The role of cognitive impairment in fall risk among older adults: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: cognitive impairment is an established fall risk factor; however, it is unclear whether a disease-specific diagnosis (i.e. dementia), measures of global cognition or impairments in specific cognitive domains (i.e. executive function) have the greatest association with fall risk. Our objective was to evaluate the epidemiological evidence linking cognitive impairment and fall risk. METHODS: studies were identified through systematic searches of the electronic databases of MEDLINE, EMBASE, PyschINFO (1988-2009). Bibliographies of retrieved articles were also searched. A fixed-effects meta-analysis was performed using an inverse-variance method. RESULTS: twenty-seven studies met the inclusion criteria. Impairment on global measures of cognition was associated with any fall, serious injuries (summary estimate of OR = 2.13 (1.56, 2.90)) and distal radius fractures in community-dwelling older adults. Executive function impairment, even subtle deficits in healthy community-dwelling older adults, was associated with an increased risk for any fall (summary estimate of OR = 1.44 (1.20, 1.73)) and falls with serious injury. A diagnosis of dementia, without specification of dementia subtype or disease severity, was associated with risk for any fall but not serious fall injury in institution-dwelling older adults. CONCLUSION: the method used to define cognitive impairment and the type of fall outcome are both important when quantifying risk. There is strong evidence global measures of cognition are associated with serious fall-related injury, though there is no consensus on threshold values. Executive function was also associated with increased risk, which supports its inclusion in fall risk assessment especially when global measures are within normal limits.
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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 | 0.015 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.038 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".