Capsular closure outweighs head size in preventing dislocation following revision total hip arthroplasty
Bibliographic record
Abstract
Introduction: The high dislocation rate following revision total hip arthroplasty (THA) has been shown to be significantly reduced by closing the posterior capsule and by the use of large diameter femoral heads. The relative importance of each of these strategies on the rate of dislocation remains unknown. We undertook a study to determine if increasing femoral head diameter, in addition to posterior capsular closure would influence the dislocation rate following revision THA. Methods: We retrospectively reviewed 144 patients who underwent a revision THA. We included all patients who underwent revision THA with closure of the posterior capsule and who had at least a 2-year minimum follow-up. 48 patients had a 28-mm femoral head, 47 had a 32-mm head and 49 patients had a 36-mm femoral head. Results: At a minimum follow-up of 2 years, there were 3 dislocations. There were no dislocations in the 28-mm group (0%), 2 in the 32-mm group (4%) and 1 in the 36-mm group (2%). Head size alone was not found to significantly decrease the risk of dislocation (28-mm versus 32-mm p = 0.12; 28-mm versus 36-mm p = 0.27; 32-mm versus 36-mm p = 0.40). Conclusion: Both large diameter heads and careful attention to surgical technique with posterior capsular closure can decrease the historically high dislocation rate after revision THA when utilising the posterolateral approach. Capsular closure outweighs the effect of femoral head diameter in preventing dislocation following revision THA through a posterolateral approach.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".