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Clinical decision rules can help to determine the need for CT imaging in children with head injuries. We aimed to validate three clinical decision rules (PECARN, CATCH, and CHALICE) in a large sample of children. In this prospective observational study, we included children and adolescents (aged <18 years) with head injuries of any severity who presented to the emergency departments of ten Australian and New Zealand hospitals. We assessed the diagnostic accuracy of PECARN (stratified into children aged <2 years and ≥2 years), CATCH, and CHALICE in predicting each rule-specific outcome measure (clinically important traumatic brain injury [TBI], need for neurological intervention, and clinically significant intracranial injury, respectively). For each calculation we used rule-specific predictor variables in populations that satisfied inclusion and exclusion criteria for each rule (validation cohort). In a secondary analysis, we compiled a comparison cohort of patients with mild head injuries (Glasgow Coma Scale score 13–15) and calculated accuracy using rule-specific predictor variables for the standardised outcome of clinically important TBI. This study is registered with the Australian New Zealand Clinical Trials Registry, number ACTRN12614000463673. Between April 11, 2011, and Nov 30, 2014, we analysed 20 137 children and adolescents attending with head injuries. CTs were obtained for 2106 (10%) patients, 4544 (23%) were admitted, 83 (<1%) underwent neurosurgery, and 15 (<1%) died. PECARN was applicable for 4011 (75%) of 5374 patients younger than 2 years and 11 152 (76%) of 14 763 patients aged 2 years and older. CATCH was applicable for 4957 (25%) patients and CHALICE for 20 029 (99%). The highest point validation sensitivities were shown for PECARN in children younger than 2 years (100·0%, 95% CI 90·7–100·0; 38 patients identified of 38 with outcome [38/38]) and PECARN in children 2 years and older (99·0%, 94·4–100·0; 97/98), followed by CATCH (high-risk predictors only; 95·2%; 76·2–99·9; 20/21; medium-risk and high-risk predictors 88·7%; 82·2–93·4; 125/141) and CHALICE (92·3%, 89·2–94·7; 370/401). In the comparison cohort of 18 913 patients with mild injuries, sensitivities for clinically important TBI were similar. Negative predictive values in both analyses were higher than 99% for all rules. The sensitivities of three clinical decision rules for head injuries in children were high when used as designed. The findings are an important starting point for clinicians considering the introduction of one of the rules. National Health and Medical Research Council, Emergency Medicine Foundation, Perpetual Philanthropic Services, WA Health Targeted Research Funds, Townsville Hospital Private Practice Fund, Auckland Medical Research Foundation, A + Trust.

Viral bronchiolitis is the most common cause of admission to hospital for infants in high-income countries. Respiratory syncytial virus accounts for 60–80% of bronchiolitis presentations. Bronchiolitis is diagnosed clinically without the need for viral testing. Management recommendations, based predominantly on high-quality evidence, advise clinicians to support hydration and oxygenation only. Evidence suggests no benefit with use of glucocorticoids or bronchodilators, with further evidence required to support use of hypertonic saline in bronchiolitis. Evidence is scarce in the intensive care unit. Evidence suggests use of high-flow therapy in bronchiolitis is limited to rescue therapy after failure of standard subnasal oxygen only in infants who are hypoxic and does not decrease rates of intensive care unit admission or intubation. Despite systematic reviews and international clinical practice guidelines promoting supportive rather than interventional therapy, universal de-implementation of interventional care in bronchiolitis has not occurred and remains a major challenge.

BackgroundFollowing a relative absence in winter 2020, a large resurgence of respiratory syncytial virus (RSV) detections occurred during the 2020/2021 summer in Western Australia. This seasonal shift was linked to SARS-CoV-2 public health measures. We examine the epidemiology and RSV testing of respiratory-coded admissions, and compare clinical phenotype of RSV-positive admissions between 2019 and 2020.MethodAt a single tertiary paediatric centre, International Classification of Diseases, 10th edition Australian Modification-coded respiratory admissions longer than 12 hours were combined with laboratory data from 1 January 2019 to 31 December 2020. Data were grouped into bronchiolitis, other acute lower respiratory infection (OALRI) and wheeze, to assess RSV testing practices. For RSV-positive admissions, demographics and clinical features were compared between 2019 and 2020.ResultsRSV-positive admissions peaked in early summer 2020, following an absent winter season. Testing was higher in 2020: bronchiolitis, 94.8% vs 89.2% (p=0.01); OALRI, 88.6% vs 82.6% (p=0.02); and wheeze, 62.8% vs 25.5% (p<0.001). The 2020 peak month, December, contributed almost 75% of RSV-positive admissions, 2.5 times the 2019 peak. The median age in 2020 was twice that observed in 2019 (16.4 vs 8.1 months, p<0.001). The proportion of RSV-positive OALRI admissions was greater in 2020 (32.6% vs 24.9%, p=0.01). There were no clinically meaningful differences in length of stay or disease severity.InterpretationThe 2020 RSV season was in summer, with a larger than expected peak. There was an increase in RSV-positive non-bronchiolitis admissions, consistent with infection in older RSV-naïve children. This resurgence raises concern for regions experiencing longer and more stringent SARS-CoV-2 public health measures.

