. |
| Total | 57 / 100 | — |
What each of these 20 components measures, and what this score is not →
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APA 7th
Berron, D., Glanz, W., Clark, L., Basche, K., Grande, X., Güsten, J., et al. (2024). A remote digital memory composite to detect cognitive impairment in memory clinic samples in unsupervised settings using mobile devices. NPJ digital medicine. https://doi.org/10.1038/s41746-024-00999-9
Vancouver
Berron D, Glanz W, Clark L, Basche K, Grande X, Güsten J, et al. A remote digital memory composite to detect cognitive impairment in memory clinic samples in unsupervised settings using mobile devices. NPJ digital medicine. 2024. doi:10.1038/s41746-024-00999-9. PMID: 38532080.
BibTeX
@article{berron2024-38532080,
author = {Berron, D. and Glanz, W. and Clark, L. and Basche, K. and Grande, X. and Güsten, J. and Billette, O. V. and Hempen, I. and others},
title = {{A remote digital memory composite to detect cognitive impairment in memory clinic samples in unsupervised settings using mobile devices}},
journal = {NPJ digital medicine},
year = {2024},
doi = {10.1038/s41746-024-00999-9},
pmid = {38532080},
url = {https://doi.org/10.1038/s41746-024-00999-9}
}
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