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Background: The Greater Toronto Area (GTA) was considered a "hot zone" for severe acute respiratory syndrome (SARS) in 2003. In accordance with mandated city-wide infection control measures, the Hospital for Sick Children (HSC) dastically reduced all services while maintaining a fully operational emergency department. Because of the GTA health service suspensions and the overlap of SARS-like symptoms with many common childhood illnesses, this introduced the potential for a change in the volumes of patients visiting the emergency department of the only regional tertiary care children's hospital. Methods: We compared HSC emergency department patient volumes, admission rates and length of stay in the emergency department in the baseline years of 2000-2002 (non-SARS years) with those in 2003 (SARS year). The data from the prior years were modeled as a time series. Using an interrupted time series analysis, we compared the 2003 data for the periods before, during and after the SARS periods with the modeled data for significant differences in the 3 aforementioned outcomes of interest. Results: Compared with the 2000-2002 data, we found no differences in visits, admission rates or length of stay in the pre-SARS period in 2003. There were significant decreases in visits and length of stay (p < 0.001) and increases in admission rates (p < 0.001) during the periods in 2003 when there were new and active cases of SARS in the GTA. All 3 outcomes returned to expected estimates coincident with the absence of SARS cases from September to December 2003. Interpretation: During the SARS outbreak in the GTA, the HSC emergency department experienced significantly reduced volumes of patients with low-acuity complaints. This gives insight into utilization rates of a pediatric emergency depart-ment during a time when there was additional perceived risk in using emergency department services and provides a foundation for emergency department preparedness policies for SARS-like p... [ABSTRACT FROM AUTHOR]

Outlines the process successfully followed by several emergency departments in the Greater Toronto Area during the SARS outbreak between February and September 2003. Modifications in emergency management operations; Construction of a large outdoor SARS assessment unit; Hospital cleaning policies; List of protective gear required for entering an airborne isolation room.

Despite many children experiencing fatigue after childhood brain injury, little is known about the predictors of this complaint. To date, traditional indices of traumatic brain injury (TBI) severity have not predicted reliably persisting fatigue (up to three years post-injury). This study aimed to establish whether persisting fatigue is predicted by serum biomarker concentrations in child TBI. We examined whether acute serum biomarker expression would improve prediction models of 12-month fatigue based on injury severity. Blood samples were collected from 87 children (1–17 years at injury) sustaining mild to severe TBI (Glasgow Coma Scale [GCS] range 3–15; mean 12.43; classified as mild TBI [n = 50, 57%] vs. moderate/severe TBI [n = 37, 43%]), and presenting to the emergency departments (ED) and pediatric intensive care units (PICU) at one of three tertiary pediatric hospitals (Royal Children's Hospital (RCH); Hospital for Sick Children (HSC), Toronto; St Justine Children's Hospital (SJH), Montreal). Six serum biomarker concentrations were measured within 24 h of injury (interleukin-6, interleukin-8 [IL-8], soluble vascular cell adhesion molecule [SVCAM], S100 calcium binding protein B [S100B], neuron specific enolase [NSE], and soluble neural cell adhesion molecule [sNCAM]). Fatigue at 12 months post-injury was measured using the Pediatric Quality of Life Inventory Multidimensional Fatigue Scale (parent report), classified as present/absent using previously derived cut-points. At 12 months post-injury, 22% of participants experienced fatigue. A model including IL-8 was the best serum biomarker for estimating the probability of children experiencing fatigue at 12 months post-injury. The IL-8 also significantly improved predictive models of fatigue based on severity. [ABSTRACT FROM AUTHOR]