Balance Impairments as Differential Markers of Dementia Disease Subtype

Ríona McArdle*, Stephanie Pratt, Christopher Buckley, Silvia Del Din, Brook Galna, Alan J. Thomas, Lynn Rochester, Lisa Alcock

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Background: Accurately differentiating dementia subtypes, such as Alzheimer’s disease (AD) and Lewy body disease [including dementia with Lewy bodies (DLB) and Parkinson’s disease dementia (PDD)] is important to ensure appropriate management and treatment of the disease. Similarities in clinical presentation create difficulties for differential diagnosis. Simple supportive markers, such as balance assessments, may be useful to the diagnostic toolkit. This study aimed to identify differences in balance impairments between different dementia disease subtypes and normal aging using a single triaxial accelerometer.

Methods: Ninety-seven participants were recruited, forming four groups: cognitive impairment due to Alzheimer’s disease (AD group; n = 31), dementia with Lewy bodies (DLB group; n = 26), Parkinson’s disease dementia (PDD group; n = 13), and normal aging controls (n = 27). Participants were asked to stand still for 2 minutes in a standardized position with their eyes open while wearing a single triaxial accelerometer on their lower back. Seven balance characteristics were derived, including jerk (combined, mediolateral, and anterior–posterior), root mean square (RMS; combined, mediolateral, and anterior–posterior), and ellipsis. Mann–Whitney U tests identified the balance differences between groups. Receiver operating characteristics and area under the curve (AUC) determined the overall accuracy of the selected balance characteristics.

Results: The PDD group demonstrated higher RMS [combined (p = 0.001), mediolateral (p = 0.005), and anterior–posterior (p = 0.001)] and ellipsis scores (p < 0.002) than the AD group (AUC = 0.71–0.82). The PDD group also demonstrated significantly impaired balance across all characteristics (p ≤ 0.001) compared to the controls (AUC = 0.79–0.83). Balance differences were not significant between PDD and DLB (AUC = 0.69–0.74), DLB and AD (AUC = 0.50–0.65), DLB and controls (AUC = 0.62–0.68), or AD and controls (AUC = 0.55–0.67) following Bonferroni correction.

Discussion: Although feasible and quick to conduct, key findings suggest that an accelerometer-based balance during quiet standing does not differentiate dementia disease subtypes accurately. Assessments that challenge balance more, such as gait or standing with eyes closed, may prove more effective to support differential diagnosis.
Original languageEnglish
Article number639337
Pages (from-to)1-10
Number of pages10
JournalFrontiers in Bioengineering and Biotechnology
Volume9
DOIs
Publication statusPublished - 11 Mar 2021

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