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Accepted for/Published in: JMIR Aging

Date Submitted: Aug 13, 2024
Date Accepted: Dec 25, 2024

The final, peer-reviewed published version of this preprint can be found here:

Performance of a Digital Cognitive Assessment in Predicting Dementia Stages Delineated by the Dementia Severity Rating Scale: Retrospective Study

Huynh D, Sun K, Patterson M, Hosseini Ghomi R, Huang B

Performance of a Digital Cognitive Assessment in Predicting Dementia Stages Delineated by the Dementia Severity Rating Scale: Retrospective Study

JMIR Aging 2025;8:e65292

DOI: 10.2196/65292

PMID: 40009769

PMCID: 11882104

Performance of Digital Cognitive Assessment in Predicting Dementia Stages Delineated by Dementia Severity Rating Scale: Retrospective Study

  • Duong Huynh; 
  • Kevin Sun; 
  • Mary Patterson; 
  • Reza Hosseini Ghomi; 
  • Bin Huang

ABSTRACT

Background:

Dementia is characterized by impairments in an individual’s cognitive and functional abilities. Digital cognitive assessments have been shown to be effective in detecting mild cognitive impairment and dementia but whether they can stage the disease remains to be studied.

Objective:

In this study, we examined: (1) the correlation between scores obtained from BC-Assess, a digital cognitive assessment, and scores obtained from the Dementia Severity Rating Scale (DSRS), and (2) the accuracy of using the BC-Assess score to predict dementia stage delineated by the DSRS score. We also explored whether BC-Assess can be combined with information from the Katz Index of Independence in Activities of Daily Living (ADL) to obtain enhanced accuracy.

Methods:

Retrospective analysis was performed on a BrainCheck dataset containing 1,751 dementia patients with different cognitive and functional assessments completed for cognitive care planning, including the DSRS, the ADL, and the BC-Assess. The patients were staged according to their DSRS total score (DSRS-TS): 982 mild (DSRS-TS: 10-18), 656 moderate (19-26), and 113 severe (37-54) patients. Pearson correlation was used to assess the associations between BC-Assess overall score (BC-OS), ADL total score (ADL-TS), and DSRS-TS. Logistic regression was used to evaluate the possibility of using patients’ BC-OS and ADL-TS to predict their stage.

Results:

We find moderate Pearson correlations between DSRS-TS and BC-OS (r = -.53), between DSRS-TS and ADL-TS (r = -.55), and a weak correlation between BC-OS and ADL-TS (r = .37). Both BC-OS and ADL-TS significantly decrease with increasing severity. BC-OS demonstrates to be a good predictor of dementia stages, with area under the ROC curve (ROC-AUC) of classification using logistic regression ranging from .733 to .917. When BC-Assess is combined with ADL, higher prediction accuracies are achieved, with ROC-AUC ranging from .786 to .961.

Conclusions:

Our results suggest that BC-Assess could serve as an effective alternative tool to DSRS for grading dementia severity, particularly in cases where DSRS, or other global assessments, may be challenging to obtain due to logistical and time constraints.


 Citation

Please cite as:

Huynh D, Sun K, Patterson M, Hosseini Ghomi R, Huang B

Performance of a Digital Cognitive Assessment in Predicting Dementia Stages Delineated by the Dementia Severity Rating Scale: Retrospective Study

JMIR Aging 2025;8:e65292

DOI: 10.2196/65292

PMID: 40009769

PMCID: 11882104

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