Compression plating versus intramedullary nailing of humeral shaft fractures—a meta-analysis
Bibliographic record
Abstract
BACKGROUND: The choice of plates or intramedullary nails for operatively treated humeral shaft fractures remains controversial, since randomized controlled trials have lacked sufficient power. A meta-analysis of existing trials would improve inferences regarding the treatment effect. METHODS: We reviewed randomized trials in Medline, Cochrane and SciSearch, along with other sources of published randomized trials from 1969-2000. Of 215 citations identified, only 3 studies were included. RESULTS: The 3 studies (involving 155 patients) were pooled, since they were homogeneous (p > 0.1). Plate fixation gave a lower relative risk of reoperation than intramedullary nailing (RR = 0.26, 95% CI 0.007-0.9, p = 0.03). This translated to a risk reduction of 74% for reoperation when plate fixation was employed. Thus, 1 reoperation could be prevented for every 10 patients treated with plates. Plate fixation also reduced the risk of shoulder problems in comparison to intramedullary nails (RR = 0.10, 95% CI 0.03-0.4, p = 0.002). INTERPRETATION: Plate fixation of humeral shaft fractures may reduce the risk of reoperation and shoulder impingement. The cumulative evidence remains inconclusive, and a larger trial is needed in order to confirm these findings.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.019 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 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".