Phenytoin is the current standard of care for second-line treatment of paediatric convulsive status epilepticus after failure of first-line benzodiazepines, but is only effective in 60% of cases and is associated with considerable adverse effects. A newer anticonvulsant, levetiracetam, can be given more quickly, is potentially more efficacious, and has a more tolerable adverse effect profile. We aimed to determine whether phenytoin or levetiracetam is the superior second-line treatment for paediatric convulsive status epilepticus. ConSEPT was an open-label, multicentre, randomised controlled trial conducted in 13 emergency departments in Australia and New Zealand. Children aged between 3 months and 16 years, with convulsive status epilepticus that failed first-line benzodiazepine treatment, were randomly assigned (1:1) using a computer-generated permuted block (block sizes 2 and 4) randomisation sequence, stratified by site and age (≤5 years, >5 years), to receive 20 mg/kg phenytoin (intravenous or intraosseous infusion over 20 min) or 40 mg/kg levetiracetam (intravenous or intraosseous infusion over 5 min). The primary outcome was clinical cessation of seizure activity 5 min after the completion of infusion of the study drug. Analysis was by intention to treat. This trial is registered with the Australian and New Zealand Clinical Trials Registry, number ACTRN12615000129583. Between March 19, 2015, and Nov 29, 2017, 639 children presented to participating emergency departments with convulsive status epilepticus; 127 were missed, and 278 did not meet eligibility criteria. The parents of one child declined to give consent, leaving 233 children (114 assigned to phenytoin and 119 assigned to levetiracetam) in the intention-to-treat population. Clinical cessation of seizure activity 5 min after completion of infusion of study drug occurred in 68 (60%) patients in the phenytoin group and 60 (50%) patients in the levetiracetam group (risk difference −9·2% [95% CI −21·9 to 3·5]; p=0·16). One participant in the phenytoin group died at 27 days because of haemorrhagic encephalitis; this death was not thought to be due to the study drug. There were no other serious adverse events. Levetiracetam is not superior to phenytoin for second-line management of paediatric convulsive status epilepticus. Health Research Council of New Zealand, A+ Trust, Emergency Medicine Foundation, Townsville Hospital Private Practice Fund, Eric Ormond Baker Charitable Fund, and Princess Margaret Hospital Foundation.

Pneumonia remains a leading cause of hospitalization and death among young children worldwide, and the diagnostic challenge of differentiating bacterial from non-bacterial pneumonia is the main driver of antibiotic use for treating pneumonia in children. Causal Bayesian networks (BNs) serve as powerful tools for this problem as they provide clear maps of probabilistic relationships between variables and produce results in an explainable way by incorporating both domain expert knowledge and numerical data. We used domain expert knowledge and data in combination and iteratively, to construct, parameterise and validate a causal BN to predict causative pathogens for childhood pneumonia. Expert knowledge elicitation occurred through a series of group workshops, surveys and one-on-one meetings involving 6-8 experts from diverse domain areas. The model performance was evaluated based on both quantitative metrics and qualitative expert validation. Sensitivity analyses were conducted to investigate how the target output is influenced by varying key assumptions of a particularly high degree of uncertainty around data or domain expert knowledge. Designed to apply to a cohort of children with X-ray confirmed pneumonia who presented to a tertiary paediatric hospital in Australia, the resulting BN offers explainable and quantitative predictions on a range of variables of interest, including the diagnosis of bacterial pneumonia, detection of respiratory pathogens in the nasopharynx, and the clinical phenotype of a pneumonia episode. Satisfactory numeric performance has been achieved including an area under the receiver operating characteristic curve of 0.8 in predicting clinically-confirmed bacterial pneumonia with sensitivity 88% and specificity 66% given certain input scenarios (i.e., information that is available and entered into the model) and trade-off preferences (i.e., relative weightings of the consequences of false positive versus false negative predictions). We specifically highlight that a desirable model output threshold for practical use is very dependent upon different input scenarios and trade-off preferences. Three commonly encountered scenarios were presented to demonstrate the potential usefulness of the BN outputs in various clinical pictures. To our knowledge, this is the first causal model developed to help determine the causative pathogen for paediatric pneumonia. We have shown how the method works and how it would help decision making on the use of antibiotics, providing insight into how computational model predictions may be translated to actionable decisions in practice. We discussed key next steps including external validation, adaptation and implementation. Our model framework and the methodological approach can be adapted beyond our context to broad respiratory infections and geographical and healthcare settings.

