Accuracy of Clinical Examination in Suspected Pediatric Scaphoid Fractures—A Systematic Review
Bibliographic record
Abstract
Background: Accurate diagnosis of scaphoid fractures in children is challenging. Many children are treated with empiric immobilization to avoid missing an occult fracture, but this results in unnecessary immobilization, investigation, and patient and healthcare-related costs. It is unknown if clinical predictors exist to guide clinicians on which patients are at high risk for fracture or require advanced imaging. This study aimed to systematically review the use of clinical predictors in the diagnosis of suspected pediatric scaphoid fractures. Methods: A systematic review of all studies evaluating clinical predictors for suspected pediatric scaphoid fractures was performed by searching MEDLINE, Embase, CENTRAL, and CINAHL databases. Studies were included if there was clinical assessment of the wrist prior to confirmatory imaging with plain radiography, magnetic resonance imaging, computed tomography, and/or bone scintigraphy. Studies were excluded if they lacked primary data, if pediatric data could not be extracted, or if they were written in a language other than English. Results: Five studies examining 7 clinical examination techniques met the criteria for inclusion in the systematic review. Study and test characteristics were extracted, but studies were too heterogeneous to permit meta-analysis. Quality assessment of the included studies demonstrated risk of bias in index testing and inconsistent definition of the reference standard. Conclusions: Evidence supporting clinical predictors in children with suspected scaphoid fracture is lacking. Further understanding of clinical predictors and the role of imaging in children with suspected scaphoid injuries is required to reduce the burden of overtreated patients.
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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 | 0.007 | 0.342 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".