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Record W4416723292 · doi:10.1186/s12877-025-06805-9

Functional continuum stratifies fall risk in older adults

2025· article· en· W4416723292 on OpenAlexaff
Xiaoxi Hu, Xiaoru Sun, Hui Zhang, Xiaofeng Wang, Xiaoyan Jiang

Bibliographic record

VenueBMC Geriatrics · 2025
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsInstitute of Aging
FundersShanghai Municipal Health Commission
KeywordsGaitConfidence intervalPreferred walking speedFall preventionStratification (seeds)Risk stratification

Abstract

fetched live from OpenAlex

OBJECTIVES: Gait speed is a validated indicator of fall risk (Grade 1 A). However, accurate prevention requires comprehensive stratification indicators. The Functional Continuum (FC), which encompasses the full range of functional changes, shows promise for stratifying fall risk. METHODS: The study included 4,949 and 5,259 individuals from the National Health and Aging Trends Study (NHATS) wave 1 as the discovery sample, and 2,649 and 2,749 newly recruited individuals from wave 5 as the independent validation sample for the gait speed and FC analyses, respectively. RESULTS: At baseline, 19.2% of participants exhibited low gait speed; over follow-up, 66.2% sustained an incident fall. In the FC cohort, baseline distributions for levels 0–3 were 35.0%, 24.9%, 21.0%, and 19.1%, respectively, with 67.7% sustaining an incident fall. Both gait speed and FC function effectively stratified fall risk, with FC showing a significant dose-effect on fall risk. After adjusting for confounders, older adults with low gait speed had an increased fall risk (hazard ratio [HR]: 1.50, 95% confidence interval [CI]: 1.31, 1.71). The worse the FC, the higher the fall risk (Level 1: HR: 1.20, 95% CI: 1.06, 1.36; Level 2: HR: 1.63, 95% CI: 1.43, 1.87; Level 3: HR: 1.80, 95% CI: 1.54, 2.09). CONCLUSIONS: FC stratified fall risk into low-, medium-, and high-risk levels, offering a comprehensive, tiered framework for guiding prevention—from general exercise and monitoring in low-risk individuals to intensive measures in higher-risk groups. These findings highlight the potential utility of FC for optimizing resource allocation in fall prevention strategies.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.019
GPT teacher head0.317
Teacher spread0.298 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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