Frailty and fracture, disability, and falls: a multiple country study from the global longitudinal study of osteoporosis in women.
Bibliographic record
Abstract
ObjectivesTo test whether women aged 55 and older with increasing evidence of a frailty phenotype would have greater risk of fractures, disability, and recurrent falls than women who were not frail, across geographic areas (Australia, Europe, and North America) and age groups.DesignMultinational, longitudinal, observational cohort study.SettingGlobal Longitudinal Study of Osteoporosis in Women (GLOW).ParticipantsWomen (N = 48,636) aged 55 and older enrolled at sites in Australia, Europe, and North America.MeasurementsComponents of frailty (slowness and weakness, poor endurance and exhaustion, physical activity, and unintentional weight loss) at baseline and report of fracture, disability, and recurrent falls at 1 year of follow-up were investigated. Women also reported health and demographic characteristics at baseline.ResultsWomen younger than 75 from the United States were more likely to be prefrail and frail than those from Australia, Canada, and Europe. The distribution of frailty was similar according to region for women aged 75 and older. Odds ratios from multivariable models for frailty versus nonfrailty were 1.23 (95% confidence interval (CI) = 1.07-1.42) for fracture, 2.29 (95% CI = 2.09-2.51) for disability, and 1.68 (95% CI = 1.54-1.83) for recurrent falls. The associations for prefrailty versus nonfrailty were weaker but still indicated statistically significantly greater risk of each outcome. Overall, associations between frailty and each outcome were similar across age and geographic region.ConclusionGreater evidence of a frailty phenotype is associated with greater risk of fracture, disability, and falls in women aged 55 and older in 10 countries, with similar patterns across age and geographic region.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".