EFFECT OF A HOME-BASED EXERCISE PROGRAM ON SUBSEQUENT FALLS IN OLDER ADULTS WITH COGNITIVE FRAILTY
Bibliographic record
Abstract
Abstract Cognitive frailty is characterized by concurrent physical frailty and mild cognitive impairment. and increases the risk for falls. Whether exercise can reduce falls in older adults with cognitive frailty is unknown. We examined the effects of a home-based exercise intervention on subsequent falls among community-dwelling older adults with cognitive frailty and a history of falls. A secondary of a 12-month randomized controlled trial among older adults aged ≥70 years with a fall in the last 12 months. Participants were randomized to either 12 months of home-based exercise (EX; n=172) or usual care (UC; n=172). For this analysis, we only included participants who were classified as cognitively frail based on a Short Physical Performance Battery (SPPB) score ≤ 9/12 and a Montreal Cognitive Assessment score < 26/30. Our primary analysis examined the effect of EX on self-reported falls over 12 months. The secondary analysis examined whether higher exercise adherence, or dose, benefits physical frailty among the EX participants. At baseline, 192 participants were classified as cognitively frail (EX=93; UC=99). Falls rates were lower in EX participants vs. UC participants (IRR=0.65; p=0.042). At 12 months, in the EX group, SPPB score was significantly higher among participants with high adherence vs. those with low adherence (estimated mean difference: 1.22; p=0.004). Exercise is a promising strategy for reducing subsequent falls in older adults with cognitive frailty and a history of falls. Greater exercise adherence, or dose, may reduce physical frailty in this population at high risk for disability.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".