Background Dissociative seizures are paroxysmal events resembling epilepsy or syncope with characteristic features that allow them to be distinguished from other medical conditions. We aimed to compare the effectiveness of cognitive behavioural therapy (CBT) plus standardised medical care with standardised medical care alone for the reduction of dissociative seizure frequency. MethodsIn this pragmatic, parallel-arm, multicentre randomised controlled trial, we initially recruited participants at 27 neurology or epilepsy services in England, Scotland, and Wales. Adults (≥18 years) who had dissociative seizures in the previous 8 weeks and no epileptic seizures in the previous 12 months were subsequently randomly assigned (1:1) from 17 liaison or neuropsychiatry services following psychiatric assessment, to receive standardised medical care or CBT plus standardised medical care, using a web-based system. Randomisation was stratified by neuropsychiatry or liaison psychiatry recruitment site. The trial manager, chief investigator, all treating clinicians, and patients were aware of treatment allocation, but outcome data collectors and trial statisticians were unaware of treatment allocation. Patients were followed up 6 months and 12 months after randomisation. The primary outcome was monthly dissociative seizure frequency (ie, frequency in the previous 4 weeks) assessed at 12 months. Secondary outcomes assessed at 12 months were: seizure severity (intensity) and bothersomeness; longest period of seizure freedom in the previous 6 months; complete seizure freedom in the previous 3 months; a greater than 50% reduction in seizure frequency relative to baseline; changes in dissociative seizures (rated by others); health-related quality of life; psychosocial functioning; psychiatric symptoms, psychological distress, and somatic symptom burden; and clinical impression of improvement and satisfaction. p values and statistical significance for outcomes were reported without correction for multiple comparisons as per our protocol. Primary and secondary outcomes were assessed in the intention-to-treat population with multiple imputation for missing observations. This trial is registered with the International Standard Randomised Controlled Trial registry, ISRCTN05681227, and ClinicalTrials.gov, NCT02325544.

Background Coronavirus disease 2019 (COVID-19) has impacted the provision of health services in all specialties. We aim to study the impact of COVID-19 on the utilization of pediatric hospital services including emergency department (ED) attendances, hospitalizations, diagnostic categories and resource utilization in Singapore. Methods We performed a retrospective review of ED attendances and hospital admissions among children < 18 years old from January 1st to August 8th 2020 in a major pediatric hospital in Singapore. Data were analyzed in the following time periods: Pre-lockdown (divided by the change in Disease Outbreak Response System Condition (DORSCON) level), during-lockdown and post-lockdown. We presented the data using proportions and percentage change in mean counts per day with the corresponding 95% confidence intervals (CIs). Results We attended to 58,367 children with a mean age of 5.1 years (standard deviation, SD 4.6). The mean ED attendance decreased by 331 children/day during lockdown compared to baseline (p < 0.001), attributed largely to a drop in respiratory (% change − 87.9, 95% CI − 89.3 to − 86.3, p < 0.001) and gastrointestinal infections (% change − 72.4, 95%CI − 75.9 to − 68.4, p < 0.001). Trauma-related diagnoses decreased at a slower rate across the same periods (% change − 40.0, 95%CI − 44.3 to − 35.3, p < 0.001). We saw 226 children with child abuse, with a greater proportion of total attendance seen post-lockdown (79, 0.6%) compared to baseline (36, 0.2%) (p < 0.001). In terms of ED resource utilization, there was a decrease in the overall mean number of procedures performed per day during the lockdown compared to baseline, driven largely by a reduction in blood investigations (% change − 73.9, 95%CI − 75.9 to − 71.7, p < 0.001). Conclusions We highlighted a significant decrease in infection-related presentations likely attributed to the lockdown and showed that the relative proportion of trauma-related attendances increased. By describing the impact of COVID-19 on health services, we report important trends that may provide guidance when planning resources for future pandemics.

Singapore was one of the earliest countries affected by the coronavirus disease 2019 (COVID-19) pandemic, with more laboratory-confirmed COVID-19 cases in early February 2020 than any other country outside China. This short report is a narrative review of our tertiary paediatric emergency department (ED) perspective and experience managing the evolving outbreak situation. Logistic considerations included the segregation of the ED into physically separate high-risk, intermediate-risk and low-risk areas, with risk-adapted use of personal protective equipment (PPE) for healthcare personnel in each ED area. Workflow considerations included the progressive introduction of outpatient COVID-19 testing in the ED for enhanced surveillance; adapting the admissions process particularly for high-risk and intermediate-risk cases; and the management of unwell accompanying adult caregivers. Manpower considerations included the reorganisation of medical manpower into modular teams to mitigate the risk of hospital transmission of COVID-19. Future plans for a tiered isolation facility should include structural modifications for the permanent isolation facility such as anterooms for PPE donning/doffing; replication of key ED functions in the tent facility such as a separate resuscitation room and portable X-ray room; and refresher PPE training. Dynamic reassessment of ED workflow processes, in conjunction with the hospital and national public health response, may help in managing this novel disease entity.

