VOLAR VERSUS DORSAL PLATING IN CORRECTIVE OSTEOTOMY OF DISTAL RADIUS MALUNION: A META-ANALYSIS EXAMINING COMPLICATIONS, REOPERATIONS, AND HARDWARE REMOVAL RATES
Bibliographic record
Abstract
The primary objective of this meta-analysis is to systematically evaluate and compare complication, reoperation, and hardware removal rates between volar and dorsal plating in the context of corrective osteotomy for dorsally-angulated distal radius malunions. An extensive search across the MEDLINE, Embase, and CINAHL (Cumulative Index to Nursing and Allied Health Literature) databases was conducted to identify studies reporting outcomes following corrective osteotomy for dorsally-angulated distal radius malunions. Coprimary outcomes included: the occurrence of major complications, minor complications, reoperation, and hardware removal rates. Meta-analysis comparing each outcome with further meta-regression model based on surgical approach to compare the odds for each outcome was built. A total of 403 patients were included; 253 patients underwent volar corrective osteotomy and 150 underwent dorsal corrective osteotomy. Mean follow-up was 30 months. Volar plating was associated with fewer reoperations (9% vs. 28%), less hardware removal (3% vs. 18%) and comparable major complications (5% vs. 6%) compared to dorsal plating. The adjusted model showed a significant reduction (approximately 85%) in the odds of reoperation and hardware removal in the volar group. There was no difference in major or minor complications between the groups. This study shows that volar plating for dorsally angulated distal radial osteotomy significantly reduces the odds of reoperation and hardware removal compared to dorsal plating, even after careful adjustment for potential confounders.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.047 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".