The Effect of Unilateral Vestibular Loss on Standing Balance During Postural Threat
Bibliographic record
Abstract
OBJECTIVE: Vestibular deficit patients have an increased fall risk and fear of falling. Postural threat, known to increase balance-related fear and anxiety, influences vestibular gains during quiet standing in young healthy adults. The current study examined whether there is a similar relationship for peripheral unilateral vestibular loss (UVL) patients in comparison to age-matched healthy controls (HC). SETTING: University laboratory. STUDY DESIGN: Prospective laboratory study. PATIENTS AND CONTROLS: Eleven UVL patients, nine with vestibular neurectomy. Eleven aged-matched HCs. MAIN OUTCOME MEASURES: Subjects stood on a hydraulic lift placed at two heights: low (0.8 m, away from the edge) and high (3.2 m, at the edge). Amplitude (root mean square), mean power frequency (MPF), and mean position were analyzed for center of foot pressure (COP) and 90% ranges for angle amplitude and velocity for trunk sway. RESULTS: Group interactions were strongest for anterior-posterior (AP) COP and trunk pitch angle. AP lean away from the edge was greater in HCs than UVLs. HCs, but not UVLs had a decrease in root mean square AP COP with height. Trunk pitch sway was changed similarly. Both groups had increased trunk pitch velocity at height. Changes with height were less for roll: MPF of lateral COP increased with height for UVLs with no changes for HCs, and trunk roll amplitude decreased for both groups. CONCLUSIONS: This report provides evidence for a differential effect of height induced postural threat on balance control between UVLs and HCs presumably due to the reduced vestibular-spinal gain in UVL subjects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".