Trends and predictors of cemented fixation in arthroplasty for patients with a hip fracture: a Canadian Joint Replacement Registry study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Cemented fixation is widely recommended during arthroplasty for hip fractures, yet it has not been universally adopted by all surgeons and hospitals. We aimed to identify which factors were associated with a higher likelihood of cemented fixation. METHODS: We identified patients ≥ 55 years old with hip fractures treated with primary arthroplasty in Canada between 2012 and 2022. We determined fixation method along with several surgeon and hospital characteristics from the Canadian Joint Replacement Registry and other Canadian databases. We used logistic regression to estimate the odds ratios (ORs) of the association between these covariates and cemented fixation. RESULTS: We identified 65,823 patients who underwent arthroplasty for hip fractures. The proportion of cases with cemented fixation for hemiarthroplasty increased by 30 percentage points over the study period; the proportion for total hip arthroplasty (THA) remained relatively stable. High-volume hospitals (≥ 500 annual hip arthroplasties with ≥ 25% of these for fractures) were least likely to cement, OR = 0.30; 95% confidence interval (CI) 0.27-0.34 vs low-volume hospitals (< 500 cases/< 25% for fractures). High volume surgeons (≥ 50 hips/year, ≥ 16/year for fractures) had an OR of 0.80 (CI 0.75-0.84) compared with < 50 hips/year surgeons. Teaching hospitals were more likely to cement, OR = 1.16 (CI 1.10-1.22). The OR of cemented fixation for hemiarthroplasty (vs THA) rose from 1.13 (CI 0.99-1.29) at the start of the study period to 2.17 (CI 2.02-2.33) at the end. CONCLUSION: The use of cemented fixation in hip fracture arthroplasty has increased across Canada over the last decade. However, surgeons and hospitals that treat more hip fracture patients are less likely to cement. The proportion of cemented fixation increases with patient age. Cement use is more common in hemiarthroplasty than in THA.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".