Total Hip Arthroplasty for Acute Displaced Femoral Neck Fractures via the Posterior Approach: A Protocol to Minimise Hip Dislocation Risk
Bibliographic record
Abstract
Total hip arthroplasty (THA) is considered superior to hip hemiarthroplasty (HHA) in long term pain relief and functional outcome after femoral neck fracture; high early dislocation rates may however negate these advantages. This study elucidates whether a protocol of careful patient selection, surgical technique algorithm and use of modern implants could yield low dislocation rates in hip fracture patients treated with THA via the posterior approach. Over a seven year period all patients admitted to our institution that were cognitively lucid, independent ambulators and without Parkinson's disease underwent THA for acute displaced femoral neck fractures using a posterior approach, large femoral heads, elevated acetabular liners and a surgical technique algorithm. Twenty-nine THAs were performed in 26 patients (mean age of 71 years, range 50-87 years) and were followed for a mean of 32 months (range 13-48 months). There was one dislocation 7 weeks postoperatively in a non-compliant patient resulting in reoperation. There were no other reoperations or major complications. Our results indicate that low dislocation rates can be accomplished for displaced femoral neck fractures treated with THA via the posterior approach using a protocol that includes careful patient selection, surgical technique focused on intraoperative stability, and the use of modern implants.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".