Meta-analysis of unipolar and bipolar hemiarthroplasty for femoral neck fractures
Bibliographic record
Abstract
Abstract Background Femoral neck fracture is a common fracture in the elderly. Improper treatment seriously impacts the patient and could potentially shorten their lifespan. Hemi-arthroplasty is a common treatment for femoral neck fractures, but the selection of unipolar prosthesis or bipolar prosthesis is still a controversial issue. Therefore, we conducted this comprehensive meta-analysis to compare the outcomes of unipolar and bipolar prostheses. Methods We searched the PubMed, EMbase, The Cochrane Library, and Web of Science databases for randomized controlled trials and cohort studies comparing unipolar hemiarthroplasty and bipolar hemiarthroplasty. The revised Jadad scale or Newcastle-Ottawa Scale was used to assess the quality of the included studies. After data extraction, continuous data were expressed as standardized mean differences and binary data were expressed as odds ratio. The postoperative infection, mortality, acetabular erosion rate, dislocation rate, and Harris hip score were compared and analyzed with Stata software. Results Nineteen studies that compared unipolar and bipolar replacement were included in the meta-analysis. We found no significant differences in the postoperative infection, mortality, dislocation rate, or Harris hip score between unipolar and bipolar replacement. The rate of acetabular erosion in the unipolar group was slightly higher than that in the bipolar group. Conclusions Existing studies have revealed that bipolar hemiarthroplasty is superior to unipolar hemiarthroplasty for femoral neck fractures in terms of acetabular erosion.
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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 | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.036 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".