Bibliographic record
Abstract
CONTEXT: Hip fractures are a public health concern because they are associated with significant morbidity, excess mortality, and the majority of the costs directly attributable to osteoporosis. OBJECTIVE: To examine trends in hip fracture rates in Canada. DESIGN, SETTING, AND PATIENTS: Ecologic trend study using nationwide hospitalization data for 1985 to 2005 from a database at the Canadian Institute for Health Information. Data for all patients with a hospitalization for which the primary reason was a hip fracture (570,872 hospitalizations) were analyzed. MAIN OUTCOME MEASURES: Age-specific and age-standardized hip fracture rates. RESULTS: There was a decrease in age-specific hip fracture rates (all P for trend <.001). Over the 21-year period of the study, age-adjusted hip fracture rates decreased by 31.8% in females (from 118.6 to 80.9 fractures per 100,000 person-years) and by 25.0% in males (from 68.2 to 51.1 fractures per 100,000 person-years). Joinpoint regression analysis identified a change in the linear slope around 1996. For the overall population, the average age-adjusted annual percentage decrease in hip fracture rates was 1.2% (95% confidence interval, 1.0%-1.3%) per year from 1985 to 1996 and 2.4% (95% confidence interval, 2.1%-2.6%) per year from 1996 to 2005 (P < .001 for difference in slopes). Similar changes were seen in both females and males with greater slope reductions after 1996 (P < .001 for difference in slopes for each sex). CONCLUSIONS: Age-standardized rates of hip fracture have steadily declined in Canada since 1985 and more rapidly during the later study period. The factors primarily responsible for the earlier reduction in hip fractures are unknown.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".