Prevalence of Cognitive and Vestibular Impairment in Seniors Experiencing Falls
Bibliographic record
Abstract
BACKGROUND: Falls are a growing concern in seniors (≥65 yrs). Cognitive impairment (CI) and vestibular impairment (VI) increase fall risk. The aim of this study is to assess the prevalence of CI and VI in seniors experiencing falls. METHODS: Participants (≥65 yrs) with falls were recruited from Falls Prevention Programs (FPPs) and a Memory Clinic (MC). CI was assessed using the Montreal Cognitive Assessment at FPPs. VI was assessed at an MC and FFPs using the Head Impulse- (video + bedside), Headshake-, Dix-Hallpike test, and test of sensory interaction in balance. Questionnaires included Dizziness Handicap Inventory (DHI) and Activities-specific Balance Confidence Scale (ABC). RESULTS: Of 41 participants (29 FPPs, 12 MC); mean age was 80.1 ± 7.1 years, and 58.5% were female. Overall, 82.9% had VI. At FPPs, 76.0% had CI, and 72.3% had CI + VI. Bilateral vestibular hypofunction (BVH) was more common than unilateral vestibular hypofunction (UVH) (70.6% vs. 29.4%); p = 0.016. Dizziness Handicap (DHI) was not different between those with a VI (23.5 ± 23.9) versus without VI [PVI + no impairment] (10.0 ± 15.4); p = 0.160. Balance confidence (ABC) was lowest in VI but not significantly different between those with a VI (63.4 ± 27.3) versus without VI [PVI + no impairment] (85.0 ± 16.5); p = 0.053. CONCLUSIONS: VI and CI are prevalent in seniors experiencing falls. For seniors with history of falls, both cognitive and vestibular functions should be considered in the assessment and subsequent treatment. Screening enables earlier detection, targeted interventions, and prevention, reducing the clinical and financial impact.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".