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Record W2055147124 · doi:10.1155/2013/935924

Risk Factors for Falls and Fragility Fractures in Community-Dwelling Seniors: A One-Year Prospective Study

2013· article· en· W2055147124 on OpenAlexafffund
Sacha Song, Joy C. MacDermid, Ruby Grewal

Bibliographic record

VenueISRN Rehabilitation · 2013
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsMcMaster UniversitySt Joseph's Health CareUniversity of WindsorWestern University
FundersCanadian Institutes of Health Research
KeywordsFear of fallingFRAXMedicineFalling (accident)Balance (ability)OsteoporosisFall preventionPoison controlBerg Balance ScalePhysical therapyFalls in older adultsGerontologyInjury preventionBone mineralDemographyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Objective . To evaluate risk factors for falls and fragility fractures in healthy seniors. Methods . Assessing 50 ambulatory community-dwelling volunteers ≥65 for demographics, BMI, bone mineral density (BMD) (DEXA), fracture risk (FRAX), balance (Biodex), fear of falling (Modified Falls Efficacy Scale (MFES)), and activity level (RAPA). One-year followup was done through phone interviews. Results . Most participants (17 males, 33 females; mean age 72.0 ± 5.5 years) had normal BMD and were active with little to no fear of falling. Balance did not correlate with FRAX or fear of falling. Activity level did not correlate with FRAX, but the active group had less fear of falling. Most scored below age specific norms on balance testing. Fear of falling was not significantly different between genders but did correlate with FRAX, indicating that patients with higher fracture risk were also more afraid of falling. Individuals who fell after one year had increased fear of falling and decreased activity levels. Conclusions . Community-dwelling seniors with higher risk of future fractures were more afraid of falling. Although healthy and active, this cohort had poor balance compared to age matched norms. Further research on how to best assess fall risk and improve balance to prevent fractures is needed.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.023
GPT teacher head0.368
Teacher spread0.345 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2013
Admission routes2
Has abstractyes

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