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Background Paediatric early warning systems (PEWS) are a means of tracking physiological state and alerting healthcare professionals about signs of deterioration, triggering a clinical review and/or escalation of care of children. A proactive end-to-end deterioration solution (the DETECT surveillance system) with an embedded e-PEWS that included sepsis screening was introduced across a tertiary children’s hospital. One component of the implementation programme was a sub-study to determine an understanding of the DETECT e-PEWS in terms of its clinical utility and its acceptability. Aim This study aimed to examine how parents and health professionals view and engage with the DETECT e-PEWS apps, with a particular focus on its clinical utility and its acceptability. Method A prospective, closed (tick box or sliding scale) and open (text based) question, e-survey of parents (n = 137) and health professionals (n = 151) with experience of DETECT e-PEWS. Data were collected between February 2020 and February 2021. Results Quantitative data were analysed using descriptive and inferential statistics and qualitative data with generic thematic analysis. Overall, both clinical utility and acceptability (across seven constructs) were high across both stakeholder groups although some challenges to utility (e.g., sensitivity of triggers within specific patient populations) and acceptability (e.g., burden related to having to carry extra technology) were identified. Conclusion Despite the multifaceted nature of the intervention and the complexity of implementation across a hospital, the system demonstrated clinical utility and acceptability across two key groups of stakeholders: parents and health professionals.

BackgroundPaediatric early warning systems (PEWS) are a means of tracking physiological state and alerting healthcare professionals about signs of deterioration, triggering a clinical review and/or escalation of care of children. A proactive end-to-end deterioration solution (the DETECT surveillance system) with an embedded e-PEWS that included sepsis screening was introduced across a tertiary children's hospital. One component of the implementation programme was a sub-study to determine an understanding of the DETECT e-PEWS in terms of its clinical utility and its acceptability.AimThis study aimed to examine how parents and health professionals view and engage with the DETECT e-PEWS apps, with a particular focus on its clinical utility and its acceptability.MethodA prospective, closed (tick box or sliding scale) and open (text based) question, e-survey of parents (n = 137) and health professionals (n = 151) with experience of DETECT e-PEWS. Data were collected between February 2020 and February 2021.ResultsQuantitative data were analysed using descriptive and inferential statistics and qualitative data with generic thematic analysis. Overall, both clinical utility and acceptability (across seven constructs) were high across both stakeholder groups although some challenges to utility (e.g., sensitivity of triggers within specific patient populations) and acceptability (e.g., burden related to having to carry extra technology) were identified.ConclusionDespite the multifaceted nature of the intervention and the complexity of implementation across a hospital, the system demonstrated clinical utility and acceptability across two key groups of stakeholders: parents and health professionals.

ObjectiveBacterial Infections remains a leading cause of death in the Paediatric Intensive Care Unit (PICU). In this era of rising antimicrobial resistance, new tools are needed to guide antimicrobial use. The aim of this study was to investigate the accuracy of procalcitonin (PCT), neutrophil gelatinase-associated lipocalin (NGAL), resistin, activated partial thromboplastin time (aPTT) waveform and C-reactive protein (CRP) for the diagnosis of serious bacterial infection (SBI) in children on admission to PICU and their use as prognostic indicators.SettingA regional PICU in the United Kingdom.PatientsConsecutive PICU admissions between October 2010 and June 2012.MeasurementsBlood samples were collected daily for biomarker measurement. The primary outcome measure was performance of study biomarkers for diagnosis of SBI on admission to PICU based on clinical, radiological and microbiological criteria. Secondary outcomes included durations of PICU stay and invasive ventilation and 28-day mortality. Patients were followed up to day 28 post-admission.Main resultsA total of 657 patients were included in the study. 92 patients (14%) fulfilled criteria for SBI. 28-day mortality was 2.6% (17/657), but 8.7% (8/92) for patients with SBI. The combination of PCT, resistin, plasma NGAL and CRP resulted in the greatest net reclassification improvement compared to CRP alone (0.69, pConclusionCombinations of biomarkers, including PCT, may improve accurate and timely identification of SBI on admission to PICU.

Acute kidney injury (AKI), a common complication in paediatric intensive care units (PICU), is associated with increased morbidity and mortality. In this single centre, prospective, observational cohort study, neutrophil gelatinase-associated lipocalin in urine (uNGAL) and plasma (pNGAL) and renal angina index (RAI), and combinations of these markers, were assessed for their ability to predict severe (stage 2 or 3) AKI in children and young people admitted to PICU. In PICU children and young people had initial and serial uNGAL and pNGAL measurements, RAI calculation on day 1, and collection of clinical data, including serum creatinine measurements. Primary outcomes were severe AKI and renal replacement therapy (RRT). Secondary outcomes were length of stay, hospital acquired infection and mortality. The area under the Receiver Operating Characteristic (ROC) curves and Youden index was used to determine biomarker performance and identify optimum cut-off values. Of 657 children recruited, 104 met criteria for severe AKI (15∙8%) and 47 (7∙2%) required RRT. Severe AKI was associated with increased length of stay, hospital acquired infection, and mortality. The area under the curve (AUC) for severe AKI prediction for Day 1 uNGAL, Day 1 pNGAL and RAI were 0.75 (95% Confidence Interval [CI] 0∙69, 0∙81), 0∙64 (95% CI 0∙56, 0∙72), and 0.73 (95% CI 0∙65, 0∙80) respectively. The optimal combination of measures was RAI and day 1 uNGAL, giving an AUC of 0∙80 for severe AKI prediction (95% CI 0∙71, 0∙88). In this heterogenous PICU cohort, urine or plasma NGAL in isolation had poorer prediction accuracy for severe AKI than in previously reported homogeneous populations. However, when combined together with RAI, they produced good prediction for severe AKI.