Fear of falling in essential tremor: a balance-related symptom independent of cognitive status
Bibliographic record
Abstract
Introduction: Essential tremor (ET) impairs motor control and postural stability. Patients with late-onset ET may also present cognitive deficits, further compromising balance in older adults. Objective: The aim of this study was to investigate whether impairments in balance and cognition are associated with fear of falling in individuals with ET. Methods: Tremor severity was assessed using the Fahn–Tolosa–Marin Tremor Rating Scale (FTM-TRS). Cognitive function was evaluated with the Montreal Cognitive Assessment (MoCA) and the Cerebellar Cognitive Affective Syndrome Scale (CCAS). Balance was assessed using the Fall Efficacy Scale (FES), Performance-Oriented Mobility Assessment (POMA), and Berg Balance Scale (BBS). Instrumental analysis via Mobility Lab® software provided data on postural sway and gait acceleration. Results: In total, 12 patients were included (42% female), aged 56–78 years (mean: 70.1; SD: 6.9). Age at tremor onset ranged from 28 to 65 years (mean: 45.8; SD: 14.9). Mean FTM-TRS scores: part A = 12.9 (SD: 7.5), part B = 7.8 (SD: 3.9), part C = 6.2 (SD: 4.2). FES correlated negatively with BBS (r = -0.71; p = 0.010) and POMA (r = -0.51; p = 0.049). Among acceleration parameters, the strongest correlations with FES were for jerkiness: area (r = 0.84; p < 0.001), coronal (r = 0.83; p = 0.001), and sagittal (r = 0.79; p = 0.002). Sway area, centroid frequency, and sagittal sway frequency also correlated with FES (r = 0.68, p = 0.016; r = 0.66, p = 0.019; r = 0.67, p = 0.018). No significant correlation was found between FES and age (r = 0.44; p = 0.09), MoCA (r = 0.32; p = 0.355), or CCAS (r = -0.35; p = 0.253). Conclusion: Fear of falling was strongly associated with impaired balance and postural instability, but not with cognitive performance.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".