Relation between surgeon volume and risk of complications after total hip arthroplasty: propensity score matched cohort study
Bibliographic record
Abstract
OBJECTIVES: To identify a cut point in annual surgeon volume associated with increased risk of complications after primary elective total hip arthroplasty and to quantify any risk identified. DESIGN: Propensity score matched cohort study. SETTING: Ontario, Canada. PARTICIPANTS: 37,881 people who received their first primary total hip arthroplasty during 2002-09 and were followed for at least two years after their surgery. MAIN OUTCOME MEASURE: The rates of various surgical complications within 90 days (venous thromboembolism, death) and within two years (infection, dislocation, periprosthetic fracture, revision) of surgery. RESULTS: Multivariate splines were developed to visualize the relation between surgeon volume and the risk for various complications. A threshold of 35 cases a year was identified, under which there was an increased risk of dislocation and revision. 6716 patients whose total hip arthroplasty was carried out by surgeons who had done ≤ 35 such procedure in the previous year were successfully matched to patients whose surgeon had carried out more than 35 procedures. Patients in the former group had higher rates of dislocation (1.9% v 1.3%, P=0.006; NNH 172) and revision (1.5% v 1.0%, P=0.03; NNH 204). CONCLUSIONS: In a cohort of first time recipients of total hip arthroplasty, patients whose operation was carried by surgeons who had performed 35 or fewer such procedures in the year before the index procedure were at increased risk for dislocation and early revision. Surgeons should consider performing 35 cases or more a year to minimize the risk for complications. Furthermore, the methods used to visualize the relationship between surgeon volume and the occurrence of complications can be easily applied in any jurisdiction, to help inform and optimize local healthcare delivery.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".