Who Did the Arthroplasty? Hip Fracture Surgery Reoperation Rates are Not Affected by Type of Training—An Analysis of the HEALTH Database
Bibliographic record
Abstract
OBJECTIVES: This study compares outcomes for patients with displaced femoral neck fractures undergoing hemiarthroplasty (HA) or total hip arthroplasty (THA) by surgeons of different fellowship training. DESIGN: Retrospective review of HEALTH trial data. SETTING: Eighty clinical sites across 10 countries. PATIENTS/PARTICIPANTS: One thousand four hundred forty-one patients ≥50 years with low-energy hip fractures requiring surgical intervention. INTERVENTION: Patients were randomized to either HA or THA groups in the initial data set. Surgeons' fellowship training was ascertained retrospectively, and outcomes were compared. MAIN OUTCOME MEASUREMENTS: The main outcome was an unplanned secondary procedure at 24 months. Secondary outcomes included death, serious adverse events, prosthetic joint infection (PJI), dislocation, discharge disposition, and use of ambulatory devices postoperatively. RESULTS: There was a significantly higher risk of PJI in patients treated by surgeons without fellowship training in arthroplasty (P = 0.01), surgeons with unknown fellowship training (P = 0.03), and surgeons with no fellowship training (P = 0.02) than those treated by an arthroplasty-trained surgeon. There were significantly higher odds of being discharged to a facility rather than home in patients who underwent surgery by a surgeon with no fellowship training compared with arthroplasty-fellowship-trained surgeons (P = 0.03). CONCLUSIONS: Arthroplasty for hip fracture can be performed by all orthopaedic surgeons with equivalent reoperation rates. Infection prevention strategies and use of "care pathways" by arthroplasty-fellowship-trained surgeons may account for the lower risk of PJI and higher rate of discharge to home. The authors advocate for the use of evidence-based infection prevention initiatives and standardized care pathways in this patient population. LEVEL OF EVIDENCE: Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".