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Enregistrement W4409016011 · doi:10.1542/gr.53-4-47

Early CT Imaging in Severe Orbital Infections

2025· article· en· W4409016011 sur OpenAlexaboutno aff

Notice bibliographique

RevueAAP Grand Rounds · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueSinusitis and nasal conditions
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineRadiology

Résumé

récupéré en direct d'OpenAlex

Source: Yu WW, Borkhoff CM, Mahant S, et al. Factors associated with early computed tomography imaging in children hospitalized with severe orbital infections. Hosp Pediatr. 2025;15(1):28-36. doi: 10.1542/hpeds.2024-007990.Investigators from multiple institutions in Canada conducted a retrospective study to identify factors associated with early CT imaging in children hospitalized with severe orbital infections. Participants were patients 2 months to 18 years old hospitalized with periorbital or orbital cellulitis at 1 of 10 hospitals in Canada from 2009 to 2019. Study patients were identified using ICD-10 codes, and the medical records of those meeting eligibility criteria were reviewed. Data collected from the medical records included type of hospital (community or children’s), demographics, physical examination findings in the ED, prior antibiotic treatment, time and day of presentation (weekend, weekday, weekday evening), subspecialty consultation within 24 hours, laboratory findings including white blood cell (WBC) count and C-reactive protein (CRP), and whether a CT was obtained. The primary study outcome was receiving an early CT scan, defined as within 24 hours of ED presentation. Multivariate Poisson regression analysis was used to identify independent predictors or early CT. Variables in the model included hospital factors (type of hospital, time of day of presentation, subspecialty consultation), patient factors (age, prior antibiotics, fever), clinical findings (proptosis, eye swollen shut), and laboratory factors (WBC and CRP).Data were analyzed on 1,144 children with a median age of 4.8 years. Among the study participants, 769 (67.2%) had a diagnosis of periorbital cellulitis, and 66 (32.8%) were diagnosed with orbital cellulitis. Overall, 494 (43.2%) patients received a CT scan within 24 hours of ED presentation. In the multivariate model, hospital factors significantly associated with an early CT scan included presentation to a children’s hospital (adjusted relative risk [aRR], 1.80; 95% confidence interval [CI], 1.32, 2.45), ophthalmology consult (aRR, 2.19; 95% CI, 1.66, 2.90), and otolaryngology consult (aRR, 2.66; 95% CI, 1.84, 3.36). Compared to those 5 to 9 years old, children <5 years of age were less likely to receive a CT scan (aRR, 0.63; 95% CI, 0.53, 0.74). Proptosis was present in 31.4% of children with an early CT scan compared to 3.2% of those with no CT scan (aRR, 1.39; 95% CI, 1.24, 1.57), and having an eye swollen shut was noted in 36.2% and 22.7%, respectively, of patients receiving or not receiving an early CT scan (aRR, 1.27; 95% CI, 1.13, 1.43). Neither the presence of fever or previous antibiotic treatment were predictors of early CT scans. Among laboratory factors, there was no significant association between early CT scan and either WBC count or CRP level.The authors conclude that patient and hospital factors were associated with early CT scans in children with severe orbital infections, but inflammatory markers were not.Dr Loyal has disclosed no financial relationship relevant to this commentary. This commentary does not contain a discussion of an unapproved/investigative use of a commercial product/device.Investigators in the current study shed light on factors associated with early CT imaging in hospitalized Canadian children with periorbital or orbital cellulitis. Their findings build on work done in single-center settings1 and is strengthened by multiple participating hospitals and a decade of data. Acknowledging that severe orbital infections are largely a clinical diagnosis, previous investigators noted that laboratory markers such as WBC and CRP, previously associated with more severe outcomes, were not associated with early imaging. These investigators hypothesize that, perhaps, institutional clinical pathways that are being increasingly utilized to aid clinical decision-making2 have not yet incorporated WBC and CRP into their algorithms for severe orbital infections and more education is needed.A notable finding of the current study was that children under 5 years of age were less likely to undergo early CT imaging, potentially due to the need for sedation or clinician concern regarding radiation risk. In a previous study of orbital cellulitis, children >5 years were more likely to require surgery. (See AAP Grand Rounds. 2022;48[3]:33.)3 Reducing the number of unnecessary CT scans is important, to reduce the pediatric radiation dose.4 Pediatric clinicians, however, ought to avoid relying solely on radiation risk as a reason to delay or forgo imaging, especially when decision-making is further complicated by a high-risk, low-prevalence disease and the need to practice high-value care while prioritizing patient safety. Another area of opportunity is better understanding the utility and accuracy of ultrasound as an alternative imaging modality.5Children who had early CT imaging may have been sent to a children’s hospital for imaging because of suspected orbital infections. The retrospective nature of the current study makes this difficult to ascertain.In hospitalized children with severe orbital infections, established clinical factors (eg, proptosis) and hospital factors (community or children’s), rather than inflammatory markers (eg, CRP), are associated with early CT imaging.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,058
Score d'incertitude au seuil0,283

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,008
Tête enseignante GPT0,274
Écart entre enseignants0,266 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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