Predicting factors of contralateral hip fractures among patients above 55 years of age
Bibliographic record
Abstract
Background. The incidence of osteoporotic fractures increases by 1-3% per year of age. Nine to twelve percent of patients that have suffered a primary hip fracture will have a fracture of the contralateral hip within 5 years. Our objective is to identify predictive factors of contralateral hip fractures among men and women over 55 years of age. Methods. A case control study with matched pairs was conducted, through a retrospective chart review of patients admitted for hip fractures at the Jewish General Hospital (JGH) and the Montreal General Hospital (MGH) between 1992 and 2004. Results. Contralateral hip fractures were most strongly associated with the use of mobility aid (OR= 5.69, CI 95% (3.20-10.14)). No other risk factors could be identified as predictors, probably due to missing data. Conclusion. This study confirms the use of mobility aid as a predictor of contralateral hip fractures. Future prospective risk studies may further optimize the diagnostic accuracy for predicting contralateral hip fractures.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".