Mid-term to long-term outcome and risk factors for failure of 158 hips with two-stage revision for periprosthetic hip joint infection
Bibliographic record
Abstract
Introduction : This study aimed to evaluate infection-free survival and outcomes after two-stage revision surgery for hip periprosthetic joint infection (PJI) performed in a specialised arthroplasty unit over 20 years. Methods : We retrospectively identified 158 hips (154 patients) treated with two-stage revision surgery for hip PJI between 2001 and 2021. We analysed their data and presented their infection-free survival, re-operation rate, mortality, risk factors and complications. Results : The mean follow-up time was 9 (2 to 21.7) years. A total of 22 hips (13.9 %) were re-infected. The infection-free survival was 94.4 % at 2 years, 89.3 % at 5 years, 84.2 % at 10 years, and 82.6 % at 15 and 20 years. The re-operation rate for aseptic causes was 12 %, and the most common cause of re-operation was dislocation (7 %). The cumulative survival for re-operation for aseptic causes was 93.6 % at 2 years, 89.7 % at 5 years, 88.8 % at 10 years, and 82.8 % at 15 and 20 years. The cumulative survival for all-cause re-revision was 88.8 % at 2 years, 80.8 % at 5 years, 74.9 % at 10 years, and 68 % at 15 and 20 years. The mean Western Ontario and McMaster Universities Arthritis Index (WOMAC) hip score significantly improved from 68.3 at the pre-operative stage to 35.9 at 2.1 (2 to 3.3) years, 35.3 at 5.3 (5 to 8.4) years, 38.3 at 11.3 (10–15) years and 43.8 at 18.7 (16.5 to 21.7) years ( p <0.01). Duration of antibiotics and gram-negative infection were the only predictive risk factors for re-infection. Conclusion : Our results of the two-stage revision protocol for hip PJI were satisfactory and comparable with the best reported outcomes.
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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 | 0.000 |
| 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".