Hip arthroscopy for the intra-articular sequelae after Thompson-Epstein type I-II traumatic hip dislocation: A 2-year minimal follow-up
Bibliographic record
Abstract
Background: Traumatic hip dislocation is a usually high-energy injury and often leads to serious intra-articular pathologies. Hip arthroscopy is an increasingly popular minimally invasive procedure for intra-articular conditions. Purpose: This study was designed to review the arthroscopic diagnosis and treatment for mechanic hip symptoms after traumatic hip dislocation and evaluate clinical outcomes. Methods: Seven consecutive patients treated with arthroscopy for mechanical hip symptoms after traumatic hip dislocation between 2005 and 2014 were enrolled in the study. We use Tonnis classification for evaluation of hip osteoarthritis by preoperative and the last follow-up plain radiography. Visual analogue scale (VAS), modified Harris Hip Score (mHHS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and 12-item short-form (SF-12) were obtained for clinical outcome assessment. All patients were followed up for a minimum of 2 years. Results: The average age of the patients when undergoing hip arthroscopy was 32.7 years. The interval from injury to arthroscopy ranged from 3 days to 2 years, with a mean of 353 days. The mean operative time was 165 mins. Loose bodies were found in 6 patients. Four patients had labral tears, five had ligamentum teres lesions and six had chondral injuries at the femoral head or acetabulum. All preoperative clinical functional scores improved at last follow-up. The mean length of postoperative hospital stay was 2.6 days. No patients had surgery-related complication. Conclusion: Hip arthroscopy is a powerful tool to detect loose bodies or intra-articular fragments after traumatic hip dislocation and provides good-to-excellent clinical outcomes. For patients with mechanic hip symptoms after traumatic hip dislocation, early referral for hip arthroscopy surgeon is recommended.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".