Gait parameters and characteristics associated with increased risk of falls in people with dementia: a systematic review
Bibliographic record
Abstract
BACKGROUND: People with dementia fall twice as often and have more serious fall-related injuries than healthy older adults. While gait impairment as a generic term is understood as a fall risk factor in this population, a clear elaboration of the specific components of gait that are associated with falls risk is needed for knowledge translation to clinical practice and the development of fall prevention strategies for people with dementia. OBJECTIVE: To review gait parameters and characteristics associated with falls in people with dementia. METHODS: Electronic databases CINAHL, EMBASE, MedLine, PsycINFO, and PubMed were searched (from inception to April 2017) to identify prospective cohort studies evaluating the association between gait and falls in people with dementia. RESULTS: Increased double support time variability, use of mobility aids, walking outdoors, higher scores on the Unified Parkinson's Disease Rating Scale, and lower average walking bouts were associated with elevated risk of any fall. Increased double support time and step length variability were associated with recurrent falls. The reviewed articles do not support using the Performance Oriented Mobility Assessment and the Timed Up-and-Go tests to predict any fall in this population. There is limited research on the use of dual-task gait assessments for predicting falls in people with dementia. CONCLUSION: This systematic review shows the specific spatiotemporal gait parameters and features that are associated with falls in people with dementia. Future research is recommended to focus on developing specialized treatment methods for these specific gait impairments in this patient population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".