Pitch side combined assessment for suspected ankle fractures
Bibliographic record
Abstract
Objective To assess the sensitivity of two musculoskeletal tests as primary examination for on site use. Methods I searched through electronic search engines for articles ranging from 2000 to 2010. I used the key words: ankle injuries, ankle examination, ankle assessment and tuning fork. Data synthesis Ankle injuries are a common injury in sport accounting for 15–45% of all sport injuries. 85% of all ankle injuries concern the lateral ankle complex. However differential diagnosis suggests the examination of fractures such as at the malleolus, fifth metatarsal, navicular, anterior calcaneus process and at the midtarsal bones. During sport events in the misfortune incidence of an ankle injury physicians are required to assess their athletes. However according to each games rules and situation they are required to assess in shortest time possible. Ottawa ankle rules (OAR) have been suggested to have a high sensitivity to detect to assess fractures (Northrup et al 2005; Papacostas et al 2001). Papacostaset al(2001) examined 122 patients and found 100% sensitivity for maleolar and midfoot fractures when applied the OAR. Leddyet al(2002) found 100% sensitivity in 217 patients applying the OAR-Buffalo modification. Moore (2009) found high sensitivity (n=10) using a tuning fork for the detection of transverse fractures. Further is suggested that the use of a tuning fork is an fast and reliable method to assess possible fractures (Moore 2009). Conclusion We believe that the combination of those two tools can provide a clear and fast initial evaluation during an event. Nevertheless in a clinical or on site setting can further increase reliability for assessing fractures where x-ray is not available. However, further investigation is required regarding the reliability of the tuning fork in assessing fractures, reliability of the examiner and time required to complete the progressive examination.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".