Do All Clavicle Fractures in Children Need To Be Managed by Orthopedic Surgeons?
Bibliographic record
Abstract
OBJECTIVES: Although many uncomplicated pediatric fractures do not require routine long-term follow-up with an orthopedic surgeon, practitioners with limited experience dealing with pediatric fractures will often defer to a strategy of frequent clinical and radiographic follow-up. Development of an evidence-based clinical care pathway can help unnecessary radiation exposure to this patient population and reduce costs to patient families and the health care system. METHODS: A retrospective analysis including patients who presented to the Hospital for Sick Children (SickKids) for management of clavicle fractures was performed. RESULTS: Three hundred forty patients (227 males, 113 females) with an average age of 8.1 years (range, 0.1-17.8) were included in the study. The mean number of clinic visits including initial consultation in the emergency department was 2.1 (1.3). The mean number of radiology department appointments was 1.8 (1.3), where patients received a mean number of 4.2 (3.0) radiographs. Complications were minimal: 2 refractures in our series and no known cases of nonunion. All patients achieved clinical and radiographic union and returned to sport after fracture healing. CONCLUSIONS: Our series suggests that the decision to treat operatively is made at the initial assessment. If no surgical indications were present at the initial assessment by the primary care physician, then routine clinical or radiographic follow-up is unnecessary. Our pediatric clavicle fracture pathway will reduce patient radiation exposure and reduce costs incurred by the health care system and patients' families without jeopardizing patient outcomes.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".