MID-TERM REVISION RISK OF PRIMARY MODULAR TOTAL HIP REPLACEMENT STEM FINDINGS FROM THE CANADIAN JOINT REPLACEMENT REGISTRY
Bibliographic record
Abstract
Modular total hip arthroplasty (MTHA) stems were introduced in order to provide increased intra-operative flexibility for restoring hip biomechanics, improving stability and potentially reducing revision risk. However, the additional interface at the neck-body junction provides another location for corrosion or mechanical failure of the stem. To delineate the mid term revision risk of MTHA stems, we examined data from the Canadian Joint Replacement Registry (CJRR) at the Canadian Institute for Health Information (CIHI). Kinectiv, Profemur and Rejuvenate modular stems were identified from CJRR records submitted between 2004 and 2014. Revision status was determined by examining the discharge abstract database (DAD) also housed by CIHI, which collects information on all revisions, regardless of whether the procedure was submitted to CJRR. A total of 2446 modular stems were identified with a mean follow up of 4.2 years (range 0 to 10). Their usage peaked in 2012 (the first year of mandatory CJRR form submission for BC, ON and MB), and dropped rapidly thereafter. A total of 155 (6.3%) were revised. This consisted of 5/301 Kinectiv (1.7%), 141/2050 ProFemur (6.9%), and 9/96 Rejuvenate (9.4%) stems. As a group, this falls below the National Institute for Clinical Excellence (NICE) guidelines of 95% survival at 10 years. While MTHA stems were introduced to improve outcomes and reduce revision risk, our findings of a 6.3% revision risk at a mean follow up of 4.2 years does not appear to support this.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".