Acute viral wheeze in children is a major cause of hospitalisation and a major risk factor for the development of asthma. However, the role of the respiratory tract microbiome in the development of acute wheeze is unclear. To investigate whether severe wheezing episodes in children are associated with bacterial dysbiosis in the respiratory tract, oropharyngeal swabs were collected from 109 children with acute wheezing attending the only tertiary paediatric hospital in Perth, Australia. The bacterial community from these samples was explored using next generation sequencing and compared to samples from 75 non-wheezing controls. No significant difference in bacterial diversity was observed between samples from those with wheeze and healthy controls. Within the wheezing group, attendance at kindergarten or preschool was however, associated with increased bacterial diversity. Rhinovirus (RV) infection did not have a significant effect on bacterial community composition. A significant difference in bacterial richness was observed between children with RV-A and RV-C infection, however this is likely due to the differences in age group between the patient cohorts. The bacterial community within the oropharynx was found to be diverse and heterogeneous. Age and attendance at day care or kindergarten were important factors in driving bacterial diversity. However, wheeze and viral infection were not found to significantly relate to the bacterial community. Bacterial airway microbiome is highly variable in early life and its role in wheeze remains less clear than viral influences.

Background Differentiating bacterial from viral pneumonia is important for guiding targeted management and judicious use of antibiotics. We assessed if clinical characteristics and blood inflammatory biomarkers could be used to distinguish bacterial from viral pneumonia. Methods Western Australian children (≤17 years) hospitalized with radiologically-confirmed community-acquired pneumonia were recruited and clinical symptoms and management data were collected. C-reactive protein (CRP), white cell counts (WCC) and absolute neutrophil counts (ANC) were measured as part of routine care. Clinical characteristics and biomarker levels were compared between cases with definite bacterial pneumonia (clinical empyema and/or bacteria detected in blood or pleural fluid), presumed viral pneumonia (presence of ≥1 virus in nasopharyngeal swab without criteria for definite bacterial pneumonia), and other pneumonia cases (pneumonia in the absence of criteria for either definite bacterial or presumed viral pneumonia). The area-under-curve (AUC) of the receiver operating characteristic (ROC) curve for varying biomarker levels were used to characterise their utility for discriminating definite bacterial from presumed viral pneumonia. For biomarkers with AUC > 0.8 (fair discriminator), Youden index was measured to determine the optimal cut-off threshold, and sensitivity, specificity, predictive values (positive and negative) were calculated. We investigated whether better discrimination could be achieved by combining biomarker values with the presence/absence of symptoms. Results From May 2015 to October 2017, 230 pneumonia cases were enrolled: 30 with definite bacterial pneumonia, 118 with presumed viral pneumonia and 82 other pneumonia cases. Differences in clinical signs and symptoms across the groups were noted; more definite bacterial pneumonia cases required intravenous fluid and oxygen supplementation than presumed viral or other pneumonia cases. CRP, WCC and ANC were substantially higher in definite bacterial cases. For a CRP threshold of 72 mg/L, the AUC of ROC was 0.82 for discriminating definite bacterial pneumonia from presumed viral pneumonia. Combining the CRP with either the presence of fever (≥38 ο C) or the absence of rhinorrhea improved the discrimination. Conclusions Combining elevated CRP with the presence or absence of clinical signs/ symptoms differentiates definite bacterial from presumed viral pneumonia better than CRP alone. Further studies are required to explore combination of biomarkers and symptoms for use as definitive diagnostic tool.

IntroductionRespiratory pathogens associated with childhood pneumonia are often detected in the upper respiratory tract of healthy children, making their contribution to pneumonia difficult to determine. We aimed to determine the contribution of common pathogens to pneumonia adjusting for rates of asymptomatic detection to inform future diagnosis, treatment and preventive strategies.MethodsA case–control study was conducted among children <18 years in Perth, Western Australia. Cases were children hospitalised with radiologically confirmed pneumonia; controls were healthy children identified from outpatient and local immunisation clinics. Nasopharyngeal swabs were collected and tested for 14 respiratory viruses and 6 bacterial species by Polymerase chain reaction (PCR). For each pathogen, adjusted odds ratio (aOR; 95% CI) was calculated using multivariate logistic regression and population-attributable fraction (95% CI) for pneumonia was estimated.ResultsFrom May 2015 to October 2017, 230 cases and 230 controls were enrolled. At least one respiratory virus was identified in 57% of cases and 29% of controls (aOR: 4.7; 95% CI: 2.8 to 7.8). At least one bacterial species was detected in 72% of cases and 80% of controls (aOR: 0.7; 95% CI: 0.4 to 1.2). Respiratory syncytial virus (RSV) detection was most strongly associated with pneumonia (aOR: 58.4; 95% CI: 15.6 to 217.5). Mycoplasma pneumoniae was the only bacteria associated with pneumonia (aOR: 14.5; 95% CI: 2.2 to 94.8). We estimated that RSV, human metapneumovirus (HMPV), influenza, adenovirus and Mycoplasma pneumoniae were responsible for 20.2% (95% CI: 14.6 to 25.5), 9.8% (5.6% to 13.7%), 6.2% (2.5% to 9.7%), 4% (1.1% to 7.1%) and 7.2% (3.5% to 10.8%) of hospitalisations for childhood pneumonia, respectively.ConclusionsRespiratory viruses, particularly RSV and HMPV, are major contributors to pneumonia in Australian children.

