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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".