Vertebral Fracture Status and the World Health Organization Risk Factors for Predicting Osteoporotic Fracture Risk
Bibliographic record
Abstract
Vertebral fractures are the most common osteoporotic fracture, and patients with prevalent vertebral fractures have a greater risk of future fractures. However, radiographically determined vertebral fractures are not identified as a distinct risk factor in the World Health Organization (WHO) fracture risk assessment tool. The objective of this study was to evaluate and compare potential risk factors including morphometric spine fracture status and the WHO risk factors for predicting 5-yr fracture risk. We hypothesized that spine fracture status provides prognostic information in addition to consideration of the WHO risk factors alone. A randomly selected, population-based community cohort of 2761 noninstitutionalized men and women > or =50 yr of age living within 50 km of one of nine regional centers was enrolled in the Canadian Multicentre Osteoporosis Study (CaMOS), a prospective and longitudinal cohort study following subjects for 5 yr. Prevalent and incident spine fractures were identified from lateral spine radiographs. Incident nonvertebral fragility fractures were determined by an annual, mailed fracture questionnaire with validation, and nonvertebral fragility fracture was defined by investigators as a fracture with minimal trauma. A model considering the WHO risk factors plus spine fracture status provided greater prognostic information regarding future fracture risk than a model considering the WHO risk factors alone. In univariate analyses, age, BMD, and spine fracture status had the highest gradient of risk. A model considering these three risk factors captured almost all of the predictive information provided by a model considering spine fracture status plus the WHO risk factors and provided greater predictive information than a model considering the WHO risk factors alone. The use of spine fracture status along with age and BMD predicted future fracture risk with greater simplicity and higher prognostic accuracy than consideration of the risk factors included in the WHO tool.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".