Dual‐task gait and mild behavioral impairment: Findings on the interface between non‐cognitive dementia markers in the COMPASS‐ND study
Bibliographic record
Abstract
Abstract Background Mild behavioral impairment (MBI) and poor dual‐task gait performance are non‐cognitive markers for dementia. Both MBI and dual‐task gait performance have been associated with an increased risk of cognitive decline, but to our knowledge the relationship between them has yet to be investigated. Method Cross‐sectional data from 193 non‐demented participants (10 cognitively normal, 48 subjective cognitive decline, 135 mild cognitive impairment; MCI) in the COMPASS‐ND study (February 2020 release) were analyzed. MBI was approximated using the Neuropsychiatric Inventory Questionnaire (NPI‐Q) using a published algorithm. Dual‐task gait cost (DTGC), operationalized as the percentage difference between dual‐task and preferred walking speeds, was assessed under three cognitive tasks: animal naming, counting backwards by one, and serial seven subtractions. Multivariable linear regression was used to determine the association between global MBI burden and DTGC, adjusting for age, sex, years of education, and Montreal Cognitive Assessment (MoCA) score, or diagnosis. Models were additionally fitted for the subgroup of participants with MCI alone. Mediation analyses were conducted using bootstrapping to determine if the association between MBI and DTGC was mediated by global cognition (MoCA), executive function (Trail Making B), verbal (Rey Auditory Verbal Learning Test) or working (Digit Span) memory. Result Participants on average were 72.4 years old (52.8% female) and had completed 15.8 years of education. MBI symptoms were observed in 46.6% of participants. Greater overall MBI burden was associated with reduced gait speed and higher DTGC for all three gait conditions in MCI, and in all participants without dementia when controlling for diagnosis or MoCA (Table 1), except for DTGC under animal naming conditions when controlling for MoCA. The associations between MBI and DTGC were mediated by executive function but not global cognition, verbal or working memory (Table 2). Conclusion In this group of older adults at risk but without dementia (SCD and MCI spectrum), MBI is associated with DTGC, which in itself is a dementia risk marker. Our findings support the role of these non‐cognitive dementia markers in the detection of at‐risk individuals. Identification of older adults at risk of incident dementia may be enhanced by considering MBI and DTGC in conjunction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".