Analysis of the relationship between surgeon procedure volume and complications after total knee arthroplasty using a propensity-matched cohort study
Bibliographic record
Abstract
OBJECTIVES: This study aimed to identify a threshold in annual surgeon volume associated with increased risk of revision (for any cause) and deep infection requiring surgery following primary elective total knee arthroplasty (TKA). DESIGN: A propensity score matched cohort study. SETTING: Ontario, Canada. PARTICIPANTS: 169 713 persons who received a primary TKA between 2002 and 2016, with 3-year postoperative follow-up. MAIN OUTCOME MEASURES: Revision arthroplasty (for any cause), and the occurrence of deep surgical infection requiring surgery. RESULTS: Based on restricted cubic spline analysis, the threshold for increased probability of revision and deep infection requiring surgery was <70 cases/year. After matching of 51 658 TKA recipients from surgeons performing <70 cases/year to TKA recipients from surgeons with greater than 70 cases/year, patients in the former group had a higher rate of revision (for any cause, 2.23% (95% Confidence Interval (CI) 1.39 to 3.07) vs 1.70% (95% CI 0.85 to 2.55); Hazard Ratio (HR) 1.33, 95% CI 1.21 to 1.47, p<0.0001) and deep infection requiring surgery (1.29% (95% CI 0.44 to 2.14) vs 1.09% (95% CI 0.24 to 1.94); HR 1.33, 95% CI 1.17 to 1.51, p<0.0001). CONCLUSIONS: For primary TKA recipients, cases performed by surgeons who had performed fewer than 70 TKAs in the year prior to the index TKA were at 31% increased relative risk of revision (for any cause), and 18% increased relative risk for deep surgical infection requiring surgery, at 3-year follow-up.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| 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".