Mid-to long-term results of revision total hip replacement in patients aged 50 years or younger
Bibliographic record
Abstract
Revision total hip replacement (THR) for young patients is challenging because of technical complexity and the potential need for subsequent further revisions. We have assessed the survivorship, functional outcome and complications of this procedure in patients aged < 50 years through a large longitudinal series with consistent treatment algorithms. Of 132 consecutive patients (181 hips) who underwent revision THR, 102 patients (151 hips) with a mean age of 43 years (22 to 50) were reviewed at a mean follow-up of 11 years (2 to 26) post-operatively. We attempted to restore bone stock with allograft where indicated. Using further revision for any reason as an end point, the survival of the acetabular component was 71% (sd 4) and 54% (sd 7) at ten- and 20 years. The survival of the femoral component was 80% (sd 4) and 62% (sd 6) at ten- and 20 years. Complications included 11 dislocations (6.1%), ten periprosthetic fractures (5.5%), two deep infections (1.1%), four sciatic nerve palsies (2.2%; three resolved without intervention, one improved after exploration and freeing from adhesions) and one vascular injury (0.6%). The mean modified Harris Hip Score was 41 (10 to 82) pre-operatively, 77 (39 to 93) one year post-operatively and 77 (38 to 93) at the latest review. This overall perspective on the mid- to long-term results is valuable when advising young patients on the prospects of revision surgery at the time of primary replacement.
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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 | 0.000 |
| 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".