Management of Isolated Skull Fractures in Pediatric Patients
Bibliographic record
Abstract
OBJECTIVES: Isolated skull fractures (ISFs) in children are one of the most common emergency department injuries. Recent studies suggest these children may be safely discharged following ED evaluation with little risk of delayed neurological compromise. The aim of this study was to propose an evidence-based protocol for the management of ISF in children in an effort to reduce medically unnecessary hospital admissions. METHODS: Using PubMed and The Cochrane Library databases, a literature search using the search terms (pediatric OR child) AND skull fracture AND (isolated OR linear) was performed. Three hundred forty-three abstracts were identified and screened based on the inclusion criteria: (1) linear, nondepressed ISF; (2) no evidence of intracranial injury; (3) age 18 years or younger; and (4) data on patient outcomes and management. Data including age, Glasgow Coma Scale score on arrival, repeat imaging, admission rates, need for neurosurgical intervention, and patient outcome were collected. Two authors reviewed each study for data extraction and quality assessment. RESULTS: Fourteen articles met the eligibility criteria. Data including admission rates, outcomes, and necessity of neurosurgical intervention were analyzed. Admission rates ranged from 56.8% to 100%; however, only 8 of more than 5000 patients developed new imaging findings after admission, all of which were nonsurgical. Only 1 patient required neurosurgical intervention for a finding evident upon initial evaluation. CONCLUSIONS: Pediatric ISF patients with a presenting Glasgow Coma Scale score of 15 who are neurologically intact and tolerating feeds without concern for nonaccidental trauma or an unstable social environment can safely be discharged following ED evaluation to a responsible caregiver.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".