Are We Over-Treating Insect Bite Related Periorbital Cellulitis in Children? The Experience of a Large, Tertiary Care Pediatric Hospital
Bibliographic record
Abstract
INTRODUCTION: Preseptal (periorbital) and orbital cellulitis are potentially catastrophic infections near the eye. Preseptal cellulitis is far more common, and although classically reported to be associated with dacrocystitis, sinusitis/upper respiratory infection, trauma/surgery, or infection from contiguous areas, it can also be associated with insect bites. The objective of this study was to determine the prevalence of insect bite-associated preseptal cellulitis and to compare clinical findings and outcomes of these patients with those having other causes for the condition. METHODS: Retrospective chart review of children with a final discharge diagnosis of periorbital cellulitis from January 2009 to December 2014 at a tertiary care children' hospital. RESULTS: 213 children were diagnosed with preseptal cellulitis during the 5-year study period, of whom 60 (28%) were associated with insect bites. Patients in the noninsect bite group more commonly had fever at presentation (P < 0.001), with increased white blood cell and C reactive protein values (both P < 0.001). No patient with insect bite-associated preseptal cellulitis presented with fever, and none underwent radiographic testing or computerized tomography; their mean age was also lower (P < 0.001) and length of stay was significantly shorter. CONCLUSIONS: This study suggests that children with preseptal cellulitis associated with insect bites could be candidates for oral antibiotic therapy with outpatient follow-up by.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".