Emergency Department Visits for Children With Cancer
Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".