Complications following hip arthroscopy: a retrospective review of the McMaster experience (2009–2012)
Bibliographic record
Abstract
BACKGROUND: The use of hip arthroscopy has been steadily rising as technology, experience and surgical education continue to advance. Previous reports of the complication rate associated with hip arthroscopy have varied. The purpose of this study was to report our experience with hip arthroscopy complications at a single Canadian institution (McMaster University). METHODS: We performed a retrospective chart review of 2 hip arthroscopists at the same institution to identify patients who had undergone the index surgery and had been followed for a minimum of 6 months postoperatively. We used a standard data entry form to collect information on patient demographic and clinical characteristics, including age, sex, surgical indication and type of complication if any. RESULTS: A total of 211 patients underwent 236 hip arthroscopies. The mean age at time of surgery was 37 ± 13 years and mean follow-up was 394 ± 216.5 days. The overall complication rate associated with hip arthroscopy was 4.2% (95% confidence interval 2.3%-7.6%). We identified 4 major and 6 minor complications. CONCLUSION: Overall, hip arthroscopy appears to be safe, with minor complications occurring more frequently than major ones. However, surgeons should recognize the possibility of serious complications associated with this procedure. Future research should focus on prospective designs looking for potential prognostic factors associated with hip arthroscopy complications.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".