Indications and outcomes of radial head excision: A systematic review
Bibliographic record
Abstract
BACKGROUND: Radial head excision has historically been a common surgical procedure for the operative management of radial head fractures and post-traumatic conditions. With recent advances in other surgical techniques, controversy exists regarding its indications. This review evaluates the indications and outcomes of radial head excision in traumatic and non-traumatic elbow pathology. METHODS: Multiple databases were searched for studies involving radial head excision. Screening and data abstraction were conducted in duplicate. Only studies reporting outcomes for radial head excision were included. RESULTS: Twenty-seven studies with 774 radial head excision patients were included. The most common indications involved acute excision of comminuted radial head fractures (n = 347) and rheumatoid arthritis (n = 201). Post-operative functional scores after acute excision were reported to be good to excellent. In the chronic setting of rheumatoid disease, radial head excision resulted in improved range of motion, although pain was not effectively relieved. DISCUSSION: Outcomes of radial head excision for acute fracture are good to excellent; however, it should not be performed when concurrent or ligamentous injuries are present. Although some studies compared excision to open reduction and internal fixation or replacement, more data are needed to make proper conclusions. The strength of these conclusions is limited by the quality of included literature.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".