Efficacy of different fixation devices in maintaining an initial reduction for surgically managed distal radius fractures.
Bibliographic record
Abstract
BACKGROUND: Fracture of the distal radius is a common injury. Many treatment options exist for the surgical management of extra-articular and intra-articular distal radius fractures. The best method of treatment for these fractures remains controversial. We sought to examine radiographic outcomes of patients treated with non-spanning external fixator (NSEF), open reduction and internal fixation (ORIF) with locking plates and screws or closed reduction and percutaneous pinning (CRPP) and compare their ability to maintain radiographic parameters over the initial 6-week postoperative period. METHODS: We performed a retrospective review of radiographs showing 211 distal radius fractures treated with NSEF, ORIF or CRPP. We examined the images for a variety of radiological parameters. Measurements were taken immediately postoperatively and at 6-week follow-up to determine whether there was any loss of reduction. RESULTS: Of the 211 fractures, 104 (49.3%) were type-A fractures, 12 (5.7%) were type-B fractures and 95 (45.0%) were type-C fractures. The 3 treatments maintained the reduction obtained at surgery until healing. The CRPP and ORIF treatments failed to maintain correction in ulnar variance for the 6-week period; however, only ORIF actually changed the ulnar variance from presurgical values. CONCLUSION: Treatment with ORIF for comminuted, intra-articular distal radius fractures produces good radiographic results with maintenance of surgical radiographic parameters, whereas NSEFand CRPP of less complex fractures also provide good results. This suggests that fracture-specific fixation with CRPP or NSEF are sufficient for certain distal radius fractures.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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".