Are We Over Treating Hand Fractures? Current Practice of Single Metacarpal Fractures
Bibliographic record
Abstract
PURPOSE: We conducted a national survey of Canadian plastic surgeons to assess if inconsistencies in management strategies exist for single metacarpal fractures. METHODS: A cross-sectional study of Canadian plastic surgeons who perform hand surgeries was conducted. A 15-question survey was distributed to all members of the Canadian Society of Plastic Surgeons. Participants' demographics, practice settings, and current treatment strategies for patients presenting with single metacarpal fractures were evaluated. RESULTS: A total of 113 Canadian plastic surgeons met inclusion criteria. The majority of respondents were male (76%), with 50% in practice for more than 15 years. Canadian surgeons used a wide variety of surgical techniques for the management of single metacarpal fractures, with close reduction (94%), Kirshner wires (94%), and splinting and immobilization (89%) being the most common. The majority of plastic surgeons stated that rotational deformity (81%) was the most important indication for surgery. Surgeons demonstrated a trend toward immobilization after splinting (48%), instead of early mobilization after splinting (21%). When results were stratified by years in practice, no differences in surgical and non-surgical management were found, although surgeons in practice for less than 15 years were more likely to suggest hand therapy. CONCLUSION: These findings demonstrate inconsistencies in management of single metacarpal fractures among Canadian plastic surgeons. Surprisingly, surgeons in the survey tended to favor immobilization, as oppose to the literature that favors mobilization. The study highlights the lack of clear guidelines dictating treatment, possibly leading to these inconsistencies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".