Association of surgeon volume with complications following direct anterior approach (DAA) total hip arthroplasty: a population-based study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Total hip arthroplasty (THA) can be performed through various surgical approaches, including direct anterior (DAA). DAA-THA may offer faster recovery but carries a higher risk of complications, which may be mitigated by surgeon volume and experience. We examined the association of surgeons' annual surgical volume with major complications after DAA-THA in a population-based sample. METHODS: A population-based retrospective cohort study was carried out on primary DAA-THA patients in Ontario between April 2016 and March 2021. We used restricted cubic splines to visually define the association between annual DAA surgeon volume and the risk of major surgical complications (fractures, dislocations, infections, and revisions) within 1 year of surgery. We further compared the complication rates amongst different DAA volume categories (< 30, 30-60, and > 60 cases/year). RESULTS: The study encompassed 9,672 DAA-THA patients (52% female, median age 67 years). We showed a sharp decline in the probability of complications as the surgical volume of DAA-THA increased within the lower range of 0-30 cases/year; the probability slightly increased after the surgical volume exceeded 60 cases/year. The overall complication rates were 3.09%, 2.24%, and 2.18% for the surgical experience group of < 30 cases/year, 30-60 cases/year, and > 60 cases/year, respectively. CONCLUSION: There was an inverse relationship between surgical volume and complication rates in DAA-THA within the lower volume ranges. Maintaining a surgical volume of at least 30 DAA-THA cases/year can minimize complications, emphasizing the importance of surgical volume in this approach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".