Abstract

BackgroundPatients’ evolving critical illness can be predicted and prevented. However, failure to identify the signs of critical illness and subsequent lack of appropriate action for patients developing acute and critical illness remain a problem. Challenges in assessing whether a child is critically ill may be due to children’s often uncharacteristic symptoms of serious illness. Children may seem relatively unaffected until shortly before circulatory and respiratory failure and cardiac arrest.The Bedside Paediatric Early Warning Score has been validated in a large multinational study and is used in two regions in Denmark. However, healthcare professionals experience difficulties in relation to measuring blood pressure and to the lack of assessment of children’s level of consciousness. In addition, is it noteworthy that in 23,288-hour studies, all seven items of the Bedside Paediatric Early Warning Score were recorded in only 5.1% of patients.This trial aims to compare two Paediatric Early Warning Score (PEWS) models to identify the better model for identifying acutely and critically ill children. The hypothesis is that the Central Denmark Region PEWS model is superior to the Bedside PEWS in terms of reducing unplanned transfers to intensive care or transfers from regional hospitals to the university hospital among already hospitalised children.Methods/designThis is a multicentre, randomised, controlled clinical trial where children are allocated to one of two different PEWS models. The study involves all paediatric departments and one emergency department in the Central Denmark Region. The primary outcome is unplanned transfer to the paediatric intensive care unit or transfer from regional hospitals to the university hospital. Based on preliminary data, 14,000 children should be included to gain a power of 80% (with a 5% significance level) and to detect a clinically significant difference of 30% of unplanned transfers to intensive care or from regional hospitals to the paediatric department at the university department. A safety interim analysis will be performed after inclusion of 7000 patients.DiscussionThis is the first randomised trial to investigate two different PEWS models. This study demonstrates the safety and effectiveness of a new PEWS model and contributes to knowledge of hospitalised children’s clinical deterioration.Trial registrationClinicalTrials.gov, NCT02433327. Registered on 27 April 2015.

Highlights

  • Patients’ evolving critical illness can be predicted and prevented

  • This study demonstrates the safety and effectiveness of a new Paediatric Early Warning Score (PEWS) model and contributes to knowledge of hospitalised children’s clinical deterioration

  • Hypothesis The hypothesis is that the Central Denmark Region PEWS is superior to the Bedside PEWS in terms of reducing hospitalised children’s unplanned transfers to the intensive care unit and transfers from regional hospitals to the university hospital due to clinical deterioration requiring proximity to a paediatric intensive care unit (PICU)

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Summary

Discussion

National and international models for early warning systems in adults exist [2, 18]. several international reports have shown that failure to identify the signs of critical illness and subsequent lack of appropriate action for patients developing acute and critical illness remain a problem [19, 20]. In a retrospective case control study, Zhai et al [26] used transfers to the PICU to develop an electronic health record-based automated algorithm and compared its effectiveness with that of two PEWS tools. The development and implementation of the PEWS may prevent acute decompensation and the need for a higher level of care It will help with early recognition and intervention on children at risk of deteriorating. Ethics approval and consent to participate The trial participants will be screened and randomised to one of the PEWS arms upon admission. Informed consent from both parents will subsequently be obtained as soon as possible.

Background
Objective
Methods/design
Data from PICU
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