Factors Associated With Early Computed Tomography Imaging in Children Hospitalized With Severe Orbital Infections
Bibliographic record
Abstract
OBJECTIVE: We identified factors associated with computed tomographic (CT) imaging within 24 hours of emergency department (ED) presentation in hospitalized children with severe orbital infections. PATIENTS AND METHODS: A multicenter retrospective cohort study was conducted that included children aged 2 months to 18 years between 2009 and 2018 who were admitted to the hospital with severe orbital infections, including periorbital and orbital cellulitis. Multivariable modified Poisson regression was used to identify possible factors associated with receiving a CT scan within 24 hours of ED presentation. RESULTS: Of 1144 children, 494 (43.2%) received a CT scan within 24 hours of ED presentation. Factors associated with receiving a CT scan within 24 hours included sex (male; adjusted relative risk [aRR], 1.18; 95% CI, 1.04-1.33), hospitalized at a children's hospital (aRR, 1.80; 95% CI, 1.32-2.45), consulted by both ophthalmology and otolaryngology (aRR, 3.12; 95% CI, 2.35-4.13) or either ophthalmology (aRR, 2.19; 95% CI, 1.66-2.90) or otolaryngology (aRR, 2.66; 95% CI, 1.84-3.86), and had proptosis (aRR, 1.39; 95% CI, 1.24-1.57) or eye swollen shut (aRR, 1.27; 95% CI, 1.13-1.43) as clinical signs upon ED presentation. Children aged younger than 5 years were less likely to receive early CT imaging (aRR, 0.63; 95% CI, 0.53-0.74). There were no associations between time of ED triage, temperature greater than 38 °C, or inflammatory markers with early CT imaging. CONCLUSION: Although several patient and hospital factors associated with early CT imaging decisions in children with severe orbital infections are associated with more severe infections, newly identified risk factors, such as inflammatory markers, were not. These findings will help better the understanding of clinical management and indications for CT imaging.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".