Background Despite international guidelines providing evidence-based recommendations on appropriate management of infants with bronchiolitis, wide variation in practice occurs. This results in infants receiving care of no benefit, with associated cost and is potentially harmful. Theoretical frameworks are increasingly used to develop interventions, utilising behaviour change techniques specifically chosen to target factors contributing to practice variation, with de-implementation often viewed as harder than implementing. This paper describes the stepped process using the Theoretical Domains Framework (TDF) to develop targeted, theory-informed interventions which subsequently successfully improved management of infants with bronchiolitis by de-implementing ineffective therapies. Explicit description of the process and rationale used in developing de-implementation interventions is critical to dissemination of these practices into real world clinical practice. Methods A stepped approach was used: (1) Identify evidence-based recommendations and practice variation as targets for change, (2) Identify factors influencing practice change (barriers and enablers) to be addressed, and (3) Identification and development of interventions (behaviour change techniques and methods of delivery) addressing influencing factors, considering evidence of effectiveness, feasibility, local relevance and acceptability. The mode of delivery for the intervention components was informed by evidence from implementation science systematic reviews, and setting specific feasibility and practicality. Results Five robust evidence-based management recommendations, targeting the main variation in bronchiolitis management were identified: namely, no use of chest x-ray, salbutamol, glucocorticoids, antibiotics, and adrenaline. Interventions developed to target recommendations addressed seven TDF domains (identified following qualitative clinician interviews ( n  = 20)) with 23 behaviour change techniques chosen to address these domains. Final interventions included: (1) Local stakeholder meetings, (2) Identification of medical and nursing clinical leads, (3) Train-the-trainer workshop for all clinical leads, (4) Local educational materials for delivery by clinical leads, (5) Provision of tools and materials targeting influencing factors, and prompting recommended behaviours, and (6) Audit and feedback. Conclusion A stepped approach based on theory, evidence and issues of feasibility, local relevance and acceptability, was successfully used to develop interventions to improve management of infants with bronchiolitis. The rationale and content of interventions has been explicitly described allowing others to de-implement unnecessary bronchiolitis management, thereby improving care.

Background Diagnosing urinary tract infections (UTIs) in children in the emergency department (ED) is challenging due to the variable clinical presentations and difficulties in obtaining a urine sample free from contamination. Clinicians need to weigh a range of observations to make timely diagnostic and management decisions, a difficult task to achieve without support due to the complex interactions among relevant factors. Directed acyclic graphs (DAG) and causal Bayesian networks (BN) offer a way to explicitly outline the underlying disease, contamination and diagnostic processes, and to further make quantitative inference on the event of interest thus serving as a tool for decision support. Methods We prospectively collected data on children present to ED with suspected UTIs. Through knowledge elicitation workshops and one-on-one meetings, a DAG was co-developed with clinical domain experts (the Expert DAG) to describe the causal relationships among variables relevant to paediatric UTIs. The Expert DAG was combined with prospective data and further domain knowledge to inform the development of an application-oriented BN (the Applied BN), designed to support the diagnosis of UTI. We assessed the performance of the Applied BN using quantitative and qualitative methods. Results We summarised patient background, clinical and laboratory characteristics of 431 episodes of suspected UTIs enrolled from May 2019 to November 2020. The Expert DAG was presented with a narrative description, elucidating how infection, specimen contamination and management pathways causally interact to form the complex picture of paediatric UTIs. Parameterised using prospective data and expert-elicited parameters, the Applied BN achieved an excellent and stable performance in predicting Escherichia coli culture results, with a mean area under the receiver operating characteristic curve of 0.86 and a mean log loss of 0.48 based on 10-fold cross-validation. The BN predictions were reviewed via a validation workshop, and we illustrate how they can be presented for decision support using three hypothetical clinical scenarios. Conclusion Causal BNs created from both expert knowledge and data can integrate case-specific information to provide individual decision support during the diagnosis of paediatric UTIs in ED. The model aids the interpretation of culture results and the diagnosis of UTIs, promising the prospect of improved patient care and judicious use of antibiotics.