Older Women with Age‐Related Macular Degeneration Have a Greater Risk of Falls: A Physiological Profile Assessment Study
Bibliographic record
Abstract
OBJECTIVES: To determine whether older women with exudative age-related macular degeneration (AMD) are at greater risk of falls. DESIGN: Cross-sectional study. SETTING: A hospital-based ophthalmology clinic in Vancouver, Canada. PARTICIPANTS: One hundred fifteen older (aged > or = 70) community-dwelling women with exudative AMD (AMD cohort) and two control groups: 54 community-dwelling women without exudative AMD drawn from the same community (non-AMD cohort) and 341 community-dwelling Australian women (Australian normative cohort). MEASUREMENTS: Participants were assessed for falls risk using the short-form Physiological Profile Assessment (PPA), which provides a fall risk index score and subcomponent measures of vision, proprioception, strength, reaction time, and postural sway. RESULTS: The mean fall risk index score in the AMD cohort (3.20) was significantly greater than that of the non-AMD cohort (1.21; P<.001), and fall risk scores increased with age to a greater extent in the AMD cohort. The higher fall risk scores in the AMD cohort resulted from significantly worse performance on each PPA test, not just the test of vision. The AMD cohort also performed worse than the Australian normative cohort in tests of vision, reaction time, and postural sway. CONCLUSION: Older women with AMD have impaired balance, slow visual reaction times, and poor vision, which in combination result in a significantly greater risk of falls than population norms. These deficits are clearly indicated in the physiological falls profile for the group. Strategies to enhance balance may be particularly beneficial to prevent falls in this group.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| 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".