Estimating osteoporotic fracture risk following a wrist fracture: a tale of two systems
Bibliographic record
Abstract
UNLABELLED: The WHO fracture risk assessment (FRAX) and Canadian Association of Radiologists and Osteoporosis Canada (CAROC) tools can both be used to determine an individual's 10-year risk of osteoporotic fracture. However, these tools differ in their risk calculation. For participants <65 years with a wrist fracture, FRAX provides a lower fracture risk estimate than CAROC resulting in fewer decisions to initiate therapy. PURPOSE: The purpose of the current report is to compare fracture risk prediction rates using the CAROC and the FRAX® tools. METHODS: Individuals ≥50 years with a distal radius fracture resulting from a fall from standing height or less were recruited from a single orthopedic clinic. Participants underwent a DXA scan of their lumbar spine and hip. Femoral neck (FN) bone mineral density (BMD) and fracture risk factors were used to determine each participant's 10-year fracture risk using both fracture risk assessment tools. Participants were categorized as low (<10 %), moderate (10-20 %), or high (>20 %) risk. Stratified by age (<65 years, >65 years), the proportion of participants in each category was compared between the tools. RESULTS: Analyses included 60 participants (mean age 65.7 ± 9.6 years). In those <65 years (n = 26), the proportion of individuals at low, moderate, and high risk differed between the FRAX and CAROC tools (p < 0.0001). FRAX categorized 69 % as low (CAROC 0 %) and 3 % as high (CAROC 12 %) risk. For individuals >65 years, almost all were at least at moderate risk (FRAX 79 %, CAROC 53 %), but fewer were at high risk using FRAX (18 vs. 47 %, p < 0.0003). CONCLUSION: For participants <65 years with a wrist fracture, FRAX provides a lower estimate of 10-year fracture risk than CAROC resulting in fewer decisions to initiate therapy. However, almost all participants >65 years were at moderate or high risk under both FRAX and CAROC and should at least be considered for pharmacotherapy.
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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 | 0.061 | 0.114 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.013 | 0.007 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".