Complex regional pain syndrome after distal radius fracture: A survey of current practices
Bibliographic record
Abstract
INTRODUCTION: Complex regional pain syndrome (CRPS) is a common complication following distal radius fractures that is difficult to diagnose and can lead to permanent disability. While various proposed prophylaxis and treatment modalities exist, high-quality evidence guiding practice is limited. This survey of Orthopaedic Trauma Association (OTA) and Canadian Orthopaedic Association (COA) members was conducted with the primary aim of assessing practice patterns in distal radius fractures complicated with CRPS. METHODS: An electronic survey was distributed to practicing orthopaedic surgeons in the COA and OTA. Questions assessed practice setting, preference in management of distal radius fractures and CRPS, comfort level in managing CRPS, and identification of gaps in management. Responses were anonymized and collected over 8 months. Response data was analyzed using descriptive statistics; thematic analysis was used on free text response. RESULTS: 134 survey responses were completed. 84% of respondents felt the incidence of CRPS in distal radius fractures was 1-10%, while 15% felt it was closer to 11-20%. 24% of respondents utilized the "Budapest Criteria" to diagnose CRPS. 40% offered prophylaxis in patients felt to be at high risk of developing CRPS. 66% of surgeons felt neutral, uncomfortable, or very uncomfortable managing CRPS in distal radius fractures. When asked to consider adopting a prophylactic therapy, 38% of surgeons indicated that a therapy that reduced the absolute risk of CRPS by 6-10% would change their practice. Gaps in current practice included lack of evidence-based treatment and prevention strategies and diagnostic uncertainty. CONCLUSION: This study identified that amongst orthopaedic surgeons in the COA and OTA, diagnosis, treatment, and prophylaxis strategies for CRPS in distal radius fractures are heterogeneous. Surgeons are not confident in their treatment of CRPS. Future studies using rigorous research methods are warranted to improve management.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".