Hip Arthroscopy in Trauma: A Systematic Review of Indications, Efficacy, and Complications
Bibliographic record
Abstract
PURPOSE: This systematic review explored the indications, efficacy, and complications of hip arthroscopy in the setting of trauma. METHODS: Databases (PubMed, Medline, Embase, and Web of Science) were searched from database inception to March 2015 for studies using hip arthroscopy in trauma treatment. Systematic screening of eligible studies was undertaken in duplicate. The inclusion criteria included studies pertaining to arthroscopic intervention of all traumatic hip injuries. Abstracted data were organized in table format with descriptive statistics presented. RESULTS: From an initial search yield of 2,809 studies, 32 studies (25 case reports and 7 case series) satisfied the criteria for inclusion. A total of 144 patients (age range, 10 to 53 years) underwent hip arthroscopy for 6 indications associated with trauma: 8 patients for bullet extraction, 6 for femoral head fixation, 82 for loose body removal, 6 for acetabular fracture fixation, 20 for labral intervention, and 23 for ligamentum teres debridement. Patients were followed up postoperatively for a mean of 2.9 years (range, 8 days to 16 years). Successful surgery was achieved in 96% of patients. The rate of major complications (i.e., pulmonary embolism and abdominal compartment syndrome) was 1.4% (2 of 144); avascular necrosis, 1.4% (2 of 144); and nerve palsy, 0.7% (1 of 144). CONCLUSIONS: Hip arthroscopy appears effective and safe in the setting of trauma. These data should be interpreted with caution because of the low-quality evidence of the included studies. Surgeons should be aware of the potential complications such as abdominal compartment syndrome and thromboembolic events when performing hip arthroscopy in the setting of trauma. LEVEL OF EVIDENCE: Level IV, systematic review of Level IV studies.
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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 | 0.008 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".