Printed In U SA. Rates of Transcervical and Pertrochanteric Hip Fractures in the Province of
Bibliographic record
Abstract
Two distinct subtypes of hip fracture, transcervical and pertrochanteric, can be distinguished on the basis of the anatomical location of the injury. While the epidemiology of hip fractures has been well described, typically, little or no distinction is made between these subtypes. The objective of this study was to compare and contrast age- and sex-specific rates of transcervical and pertrochantenc fractures in Quebec, Canada. The data for this study were obtained from a database containing records of all persons discharged from all hospitals in Quebec from 1981 to 1992. Rates of hip fracture were calculated by using the population aged 50 years and older as the denominator, and changes in rates over time were assessed using Poisson regression. There were no statistically significant trends in the changes in rates over time (i e., 95 percent confidence intervals overlapped the null value). Among women below age 70 years, transcervical fractures were more common, whereas among older women, pertrochantenc fractures predominated. Among men, pertrochanteric fractures predominated at all ages. There was a marked seasonal vanation in the occurrence of all hip fractures combined: Compared with the summer months, the relative nsk of all hip fractures dunng the winter was 1.32 (95 percent confidence interval 1.28-1.36). The results of this study indicate that the two subtypes of hip fracture, transcervical and pertrochanteric, have different patterns of occurrence, suggesting different nsk factor profiles. Clearly, a multidisciplinary research approach is needed before it will be possible to untangle
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.030 | 0.005 |
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".