Falls and injury prevention should be part of every stroke rehabilitation plan
Bibliographic record
Abstract
OBJECTIVE: To evaluate falls incidence, circumstances and consequences in people who return home after stroke rehabilitation, so that appropriate falls and injury prevention strategies can be developed. DESIGN: Prospective cohort study. SETTING: Community. SUBJECTS: Fifty-six subjects with stroke who were participating in a rehabilitation programme and returning to live in a community setting completed the study. MAIN MEASURES: Subjects completed a prospective falls diary for six months after discharge from rehabilitation, and were interviewed after falls. Physical function was measured by the Berg Balance Scale (BBS) and the Functional Independence Measure (FIM). RESULTS: Forty-six per cent of people (26/56) fell, with most falls (63/103 falls) occurring in the two months after discharge from rehabilitation. One subject had 37 similar falls and these falls were excluded from further analysis. Falls occurred more often indoors (50/66), during the day (46/66) and towards the paretic side (25/66). People required assistance to get up after 25 falls (38%) and 36 falls (55%) resulted in an injury. People sought professional health care after only 16 falls, and activity was restricted after 29 falls (44%). The Berg Balance Scale and Functional Independence Measure scores were lower in people who had longer lies after a fall, and who restricted their activity after a fall (p < 0.05). Lower physical function scores were also associated with falling in the morning, wearing multifocal glasses at the time of a fall, and injurious falls (p < 0.05). CONCLUSION: Falls are common when people return home after stroke. Of concern are the small number seeking health professionals' assistance after a fall, the high proportion restricting their activity as a result of a fall and the number of falls occurring towards the paretic side.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".