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Record W2947618001 · doi:10.1093/pch/pxz066.035

36 Management of Periorbital and Orbital Cellulitis in two Eras at a Tertiary Care Pediatric Hospital

2019· article· en· W2947618001 on OpenAlexaff
Carsten Krueger, Sanjay Mahant, Nurshad Begum, Patricia C. Parkin, Peter J. Gill

Bibliographic record

VenuePaediatrics & Child Health · 2019
Typearticle
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsSick childMedicinePediatricsFamily medicineGeneral surgery

Abstract

fetched live from OpenAlex

Pediatric orbital cellulitis is a common but serious infection that, if untreated, can result in severe complications such as meningitis, sinus venous thrombosis, and blindness. Clinically, orbital cellulitis can be difficult to differentiate from periorbital cellulitis, and often requires orbital imaging. The most common causal infectious agents have changed over time largely due to the development of vaccines (e.g. H. influenzae serotype b and heptavalent pneumococcal conjugate vaccines), and with them, empiric antibiotic recommendations. To compare the management and outcomes of children hospitalized with periorbital or orbital cellulitis from two eras. Data were extracted from the health records of children less than 18 years hospitalized at a tertiary care pediatric hospital with a diagnosis of periorbital or orbital cellulitis from 2000–2005 and 2012–2016. Patient demographics, use of diagnostic imaging (CT and/or MRI), number and type of intravenous antibiotics, use of intranasal steroids, length of stay, and rates of surgery were collected using a standardized data collection form. Data from the two eras were compared using t-tests and Mann–Whitney U tests (for continuous data) and chi-square tests (for proportions). Overall, 362 children were included, 161 from 2000–2005, and 201 from 2012–2016. There were no significant differences in mean age (75 months) or sex distribution (67% male) between the two eras. There was no significant difference in rates of CT scan (56% vs 59%), but there was a significant increase in rates of MRI (5% vs 12%, p=0.03). There was an increase in the mean number of intravenous antibiotics used (1.7 vs 2.4, p<0.01), an increase in Ceftriaxone (16% vs 77%, p<0.01) and Cloxacillin (7% vs 47%, p<0.01), and a decrease in Cefuroxime (56% vs 11%, p<0.01). There was an increase in intranasal steroid use (3% vs 45%, p<0.01). There were no significant differences in outcomes, including length of stay (median 90.3 vs 83 hours) and surgical rates (18% vs 17%). Between 2000–2005 and 2012–2016, there were substantial changes in management of orbital and periorbital cellulitis, specifically use of MRI, number and type of intravenous antibiotics, and use of intranasal steroids. Use of CT scan remained high in both eras. There was no change in length of stay or frequency of surgical intervention. Future research is needed to optimize management, reduce harms from ionizing radiation of CT scans, and improve outcomes of children hospitalized with periorbital and orbital cellulitis.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.005
GPT teacher head0.267
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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