COMPRESSION SCREWS IN THE TREATMENT OF FRACTURES: A SCOPING REVIEW
Bibliographic record
Abstract
The purpose of this scoping review was to identify and describe the current body of evidence on internal fracture fixation devices that require compression screws. Electronic literature searches were conducted and 665 unique studies were included. Investigations on avulsion fractures represented a small proportion of these studies (45 studies), the remainder being those on patients with fractures with vascular compromise risk. The most common type of avulsion injury investigated was tibial avulsion fractures, followed by fifth metatarsal and calcaneal avulsions. For vascular compromised fractures, greater than half of the studies were on femoral neck injuries while scaphoid injury studies also represented a substantial proportion of this evidence base. Most of the studies were case series and there was limited randomized clinical trial evidence. A total of 429 studies provided sufficient information on the devices used in their investigation; DePuy-Synthes and Acumed ranked as the top two companies in cumulative publications over the last decade. There is a large body of evidence on internal fixation compression screw devices used in the management of fractures; however, the literature is generally dominated by non-comparative research studies. Opportunities to improve the evidence base are large. Manufacturer priority on evidence-based product development is key to ongoing research inquiry.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".