A Review of Techniques Used in the Management of Growing Skull Fractures
Bibliographic record
Abstract
BACKGROUND: Growing skull fractures (GSFs) are rare complications of pediatric head trauma that comprise skull fractures associated with an underlying dural tear and an intact arachnoid membrane. They are often misdiagnosed, and delay in management can lead to progression of the disease along with its neurological sequelae. Multiple clinical reports and qualitative reviews on this entity exist. To our knowledge, this represents the largest clinical review reporting on established techniques in the management of these fractures. METHODS: A literature search was performed on the databases Embase, Medline, Cochrane, and PubMed from their inception until February 2015 using the terms "Growing," "Skull," "Fracture," and their equivalent terms. Studies included were case series with 5 or more patients describing GSFs and their management. RESULTS: Twenty-two articles reporting 440 patients were included in the analysis. The mean age at trauma was 8.8 months, with the mean at presentation of 21.9 months and 57.8% of the patients being males. Most commonly, a combined dura-cranioplasty was done in 61.6% of the patients. A range of autoplastic and alloplastic materials were used in both of these techniques. Improvement from preoperative clinical status in seizures and neurological deficits was noted in 18 (12.7%) and 11 (7.05%) of the patients, respectively, following operative repair and medical management. DISCUSSION: Early recognition is crucial in the management and treatment of GSF. Children at risk for developing GSF should be monitored clinically for up to 3 months following the initial insult. The surgical treatment depends on the size of the fracture and the age of the patient. A summary of the presentation, management, associated outcomes, complications, and recommendations discussed in the literature are reported within.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".