The role of cognitive impairment in fall risk among older adults: a systematic review and meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 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 | 0.000 | 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 it