Simplified System for Absolute Fracture Risk Assessment: Clinical Validation in Canadian Women
Bibliographic record
Abstract
Absolute 10-yr fracture risk based on multiple factors is the preferred method for risk assessment. A simplified risk assessment system from sex, age, DXA, and two clinical risk factors (CRFs)--prior fracture and systemic corticosteroid (CS) use--has been used in Canada since 2005. This study was undertaken to evaluate this system in the Canadian female population. A total of 16,205 women > or =50 yr of age at the time of baseline BMD (1998-2002) were identified in a database containing all clinical DXA test results for the Province of Manitoba, Canada. Basal 10-yr fracture risk from age and minimum T-score (lumbar spine, femur neck, trochanter, total hip) was categorized as low (<10%), moderate (10-20%), or high (>20%). Health service records since 1987 were assessed for prior fracture codes (N = 5224), recent major CS use (N = 616), and fracture codes after BMD testing (mean, 3.1 yr of follow-up) for the hip, vertebrae, forearm, or humerus (designated osteoporotic, N = 757). Fracture risk predicted from age and minimum T-score alone showed a significant gradient in observed fracture rates (low 5.1 [95% CI, 4.1-6.4], moderate 11.5 [95% CI, 10.1-13.0], high 25.4 [95% CI, 23.2-27.9] per 1000 person-years; p-for-trend <0.0001). There was an incremental increase in incident fracture rates from a prior fracture (13.9 [95% CI, 11.3-16.4] per 1000 person-years) or major CS use (11.2 [95% CI, 4.1-18.2] per 1000 person-years). This simplified fracture risk assessment system provides an assessment of fracture risk that is consistent with observed fracture rates.
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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 | 0.015 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".