What Factors Increase Revision Surgery Risk When Treating Displaced Femoral Neck Fractures With Arthroplasty: A Secondary Analysis of the HEALTH Trial
Bibliographic record
Abstract
OBJECTIVES: HEALTH was a randomized controlled trial comparing total hip arthroplasty with hemiarthroplasty in low-energy displaced femoral neck fracture patients aged ≥50 years with unplanned revision surgery within 24 months of the initial procedure being the primary outcome. No significant short-term differences between treatment arms were observed. The primary objective of this secondary HEALTH trial analysis was to determine if any patient and surgical factors were associated with increased risk of revision surgery within 24 months after hip fracture. METHODS: We analyzed 9 potential factors chosen a priori that could be associated with revision surgery. The factors included age, body mass index, major comorbidities, independent ambulation, type of surgical approach, length of operation, use of femoral cement, femoral head size, and degree of femoral stem offset. Our statistical analysis was a multivariable Cox regression using reoperation within 24 months of index surgery as the dependent variable. RESULTS: Of the 1441 patients included in this analysis, 8.1% (117/1441) experienced reoperation within 24 months. None of the studied factors were found to be predictors of revision surgery (P > 0.05). CONCLUSION: Both total and partial hip replacements are successful procedures in low-energy displaced femoral neck fracture patients. We were unable to identify any patient or surgeon-controlled factors that significantly increased the need for revision surgery in our elderly and predominately female patient population. One should not generalize our findings to an active physiologically younger femoral neck fracture 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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.011 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".