Balance Impairment as a Risk Factor for Falls in Community-Dwelling Older Adults Who Are High Functioning: A Prospective Study
Bibliographic record
Abstract
BACKGROUND: Screening should have simple and easy-to-administer methods that identify impairments associated with future fall risk, but there is a lack of literature supporting validation for their use. OBJECTIVE: The aim of this study was to evaluate the independent contribution of balance assessment on future fall risk, using 5 methods to quantify balance impairment, for the outcomes "any fall" and "any injurious fall" in community-dwelling older adults who are higher functioning. DESIGN: This was a prospective cohort study. METHODS: A sample of 210 community-dwelling older adults (70% male, 30% female; mean age=79.9 years, SD=4.7) received a comprehensive geriatric assessment at baseline, which included the Berg Balance Scale to measure balance. Information on daily falls was collected for 12 months by each participant's monthly submission of a falls log calendar. RESULTS: Seventy-eight people (43%) fell, of whom 54 (30%) sustained an injurious fall and 32 (18%) had recurrent falls (> or =2 falls). Different balance measurement methods identified different numbers of people as impaired. Adjusted relative risk (RR) estimates for an increased risk of any fall were 1.58 (95% confidence interval [CI]=1.06, 2.35) for self-report of balance problems, 1.58 (95% CI=1.03, 2.41) for one-leg stance, and 1.46 (95% CI=1.02, 2.09) for limits of stability. An adjusted RR estimate for an increased risk of an injurious fall of 1.95 (95% CI=1.15, 3.31) was found for self-report of balance problems. Limitations The study was a secondary analysis of data. CONCLUSIONS: Not all methods of evaluating balance impairment are associated with falls. The number of people identified as having balance impairment varies with the measurement tool; therefore, the measurement tools are not interchangeable or equivalent in defining an at-risk population. The thresholds established in this study indicate individuals who should receive further comprehensive fall assessment and treatment to prevent falls.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".