Distal biceps tendon injuries treatment: A survey of orthopaedic surgeons’ current practice and preferences
Bibliographic record
Abstract
Purpose: Distal biceps tendon (DBT) injuries are relatively uncommon. Controversies exist regarding the best approach, leading to variations in treatment. This study aims to understand the preferences and practices of orthopedic surgeons regarding management of DBT injuries, as well as assess the feasibility of a future pilot randomized controlled trial (RCT) to evaluate the impact of various surgical factors on patient outcomes. Methods: A cross-sectional international survey was conducted amongst surgeons treating patients with DBT injuries. The survey included questions about treatment preferences, surgical techniques, case volumes, and interest in participating in a future RCT. Results: Responses from 491 orthopedic surgeons from 26 countries/territories were obtained. Most surgeons had limited exposure to DBT ruptures. Variations were observed in the work-up process, with some relying solely on clinical examinations while others used diagnostic imaging. A single incision approach was the most common surgical technique, and tendon fixation with suspensory cortical buttons was frequently preferred. Most surgeons did not explore or repair the bicipital aponeurosis. Interest in participating in a future RCT varied for different surgical controversies. Conclusion: This survey provides valuable insights into surgeons' preferences and practices for DBT injury management. The study highlights the need for standardization in the work-up process and the use of evidence-based guidelines. Current practices may be influenced by factors such as training, implant availability, and costs. The survey also identified surgeons and centers interested in collaboration for future multicenter trials, allowing for equitable access to surgical collaboration opportunities and addressing the lack of evidence in DBT rupture treatment. Level of Evidence: Level V, expert-opinion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".