MétaCan
Menu
Back to cohort
Record W2884707242 · doi:10.1159/000490850

Quantitative Mobility Assessment for Fall Risk Prediction in Dementia: A Systematic Review

2018· review· en· W2884707242 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDementia and Geriatric Cognitive Disorders · 2018
Typereview
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsUniversity of TorontoToronto Rehabilitation InstituteUniversity Health Network
Fundersnot available
KeywordsDementiaGaitBalance (ability)Physical medicine and rehabilitationPoison controlInjury preventionFall preventionPsychologyHuman factors and ergonomicsMedicineDiseaseMedical emergency

Abstract

fetched live from OpenAlex

BACKGROUND: Impairments of gait and balance often progress through the course of dementia, and are associated with increased risk of falls. SUMMARY: This systematic review provides a critical analysis of the evidence linking quantitative measures of gait and balance to fall risk in older adults with dementia. Various instrumented measures of gait and postural stability including gait speed and non-instrumented performance measures including Timed Up and Go were shown to be capable of distinguishing fallers from non-fallers. Key Messages: Existing reviews indicate that impairments of gait and balance are associated with increased risk of falls in cognitively intact older people. There are inconsistencies, however, regarding the characteristics most predictive of a fall. In order to advance fall prevention efforts, there is an important need to understand the relationship between gait, balance, and fall risk, particularly in high-risk populations such as individuals with dementia.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.119
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.036
GPT teacher head0.417
Teacher spread0.381 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it