Optimal Technical Factors During Operative Management of Low-Energy Femoral Neck Fractures
Bibliographic record
Abstract
OBJECTIVE: To determine if cancellous screw (CS) and sliding hip screw (SHS) technical factors during low-energy femoral neck fracture fixation affects a 24-month revision surgery rate and health-related quality of life (HRQL). DESIGN: Prospective randomized controlled study. SETTING: International, multicenter. PATIENTS: Eight hundred ninety-eight femoral neck fracture patients age 50 years and older. INTERVENTION: Patients were randomized to fracture stabilization with either CSs or a SHS device as part of the Fixation Using Alternative Implants for the Treatment of Hip Fractures (FAITH) trial. CS technical factors analyzed included screw diameter, short versus long screw threads, screw number and formation, screw orientation, and washer use. SHS technical factors studied were side plate length, supplemental screw use, lag screw position, and tip-apex distance. MAIN OUTCOME MEASUREMENTS: Revision surgeries within 24 months to promote fracture healing, relieve pain, treat infection, or improve function. In addition, HRQL measures were collected, including the SF-12 Physical Component Score and Western Ontario and McMaster Universities Osteoarthritis Index. RESULTS: The 3-screw inverted triangle pattern had a significantly lower revision surgery rate than a 3-screw triangle formation (P = 0.004). No other CS or SHS technical factors were predictive of revision surgery or affected a patient's HRQL (P > 0.05). CONCLUSIONS: A 3-screw inverted triangle pattern was superior to a 3-screw triangle formation. However, injury and patient factors such as fracture displacement, age, smoking status and sex play a more significant role in clinical outcomes for low-energy femoral neck fracture treatment. LEVEL OF EVIDENCE: Therapeutic Level III. 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".