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Enregistrement W2316145668 · doi:10.1542/gr.33-5-56

Emergency Department Visits for Children With Cancer

2015· article· en· W2316145668 sur OpenAlexaboutno aff

Notice bibliographique

RevueAAP Grand Rounds · 2015
Typearticle
Langueen
DomaineMedicine
ThématiqueChildhood Cancer Survivors' Quality of Life
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineEmergency departmentCitationIconCancerFamily medicineMedical emergencyLibrary scienceNursingInternal medicine

Résumé

récupéré en direct d'OpenAlex

Source: Mueller EL, Sabbatini A, Gebremariam A, et al. Why pediatric patients with cancer visit the emergency department: United States, 2006–2010. Pediatr Blood Cancer. 2015; 62(2): 490– 549; doi: 10.1002/pbc.25288Investigators from the University of Michigan and the Hospital for Sick Children, Toronto, conducted a retrospective cohort study to determine the reasons for which children with cancer seek emergent care and the factors associated with consequent hospital admission. Using data from the Healthcare Cost and Utilization Project’s Nationwide Emergency Department Sample (NEDS), children diagnosed with cancer were selected by assessing all US pediatric emergency department (ED) encounters from 2006–2010. De-identified data included primary cancer and ED discharge, patient demographics, hospital characteristics, and inpatient data, when appropriate. Since NEDS is a national database containing a 20% stratified probability sample of all hospital-based EDs, weighted analyses were conducted to attain representative estimates of ED visits, disposition status, and factors relating to admission. Characteristics of visits that led to discharge from the ED versus hospital admission were compared using regression analysis.A total of 294,289 ED visits for children with cancer, aged 0–19 years, representing 0.2% of all nationwide pediatric ED evaluations over this 5-year period, were analyzed. Acute lymphoblastic leukemia comprised 25.9% of malignancies in this cohort, followed by central nervous system tumor (8.1%) and acute myelogenous leukemia (7.5%). Of the top 10 reasons for ED encounters, fever and febrile neutropenia (FN) represented 19.2% of the visits, blood stream infections 4.3% of visits, upper respiratory infection 2.8%, pneumonia 2.5%, and neutropenia 2.2%. Overall, 43.6% of ED visits led to admission for the child at the same hospital as the ED, with highest admission rates for FN (82.3%), neutropenia (80.1%), blood stream infection (74.7%), and pneumonia (67.8%). The average transfer rate to another hospital was 3.7% with highest transfer rates for seizures (9.9%), FN (6.5%), and neutropenia (6.2%). Approximately 0.1% of children with cancer died in the ED.Variables significantly associated with admission versus discharge included age <4 years compared to age 15–19 years, having the highest quartile of median household income compared to the lowest, and having public insurance compared to self-pay status. Children presenting to metropolitan teaching hospitals were more likely to be admitted, while children presenting to non-metropolitan hospitals were less likely to be admitted compared to those attending a metropolitan non-teaching hospital. Children presenting with FN, neutropenia only, pneumonia, and dehydration were more likely to be admitted than discharged home.The authors conclude that children with cancer present to EDs most commonly with fever and FN. Younger age, having FN or neutropenia, and socioeconomic issues were associated with hospital admission from the ED.Dr Hogan 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.Despite improved outcomes for children diagnosed with cancer, immunosuppression remains a common and potentially lethal toxicity related to current chemotherapy, radiotherapy, and immunotherapy. In addition, surgically implanted devices, such as central venous catheters and prostheses, increase the risk for sepsis. Previous studies in hospitalized children have reported inpatient FN episodes associated with 14%–32% infectious complication rates and 0.5%–6.6% mortality rates.1,2 The authors of the current study evaluated ED diagnoses and dispositions of children with cancer, selected from a contemporary national database, representing approximately 30 million weighted hospital-based ED encounters per year.3FN is considered an oncologic emergency and ED personnel must be prepared for this high level of medical acuity.4,5 In an effort to improve outcomes, updated guidelines have been proposed which attempt to standardize emergency practices and stratify patient care based on risk factors.5,6 Although age and malignancy type are infectious risk factors included in the current study, other meaningful risk factors such as disease status (eg, stage, remission, relapse), intensity of treatment based on dose, type, and timing, and comorbid conditions were not assessed.4–6Centralization of pediatric oncology centers in large tertiary hospitals seems to have improved emergent care of treatment-related complications.5,7 The authors of the current study suggest that ED admission and transfer decisions may relate to traveling distances and coordination of multiple subspecialties. Although median household income and insurance status were associated with ED-directed admissions, cultural differences and other economic burdens, which were not addressed, may impact ED utilization and hospitalization. 7 Improving outcomes includes investigation of prevention and supportive measures to eliminate socioeconomic and biologic risk factors.7

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 enseignants0,032
Score d'incertitude au seuil0,594

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 Opus0,040
Tête enseignante GPT0,337
Écart entre enseignants0,297 · 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
Publié2015
Routes d'admission1
Résumé présentoui

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