Optimal Internal Fixation for Femoral Neck Fractures: Multiple Screws or Sliding Hip Screws?
Bibliographic record
Abstract
INTRODUCTION: The number of hip fractures is likely to exceed 500,000 in the United States and 88,000 in Canada annually over the next 40 years. Hip fractures are associated with a 30% mortality rate at 1 year and profound temporary, and sometimes permanent, impairment of independence and quality of life. OBJECTIVES: Although much focus has centered around the comparison of arthroplasty versus internal fixation devices in the treatment of femoral neck fractures, the optimal approach for internal fixation has been largely ignored. Identifying the optimal technique for internal fixation could reduce the historically high rates of revision surgery that have fueled arguments against fixing patients with displaced femoral neck fractures. RESULTS: Both indirect and direct comparisons suggest a possible benefit for a sliding hip screw over multiple cancellous screws in reducing the need for revision surgery. The indirect nature of the comparison from the meta-analysis of arthroplasty versus internal fixation, and the small sample sizes, methodological limitations, and nonsignificant pooled estimate from the direct comparisons, leaves the issue very much in doubt. CONCLUSIONS: Although the rationale for arthroplasty continues to gain popularity, previous studies suggest that we have yet to identify the best approach for internal fixation. Previous trials suggest that the issue is largely unresolved and solutions will likely come from larger randomized trials comparing alternative devices for fixing the hip.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".