Practice Patterns in the Management of Preseptal and Orbital Cellulitis: A National Survey
Bibliographic record
Abstract
OBJECTIVE: To describe clinical practice patterns in diagnostic testing, antibiotic treatment, hospitalization, subspecialty consultation, and discharge recommendations for children with preseptal and orbital cellulitis across Canadian hospitals. METHODS: A cross-sectional survey of pediatric hospitalists and pediatric emergency department (ED) physicians was conducted. The survey was distributed through the Canadian Pediatric Inpatient Research Network and completed by hospital representatives. Site-level clinical management specific to clinician was assessed. Data were analyzed descriptively. RESULTS: Of 40 hospitals contacted (17 children's and 23 community hospitals), 32 responded (80%; 13 children's hospitals, 19 community hospitals). The most ordered tests in the ED were complete blood count (81.9%) and C-reactive protein (CRP; 81.9%). When not ordered in the ED, 20 (62.5%) pediatric inpatient services ordered CRP and 4 (12.5%) ordered erythrocyte sedimentation rate. For admitted children, computed tomography scans were ordered always or frequently by 46.2% of children's hospital pediatricians and 5.3% of community hospital pediatricians. Ophthalmology (n = 11, 84.6%), otolaryngology (n = 9, 69.2%), and infectious diseases (n = 6, 46.2%) were frequently consulted at children's hospitals. Children with preseptal cellulitis not requiring admission were usually discharged home on oral cephalexin, whereas 2 sites recommended intravenous (IV) ceftriaxone. All children admitted with orbital cellulitis received IV antibiotics initially, most commonly a third-generation cephalosporin with antianerobic and antistaphylococcal agents or a third-generation cephalosporin with an antistaphylococcal agent. CONCLUSIONS: There is limited consensus on diagnostic tests, subspeciality consultation, and empirical antibiotic therapy for preseptal and orbital cellulitis. This survey provides insight into health system-level usage that highlights the need to develop a clinical practice guideline to help standardize management.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".