Effect of Stroke on Fall Rate, Location and Predictors: A Prospective Comparison of Older Adults with and without Stroke
Bibliographic record
Abstract
BACKGROUND: The literature suggests that stroke is a major risk factor for falls, but there is a lack of prospective, controlled studies which quantify fall-risk after stroke. The purpose of this study was to compare the rates, location and predictors among individuals recently discharged home from stroke rehabilitation to age and sex matched controls. METHODOLOGY/PRINCIPAL FINDINGS: A sample of 80 people with stroke and 90 controls received baseline assessments of balance, mobility and balance confidence. Falls were recorded prospectively over 13 months for both groups. Group differences in fall rates and contribution of clinical measures to falls were determined using negative binomial regression. Fall location was compared between groups using χ(2) statistics. The rate of falls for individuals with stroke was 1.77 times the rate for the control group. People with stroke were more likely to fall at home. Poorer balance (Berg Balance Scale) was associated with greater falls for both stroke and control groups (incidence rate ratio [IRR]: 0.908 and IRR: 0.877 respectively). A faster Timed Up and Go Test was associated with greater falls for the stroke group (IRR: 0.955) while better walking endurance (Six Minute Walk Test) was associated with greater falls for the controls (IRR: 1.004). Balance confidence was not an independent predictor in either group. CONCLUSIONS: Individuals recently discharged home are at greater risk of falling than individuals without stroke. Attention to home environment is warranted. Balance function can predict falls for both people with stroke and age and sex matched controls. Increased mobility may increase exposure to fall opportunities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".