Cluster analysis to identify the profiles of individuals with compromised bone health versus unfortunate wrist fractures within the Canadian Longitudinal Study of Aging (CLSA) database
Bibliographic record
Abstract
We used cluster analysis to determine the profiles of individuals who sustained wrist fractures. We found two groups: (1) young and active and (2) older and less active. This information may be used to identify individuals who require further bone health interventions to optimize healthy aging. INTRODUCTION: Distal radial fractures (DRF) are the most common of all fractures, with 6% of males and 33% of females having one at some point in their lifetime. We hypothesize that DRF consists of two subpopulations: one with compromised bone health that is early in the osteoporosis (OP) trajectory and another which are active and healthy and suffer a misfortune fracture due to their high activity levels or risk-taking behaviors. The latter is likely to recover with a minimal disability, while the former may signal a negative health trajectory of disability and early mortality. OBJECTIVE: To determine the profiles of individuals who sustained wrist fractures using cluster analysis within the Comprehensive Cohort of the Canadian Longitudinal Study on Aging (CLSA) database considering factors that reflect bone health and activity levels. METHODS: We included all the individuals who had a wrist fracture within the CLSA comprehensive cohort of the database (n = 968). The baseline data was used for this analysis. A 2-step cluster analysis was used to identify profiles that were both statistically and clinically meaningful. Variables that were used in the cluster analysis include demographic variables, physical activity status indicators, general health indicators, mobility indicators, bone health indicators, comorbid conditions, and lifestyle factors. RESULTS: We were able to identify two distinct profiles that were statistically and clinically meaningful confirming our hypothesis. One cluster included a predominantly younger cohort, who are physically active, with less comorbid conditions, better bone health, and better general health, while the opposite was true of the first cohort. CONCLUSION: We were able to identify two clusters-a healthy profile and a bone health compromised profile. This information may be used to identify the subgroup of people who should be targeted in the future for more intensive preventive health services to optimize healthy aging.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".