The epidemiology of scaphoid fractures and non-unions in Switzerland: a nationwide analysis of the socioeconomic impact.
Bibliographic record
Abstract
Scaphoid fractures are the second most common wrist injury after distal radius fractures and primarily affect young individuals in their most productive working years. Some scaphoid fractures fail to heal, potentially resulting in chronic pain, functional impairment, and long-term osteoarthritis in the wrist, which may require salvage procedures and can have a significant impact on work capacity. Considerable debate exists around the biological and injury-related risk factors for scaphoid non-unions, as well as the criteria for surgical intervention. However, epidemiological data are still limited, often derived from small populations, and incidence reports about scaphoid non-unions remain inconsistent. In a retrospective analysis of over 9 Mio injuries, recorded by the Swiss National Accident Insurance (Suva) Statistical Service from 2008 to 2021, we identified 16,691 scaphoid fractures. The male-to-female ratio was 4:1 for both scaphoid fractures and non-unions. The rate of primary surgery was 1:3. Around 14% of scaphoid fractures progressed to non-union, and 3% developed posttraumatic arthritis. Patients with non-unions were three times more likely to be unable to work for more than 12 months. Blue-collar workers were particularly at risk for a non-union and for extended work absence. Notably, the type of treatment (surgical or non-surgical) had no significant effect on work absence-non-union itself was the key determinant.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".