Important risk factors and attributable risk of vertebral fractures in the population-based Tromsø study
Bibliographic record
Abstract
BACKGROUND: Vertebral fractures, the most common type of osteoporotic fractures, are associated with increased risk of subsequent fracture, morbidity, and mortality. The aim of this study was to examine the contribution of important risk factors to the variability in vertebral fracture risk. METHODS: Vertebral fracture was ascertained by VFA method (DXA, GE Lunar Prodigy) in 2887 men and women, aged between 38 and 87 years, in the population-based Tromsø Study 2007/2008. Bone mineral density (BMD; g/cm2) at the hip was measured by DXA. Lifestyle information was collected by questionnaires. Multivariable logistic regression model, with anthropometric and lifestyle factors included, was used to assess the association between each or combined risk factors and vertebral fracture risk. Population attributable risk was estimated for combined risk factors in the final multivariable model. RESULTS: In both sexes, age (odds ratio [OR] per 5 year increase: 1.32; 95% CI 1.19-1.45 in women and 1.21; 95% CI 1.10-1.33 in men) and BMD (OR per SD decrease: 1.60; 95% CI 1.34-1.90 in women and1.40; 95% CI 1.18-1.67 in men) were independent risk factors for vertebral fracture. At BMD levels higher than 0.85 g/cm2, men had a greater risk of fracture than women (OR 1.52; 95% CI 1.14-2.04), after adjusting for age. In women and men, respectively, approximately 46% and 33% of vertebral fracture risk was attributable to advancing age (more than 70 years) and low BMD (less than 0.85 g/cm2), with the latter having a greater effect than the former. CONCLUSIONS: These data confirm that age and BMD are major risk factors for vertebral fracture risk. However, in both sexes the two factors accounted for less than half of fracture risk. The identification of individuals with vertebral fracture is still a challenge.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".