Total hip arthroplasty using a combined anterior and posterior approach via a lateral incision in patients with ankylosed hips
Bibliographic record
Abstract
BACKGROUND: For most patients with severely ankylosed hips, traditional surgical approaches do not provide sufficient exposure during THAs. We report our experience with a combined anterior and posterior approach using a lateral incision for total hip arthroplasty (THA) in patients with severe, spontaneous bony hip ankylosis. METHODS: Between January 2004 and December 2008, patients with severe, spontaneous bony hip ankylosis underwent THA via a combined anterior and posterior approach using a lateral incision. RESULTS: We included 47 patients (76 hips) with a mean age of 53 (range 22-72) years in our study. All surgeries were successful, and no significant postoperative complications occurred. The mean operative duration was 1.5 (range 1.3-1.7) hours, and mean blood loss was 490 (range 450-580) mL. The mean duration of follow-up was 5.5 (range 2-11) years. Harris hip score improved from 53 to 88 points postoperatively, and the outcome was good to excellent in 88.37% of cases. Heterotopic ossification occurred in 6 hips, and infection, which resolved with antibiotics, occurred in 1 patient. CONCLUSION: This combined anterior and posterior approach to THA using a lateral incision in patients with severe, spontaneous ankylosis provides very good exposure, protects the abduction unit and results in good to excellent postoperative recovery.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".