Of the three methods we evaluated, the BL tape method provided the most accurate and precise weight estimation for Singapore children. The APLS and Luscombe formulae underestimated and overestimated the children's weights, respectively, and were considerably less precise.

We aim to study the association between hyperglycemia and in-hospital outcomes among children with moderate and severe traumatic brain injury (TBI). This retrospective cohort study was conducted in a tertiary pediatric hospital between 2003 and 2013. All patients < 16 years old who presented to the Emergency Department within 24 hours of head injury with a Glasgow Coma Scale (GCS) ≤ 13 were included. Our outcomes of interest were death, 14 ventilation-free, 14 pediatric intensive care unit- (PICU-) free, and 28 hospital-free days. Hyperglycemia was defined as glucose > 200 mg/dL (11.1 mmol/L). Among the 44 patients analyzed, the median age was 8.6 years (interquartile range (IQR) 5.0–11.0). Median GCS and pediatric trauma scores were 7 (IQR 4–10) and 4 (IQR 3–6), respectively. Initial hyperglycemia was associated with death (37% in the hyperglycemia group versus 8% in the normoglycemia group, p = 0.019), reduced median PICU-free days (6 days versus 11 days, p = 0.006), and reduced median ventilation-free days (8 days versus 12 days, p = 0.008). This association was however not significant in the stratified analysis of patients with GCS ≤ 8. Conclusion. Our findings demonstrate that early hyperglycemia is associated with increased mortality, prolonged duration of mechanical ventilation, and PICU stay in children with TBI.

BackgroundPediatric traumatic brain injury (TBI) constitutes a significant burden and diagnostic challenge in the emergency department (ED). While large North American research networks have derived clinical prediction rules for the head injured child, these may not be generalizable to practices in countries with traditionally low rates of computed tomography (CT). We aim to study predictors for moderate to severe TBI in our ED population aged < 16 years.MethodsThis was a retrospective case–control study based on data from a prospective surveillance head injury database. Cases were included if patients presented from 2006 to 2014, with moderate to severe TBI. Controls were age-matched head injured children from the registry, obtained in a 4 control: 1 case ratio. These children remained well on diagnosis and follow up. Demographics, history, and physical examination findings were analyzed and patients followed up for the clinical course and outcome measures of death and neurosurgical intervention. To predict moderate to severe TBI, we built a machine learning (ML) model and a multivariable logistic regression model and compared their performances by means of Receiver Operating Characteristic (ROC) analysis.ResultsThere were 39 cases and 156 age-matched controls. The following 4 predictors remained statistically significant after multivariable analysis: Involvement in road traffic accident, a history of loss of consciousness, vomiting and signs of base of skull fracture. The logistic regression model was created with these 4 variables while the ML model was built with 3 extra variables, namely the presence of seizure, confusion and clinical signs of skull fracture. At the optimal cutoff scores, the ML method improved upon the logistic regression method with respect to the area under the ROC curve (0.98 vs 0.93), sensitivity (94.9% vs 82.1%), specificity (97.4% vs 92.3%), PPV (90.2% vs 72.7%), and NPV (98.7% vs 95.4%).ConclusionsIn this study, we demonstrated the feasibility of using machine learning as a tool to predict moderate to severe TBI. If validated on a large scale, the ML method has the potential not only to guide discretionary use of CT, but also a more careful selection of head injured children who warrant closer monitoring in the hospital.

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ObjectivesFebrile infants younger than 3 months old present a diagnostic dilemma to the emergency physician. We aim to describe a large population of febrile infants less than 3 months old presenting to a pediatric emergency department (ED) and to assess the performance of current heart rate guidelines in the prediction of serious infections (SI).Materials and methodsWe performed a retrospective review of febrile infants younger than 3 months old, between March 2015 and Feb 2016, in a large tertiary pediatric ED. We documented the primary outcome of SI for each infant, as well as the clinical findings, vital signs, and Severity Index Score (SIS). We assessed the performance of the Paediatric Canadian Triage and Acuity Scale (PaedCTAS), Advanced Pediatric Life Support (APLS) guidelines and Fleming normal reference values, using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under receiver operating characteristics curve (AUC).Results1057 infants were analyzed, with 326 (30.6%) infants diagnosed with SI. High temperature, tachycardia, and low SIS score were significantly associated with SI. Item analysis showed that the SIS performance was driven by the presence of mottling (p = 0.003) and high temperature (p<0.001). The APLS guideline had the highest sensitivity (66.0%, 95% CI 60.5–71.1%), NPV (73.3%, 95% CI 69.7–76.5%) and AUC (0.538), while the PaedCTAS (2 standard deviation from normal) had the highest specificity (98.5%, 95% CI 97.3–99.3%) and PPV (55.2%, 95% CI 32.7–71.0%).ConclusionsCurrent guidelines on infantile heart rates have a variable performance. In our study, the APLS heart rate guidelines performed with the highest sensitivity, but no individual guideline predicted for SIs satisfactorily.